HMDB: a knowledgebase for the human metabolome

Ferrous ascorbate as a potential biomarker for diabetic retinopathy: a vitreous humour metabolomics study

BACKGROUND

This study aimed to explore differences in vitreous humour metabolites and metabolic pathways between patients with and without diabetic retinopathy (DR) and identify potential metabolite biomarkers.

METHODS

Clinical data and vitreous fluid samples were collected from 125 patients (40 without diabetes, 85 with DR). The metabolite profiles of the vitreous fluid samples were analysed using ultra-high performance liquid chromatography, Q-Exactive mass spectrometry, and multivariate statistical analysis. A machine learning model based on Least Absolute Shrinkage and Selection Operator Regularized logistic regression was used to build a risk scoring model based on selected metabolite levels. Candidate metabolites were regressed to glycated haemoglobin levels by a logistic regression model.

RESULTS

Twenty differential metabolites were identified between the DR and control groups and were significantly enriched in five Kyoto Encyclopedia of Genes and Genomes pathways (arginine biosynthesis; tricarboxylic acid cycle; alanine, aspartate, and glutamate metabolism; tyrosine metabolism; and D-glutamate metabolism). Ferrous ascorbate significantly contributes to poorer glycaemic control outcomes, offering insights into potential new pathogenic pathways in DR.

CONCLUSIONS

Disorders in the metabolic pathways of arginine biosynthesis, tricarboxylic acid cycle, alanine, aspartate, glutamate metabolism, tyrosine metabolism, and D-glutamate metabolism were associated with DR. Risk scores based on vitreous fluid metabolites can be used for the diagnosis and management of DR. Ferrous ascorbate can provide insights into potential new pathogenic pathways for DR.

Mitochondrial defects and metabolic vulnerabilities in Lynch syndrome-associated MSH2-deficient endometrial cancer

Lynch syndrome (LS) is defined by inherited mutations in DNA mismatch repair genes, including MSH2, and carries 60% lifetime risk of developing endometrial cancer (EC). Beyond hypermutability, specific mechanisms for LS-associated endometrial carcinogenesis are not well understood. Here, we assessed the effects of MSH2 loss on EC pathogenesis using a novel mouse model (PR-Cre Msh2 flox/flox , abbreviated Msh2KO), primary cell lines established from this model, human tissues, and human EC cell lines with isogenic MSH2 knockdown. Beginning at eight months of age, 30% of Msh2KO mice exhibited endometrial atypical hyperplasia (AH), a precancerous lesion. At 12 to 16 months of age, 47% of Msh2KO mice exhibited either AH or ECs with histologic features similar to human LS-related ECs. Transcriptomic profiling of EC from Msh2KO mice revealed a transcriptomic signature for mitochondrial dysfunction. Studies in vitro and in vivo revealed mitochondrial dysfunction based upon two mechanisms: marked mitochondrial content reduction, along with pronounced disruptions to the integrity of retained mitochondria. Human LS-related ECs also exhibited mitochondrial content reduction compared with non-LS-related ECs. Functional studies revealed metabolic reprogramming of MSH2-deficient EC cells in vitro , including reduced oxidative phosphorylation and increased susceptibility to glycolysis suppression. We are the first to identify mitochondrial dysfunction and metabolic disruption as a consequence of MSH2 deficiency-related EC. Mitochondrial and metabolic aberrations should be evaluated as novel biomarkers for endometrial carcinogenesis or risk stratification and could serve as targets for cancer interception in women with LS.

Significance

This is the first study to report mitochondrial dysfunction contributing to MSH2-deficient endometrial cancer development, identifying a noncanonical pathway for MSH2 deficient carcinogenesis, which also imparts vulnerability to metabolic targeting.

Structure of prolylrapamycin: confirmation through a revised and detailed NMR assignment study

A complete and detailed characterization of Rapamycin (1) and Prolylrapamycin (2) has been conducted by homo- and hetero-nuclear NMR experiments in DMSO-d6 along with HRMS and FT-IR spectra and DSCs analyses. The NMR experiments allowed the assignment of every single proton and carbon atom belonging to the two structures and the definitive confirm of the presence of a pyrrolidine ring in Prolylrapamycin (2) in place of the piperidine ring that characterizes the structure of Sirolimus.

Plasma Metabolite Profiling Identifies Nondiabetic Chronic Pancreatitis Patients With Metabolic Alterations Progressing to Prediabetes Before HbA1c

INTRODUCTION

Diabetes (T3cDM) secondary to chronic pancreatitis (CP) arises due to endocrine dysfunction and metabolic dysregulations. Currently, diagnostic tests are not available to identify patients who may progress from normoglycemia to hyperglycemia in CP. We conducted plasma metabolomic profiling to diagnose glycemic alterations early in the course of disease.

METHODS

Liquid chromatography-tandem mass spectrometry was used to generate untargeted, targeted plasma metabolomic profiles in patients with CP, controls (n = 445) following TRIPOD guidelines. Patients were stratified based on glucose tolerance tests following ADA guidelines. Multivariate analysis was performed using partial least squares discriminant analysis to assess discriminatory ability of metabolites among stratified groups. COMBIROC and logistic regression were used to derive biomarker signatures. AI-ML tool (Rapidminer) was used to verify these preliminary results.

RESULTS

Ceramide, lysophosphatidylethanolamine, phosphatidylcholine, lysophosphatidic acid (LPA), phosphatidylethanolamine, carnitine, and lysophosphatidylcholine discriminated T3cDM CP patients from healthy controls with AUC 93% (95% CI 0.81-0.98, P < 0.0001), and integration with pancreatic morphology improved AUC to 100% (95% CI 0.93-1.00, P < 0.0001). LPA, phosphatidylinositol, and ceramide discriminated nondiabetic CP with glycemic alterations (pre-diabetic CP); AUC 66% (95% CI 0.55-0.76, P = 0.1), and integration enhanced AUC to 74% (95% CI 0.55-0.88, P = 0.86). T3cDM was distinguished from prediabetic by LPA, phosphatidylinositol, and sphinganine (AUC 70%; 95% CI 0.54-0.83, P = 0.08), and integration improved AUC to 83% (95% CI 0.68-0.93, P = 0.05). CombiROC cutoff identified 75% and 78% prediabetes in validation 1 and 2 cohorts. Random forest algorithm assessed performance of integrated panel demonstrating AUC of 72% in predicting glycemic alterations.

DISCUSSION

We report for the first time that a panel of metabolites integrated with pancreatic morphology detects glycemia progression before HbA1c in patients with CP.

An Optimized Method for LC-MS-Based Quantification of Endogenous Organic Acids: Metabolic Perturbations in Pancreatic Cancer

Accurate and reliable quantification of organic acids with carboxylic acid functional groups in complex biological samples remains a major analytical challenge in clinical chemistry. Issues such as spontaneous decarboxylation during ionization, poor chromatographic resolution, and retention on a reverse-phase column hinder sensitivity, specificity, and reproducibility in multiple-reaction monitoring (MRM)-based LC-MS assays. We report a targeted metabolomics method using phenylenediamine derivatization for quantifying carboxylic acid-containing metabolites (CCMs). This method achieves accurate and sensitive quantification in various biological matrices, with recovery rates from 90% to 105% and CVs ≤ 10%. It shows linearity from 0.1 ng/mL to 10 µg/mL with linear regression coefficients of 0.99 and LODs as low as 0.01 ng/mL. The library included a wide variety of structurally variant CCMs such as amino acids/conjugates, short- to medium-chain organic acids, di/tri-carboxylic acids/conjugates, fatty acids, and some ring-containing CCMs. Comparing CCM profiles of pancreatic cancer cells to normal pancreatic cells identified potential biomarkers and their correlation with key metabolic pathways. This method enables sensitive, specific, and high-throughput quantification of CCMs from small samples, supporting a wide range of applications in basic, clinical, and translational research.

Mendelian randomization analysis reveals causal associations of serum metabolites with sepsis and 28-day mortality

Metabolic disorder has been found to be an important factor in the pathogenesis and progression of sepsis. However, the causation of such an association between serum metabolites and sepsis has not been established. We conducted a two-sample Mendelian randomization (MR) study. A genome-wide association study of 486 human serum metabolites was used as the exposure, whereas sepsis and sepsis mortality within 28 days were set as the outcomes. In MR analysis, 6 serum metabolites were identified to be associated with an increased risk of sepsis, and 6 serum metabolites were found to be related to a reduced risk of sepsis. Furthermore, there were 9 metabolites positively associated with sepsis-related mortality, and 8 metabolites were negatively correlated with sepsis mortality. In addition, "glycolysis/gluconeogenesis" (p = 0.001), and "pyruvate metabolism" (p = 0.042) two metabolic pathways were associated with the incidence of sepsis. This MR study suggested that serum metabolites played significant roles in the pathogenesis of sepsis, which may provide helpful biomarkers for early disease diagnosis, therapeutic interventions, and prognostic assessments for sepsis.

Metabolomic analysis reveals the biological characteristics of giant congenital melanocytic nevi

Giant congenital melanocytic nevi (GCMN) is a congenital cutaneous developmental deformity tumor that usually occurs at birth or in the first few weeks after birth, but its pathogenesis is still unclear. In this study, nuclear magnetic resonance-based metabolomics strategy was employed to evaluate the metabolic variations in serum and urine of the GCMN patients in order to understand its underlying biochemical mechanism and provide a potential intervention idea. Twenty-nine metabolites were observed to change significantly in serum and urine metabolomes, which are mainly involved in a variety of metabolic pathways including glyoxylate and dicarboxylate metabolism, TCA cycle and metabolisms of amino acids. The substantial cores of all the disturbed metabolic pathways are related to amino acid metabolism and carbohydrate metabolism and regulate the physiological state of the GCMN patients. Our results provide the physiological basis and physiological responses of GCMN and will be helpful for better understanding the molecular mechanisms of GCMN in future research.

Rats Orally Administered with Ethyl Alcohol for a Prolonged Time Show Histopathology of the Epididymis and Seminal Vesicle Together with Changes in the Luminal Metabolite Composition

Prolonged ethanol (EtOH) consumption is associated with male infertility, with a decreased spermatogenesis rate as one cause. The defective maturation and development of sperm during their storage in the cauda epididymis and transit in the seminal vesicle can be another cause, possibly occurring before the drastic spermatogenesis disruption. Herein, we demonstrated that the cauda epididymis and seminal vesicle of rats, orally administered with EtOH under a regimen in which spermatogenesis was still ongoing, showed histological damage, including lesions, a decreased height of the epithelial cells and increased collagen fibers in the muscle layer, which implicated fibrosis. Lipid peroxidation (shown by malondialdehyde (MDA) levels) was observed, indicating that reactive oxygen species (ROS) were produced along with acetaldehyde during EtOH metabolism by CYP2E1. MDA, acetaldehyde and other lipid peroxidation products could further damage cellular components of the cauda epididymis and seminal vesicle, and this was supported by increased apoptosis (shown by a TUNEL assay and caspase 9/caspase 3 expression) in these two tissues of EtOH-treated rats. Consequently, the functionality of the cauda epididymis and seminal vesicle in EtOH-treated rats was impaired, as demonstrated by a decreases in 1H NMR-analyzed metabolites (e.g., carnitine, fructose), which were important for sperm development, metabolism and survival in their lumen.

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.

Paternal microbiome perturbations impact offspring fitness

The gut microbiota operates at the interface of host-environment interactions to influence human homoeostasis and metabolic networks1-4. Environmental factors that unbalance gut microbial ecosystems can therefore shape physiological and disease-associated responses across somatic tissues5-9. However, the systemic impact of the gut microbiome on the germline-and consequently on the F1 offspring it gives rise to-is unexplored10. Here we show that the gut microbiota act as a key interface between paternal preconception environment and intergenerational health in mice. Perturbations to the gut microbiota of prospective fathers increase the probability of their offspring presenting with low birth weight, severe growth restriction and premature mortality. Transmission of disease risk occurs via the germline and is provoked by pervasive gut microbiome perturbations, including non-absorbable antibiotics or osmotic laxatives, but is rescued by restoring the paternal microbiota before conception. This effect is linked with a dynamic response to induced dysbiosis in the male reproductive system, including impaired leptin signalling, altered testicular metabolite profiles and remapped small RNA payloads in sperm. As a result, dysbiotic fathers trigger an elevated risk of in utero placental insufficiency, revealing a placental origin of mammalian intergenerational effects. Our study defines a regulatory 'gut-germline axis' in males, which is sensitive to environmental exposures and programmes offspring fitness through impacting placenta function.

1H-NMR Metabolomic Study of the Mushroom Pleurotus djamor for the Identification of Nematocidal Compounds

Due to the increasing populations of anthelmintic-resistant gastrointestinal nematodes and as a consequence of the adverse effects of synthetic drugs, this study focuses on the search for secondary metabolites with nematocidal activity from the edible mushroom Pleurotus djamor using The proton nuclear magnetic resonance (1H-NMR) metabolomics. The highest activity was shown by the ethyl acetate fractions of mycelium (EC50 290.8 µg/mL) and basidiomes (EC50 282.7 µg/mL). Principal component analysis (PCA) and hierarchical data analysis (HCA) of the 1H-NMR metabolic profiles data showed that the ethanolic extracts, the ethyl acetate, butanol, and water fractions from mycelium have different metabolic profiles than those from basidiomes, while low polarity (hexane) fractions from both stages of fungal development show similar profiles. Orthogonal partial least squares discriminant analysis (OPLS-DA) allowed the identification of signals in the 1H-NMR metabolic profile associated with nematocidal activity. The signals yielded via OPLS-DA and bidimensional NMR analysis allowed the identification of uracil as a component in the ethyl acetate fraction from basidiomes, with an EC50 of 237.7 µg/mL. The results obtained showed that chemometric analyses of the 1H-NMR metabolic profiles represent a viable strategy for the identification of bioactive compounds from samples with complex chemical profiles.

Anticancer properties and metabolomic profiling of Shorea roxburghii extracts toward gastrointestinal cancer cell lines

BACKGROUND

Gastrointestinal cancer (GIC) ranks as the highest cause of cancer-related deaths globally. GIC patients are often diagnosed at advanced stages, limiting effective treatment options. Chemotherapy, the common GIC recommendation, has significant disadvantages such as toxicity and adverse effects. Natural products contain substances with diverse pharmacological characteristics that promise for use in cancer therapeutics. In this study, the flower of renowned Asian medicinal plant, Shorea roxburghii was collected and extracted to investigate its phytochemical contents, antioxidant, and anticancer properties on GIC cells.

METHODS

The phytochemical contents of Shorea roxburghii extract were assessed using suitable methods. Phenolic content was determined through the Folin-Ciocalteu method, while flavonoids were quantified using the aluminum chloride (AlCl3) method. Antioxidant activity was evaluated using the FRAP and DPPH assays. Cytotoxicity was assessed in GIC cell lines via the MTT assay. Additionally, intracellular ROS levels and apoptosis were examined through flow cytometry techniques. The correlation between GIC cell viability and phytochemicals, 1H-NMR analysis was conducted.

RESULTS

Among the four different solvent extracts, ethyl acetate extract had the highest phenolic and flavonoid contents. Water extract exhibited the strongest reducing power and DPPH scavenging activity following by ethyl acetate. Interestingly, ethyl acetate extract demonstrated the highest inhibitory activity against three GIC cell lines (KKU-213B, HepG2, AGS) with IC50 values of 91.60 µg/ml, 39.38 µg/ml, and 35.59 µg/ml, while showing less toxicity to normal fibroblast cells. Ethyl acetate extract induced reactive oxygen species and apoptosis in GIC cell lines by downregulating anti-apoptotic protein Bcl-2. Metabolic profiling-based screening revealed a positive association between reduced GIC cell viability and phytochemicals like cinnamic acid and its derivatives, ferulic acid and coumaric acid.

CONCLUSIONS

This study highlights the potential of natural compounds in Shorea roxburghii in the development of more effective and safer anticancer agents as options for GIC as well as shedding light on new avenues for cancer treatment.

Metabolic difference between patient-derived xenograft model of pancreatic ductal adenocarcinoma and corresponding primary tumor

BACKGROUND

Patients-derived xenograft (PDX) model have been widely used for tumor biological and pathological studies. However, the metabolic similarity of PDX tumor to the primary cancer (PC) is still unknown.

METHODS

In present study, we established PDX model by engrafting primary tumor of pancreatic ductal adenocarcinoma (PDAC), and then compared the tumor metabolomics of PC, the first generation of PDX tumor (PDXG1), and the third generation of PDX tumor (PDXG3) by using 1H NMR spectroscopy. Then, we assessed the differences in response to chemotherapy between PDXG1 and PDXG3 and corresponding metabolomic differences in drug-resistant tumor tissues. To evaluate the metabolomic similarity of PDX to PC, we also compared the metabolomic difference of cell-derived xenograft (CDX) vs. PC and PDX vs. PC.

RESULTS

After engraftment, PDXG1 tumor had a low level of lactate, pyruvate, citrate and multiple amino acids (AAs) compared with PC. Metabolite sets enrichment and metabolic pathway analyses implied that glycolysis metabolisms were suppressed in PDXG1 tumor, and tricarboxylic acid cycle (TCA)-associated anaplerosis pathways, such as amino acids metabolisms, were enhanced. Then, after multiple passages of PDX, the altered glycolysis and TCA-associated anaplerosis pathways were partially recovered. Although no significant difference was observed in the response of PDXG1 and PDXG3 to chemotherapy, the difference in glycolysis and amino acids metabolism between PDXG1 and PDXG3 could still be maintained. In addition, the metabolomic difference between PC and CDX models were much larger than that of PDX model and PC, indicating that PDX model still retain more metabolic characteristics of primary tumor which is more suitable for tumor-associated metabolism research.

CONCLUSIONS

Compared with primary tumor, PDX models have obvious difference in metabolomic level. These findings can help us design in vivo tumor metabolomics research legitimately and analyze the underlying mechanism of tumor metabolic biology thoughtfully.

CoMentG: comprehensive retrieval of generic relationships between biomedical concepts from the scientific literature

The CoMentG resource contains millions of relationships between terms of biomedical interest obtained from the scientific literature. At the core of the system is a methodology for detecting significant co-mentions of concepts in the entire PubMed corpus. That method was applied to nine sets of terms covering the most important classes of biomedical concepts: diseases, symptoms/clinical signs, molecular functions, biological processes, cellular compartments, anatomic parts, cell types, bacteria and chemical compounds. We obtained more than 7 million relationships between more than 74 000 terms, and many types of relationships were not available in any other resource. As the terms were obtained from widely used resources and ontologies, the relationships are given using the standard identifiers provided by them and hence can be linked to other data. A web interface allows users to browse these associations, searching for relationships for a set of terms of interests provided as input, such as between a disease and their associated symptoms, underlying molecular processes or affected tissues. The results are presented in an interactive interface where the user can explore the reported relationships in different ways and follow links to other resources. Database URL: https://csbg.cnb.csic.es/CoMentG/.

Mitochondrial complex I activity in microglia sustains neuroinflammation

Sustained smouldering, or low-grade activation, of myeloid cells is a common hallmark of several chronic neurological diseases, including multiple sclerosis1. Distinct metabolic and mitochondrial features guide the activation and the diverse functional states of myeloid cells2. However, how these metabolic features act to perpetuate inflammation of the central nervous system is unclear. Here, using a multiomics approach, we identify a molecular signature that sustains the activation of microglia through mitochondrial complex I activity driving reverse electron transport and the production of reactive oxygen species. Mechanistically, blocking complex I in pro-inflammatory microglia protects the central nervous system against neurotoxic damage and improves functional outcomes in an animal disease model in vivo. Complex I activity in microglia is a potential therapeutic target to foster neuroprotection in chronic inflammatory disorders of the central nervous system3.

The effects of residual dipolar coupling on carnosine in proton muscle spectra

Carnosine, an MR-visible dipeptide in human muscle, is well characterized by two peaks at ~8 and ~7 ppm from C2 and C4 imidazole protons. Like creatine and other metabolites, carnosine is subject to residual dipolar coupling in the anisotropic environment of muscle fibers, but the effects have not been studied extensively. Single-voxel TE 30-32 PRESS spectra from three different 3T studies were acquired from gastrocnemius medialis and soleus muscles in the human lower leg. In these studies, carnosine T2 values were measured, and spectra were obtained at three different foot angles. LCModel was used to fit the carnosine peaks with a basis set that was generated using shaped RF pulses and included a range of dipolar couplings affecting the C4 peak. A seven-parameter analytic expression was used to fit the CH2 doublets of creatine. It incorporated an optimized "effective TE" value to model the effect of shaped RF pulses. The fits confirm that the triplet C4 peak of carnosine is dipolar coupled to a pair of CH2 protons, with no need to include a contribution from a separate pool of freely rotating uncoupled carnosine. Moreover, the couplings experienced by carnosine C4 protons and creatine CH2 protons are strongly correlated (R2  =  0.88, P<0.001), exhibiting a similar 3cos2 θ - 1 dependence on the angle θ between fiber orientation and B0. T2 values for the singlet C2 peak of gastrocnemius carnosine are inversely proportional to the C4 dipolar coupling strength (R2  = 0.97, P < 0.001), which in turn is a function of foot orientation. This dependence indicates that careful positioning of the foot while acquiring lower leg muscle spectra is important to obtain reproducible carnosine concentrations. As proton magnetic resonance spectroscopy of carnosine is currently used to non-invasively estimate the muscle fiber typology, these results have important implications in sport science.

Profiling of Metabolites in a Fermented Soy Dietary Supplement Reinforces its Role in the Management of Intestinal Inflammation

SCOPE

Gastro-AD (GAD) is a soy flour derived product that undergoes an industrial fermentation with Lactobacillus delbrueckii R0187 and has demonstrated clinical effects in gastroesophageal reflux and peptic ulcer symptom resolution. The aim of this study is to describe and link GAD's metabolomic profile to plausible mechanisms that manifest and explain the documented clinical outcomes.

METHODS AND RESULTS

1H NMR spectroscopy with multivariate statistical analysis is used to characterize the prefermented soy flour and GAD products. The acquired spectra are screened using various resources and the molecular assignments are confirmed using total correlation spectroscopy (TOCSY). Peaks corresponding to different metabolites are integrated and compared between the two products for relative changes. HPLC and GC are used to quantify some specific molecules. NMR analyses demonstrate significant changes in the composition of various assigned bioactive moieties. HPLC and GC analysis demonstrate deglycation of isoflavones after fermentation, resulting in estrogenically active secondary metabolites that have been previously shown to help to reduce inflammation.

CONCLUSION

The identification of bioactive molecules, such as genistein and SCFAs, capable of modulating anti-inflammatory signaling cascades in the stomach's gastric and neuroendocrine tissues can explain the reported biological effects in GAD and is supported by in vivo data.

Advancements in CHO metabolomics: techniques, current state and evolving methodologies

Background: Investigating the metabolic behaviour of different cellular phenotypes, i.e., good/bad grower and/or producer, in production culture is important to identify the key metabolite(s)/pathway(s) that regulate cell growth and/or recombinant protein production to improve the overall yield. Currently, LC-MS, GC-MS and NMR are the most used and advanced technologies for investigating the metabolome. Although contributed significantly in the domain, each technique has its own biasness towards specific metabolites or class of metabolites due to various reasons including variability in the concept of working, sample preparation, metabolite-extraction methods, metabolite identification tools, and databases. As a result, the application of appropriate analytical technique(s) is very critical. Purpose and scope: This review provides a state-of-the-art technological insights and overview of metabolic mechanisms involved in regulation of cell growth and/or recombinant protein production for improving yield from CHO cultures. Summary and conclusion: In this review, the advancements in CHO metabolomics over the last 10 years are traced based on a bibliometric analysis of previous publications and discussed. With the technical advancement in the domain of LC-MS, GC-MS and NMR, metabolites of glycolytic and nucleotide biosynthesis pathway (glucose, fructose, pyruvate and phenylalanine, threonine, tryptophan, arginine, valine, asparagine, and serine, etc.) were observed to be upregulated in exponential-phase thereby potentially associated with cell growth regulation, whereas metabolites/intermediates of TCA, oxidative phosphorylation (aspartate, glutamate, succinate, malate, fumarate and citrate), intracellular NAD+/NADH ratio, and glutathione metabolic pathways were observed to be upregulated in stationary-phase and hence potentially associated with increased cell-specific productivity in CHO bioprocess. Moreover, each of technique has its own bias towards metabolite identification, indicating their complementarity, along with a number of critical gaps in the CHO metabolomics pipeline and hence first time discussed here to identify their potential remedies. This knowledge may help in future study designs to improve the metabolomic coverage facilitating identification of the metabolites/pathways which might get missed otherwise and explore the full potential of metabolomics for improving the CHO bioprocess performances.

Isolation, Bioactivity, and Molecular Docking of a Rare Gastrodin Isocitrate and Diverse Parishin Derivatives from Gastrodia elata Blume

Gastrodia elata Blume (G. elata) is a well-known medicine food homology plant widely used in treating neurological disorders such as Alzheimer's disease (AD). Here, undiscovered gastrodin derivatives were systematically studied. Seven novel gastrodin derivatives (1-7), including a unique gastrodin isocitrate (1) and six differently substituted parishin derivatives (2-7), were isolated. Structural identification was mainly based on 1D and 2D NMR data, high-resolution ESI-MS data, and HPLC analysis. Notably, the stereochemistry of 1 was further elucidated by ECD calculations. Compounds 1 and 6 showed neuroprotective effects on the H2O2-induced PC12 cell injury model. Molecular docking analysis exhibited that 1 and 6 had good affinities with three popular AD-related targets. These findings not only enriched the chemical diversity but also revealed potential active components in G. elata.

Children with Hirschsprung disease exhibited alterations in host-microbial co-metabolism after pull-through operation

PURPOSE

This study aims to compare the fecal metabolome in post pull-through HD with and without HAEC patients and healthy young children using nuclear magnetic resonance (NMR) spectroscopy.

METHODS

Fresh fecal samples were collected from children under 5 years of age in both post-pull-through HD patients and healthy Thai children. A total of 20 fecal samples were then analyzed using NMR spectroscopy.

RESULTS

Thirty-four metabolites identified among HD and healthy children younger than 5 years were compared. HD samples demonstrated a significant decrease in acetoin, phenylacetylglutamine, and N-acetylornithine (corrected p value = 0.01, 0.04, and 0.004, respectively). Succinate and xylose significantly decreased in HD with HAEC group compared to HD without HAEC group (corrected p value = 0.04 and 0.02, respectively). Moreover, glutamine and glutamate metabolism, and alanine, aspartate, and glutamate metabolism were the significant pathways involved, with pathway impact 0.42 and 0.50, respectively (corrected p value = 0.02 and 0.04, respectively).

CONCLUSION

Differences in class, quantity, and metabolism of protein and other metabolites in young children with HD after pull-through operation were identified. Most of the associated metabolic pathways were correlated with the amino acids metabolism, which is required to maintain intestinal integrity and function.

Targeting carnitine palmitoyl transferase 1A (CPT1A) induces ferroptosis and synergizes with immunotherapy in lung cancer

Despite the successful application of immune checkpoint therapy, no response or recurrence is typical in lung cancer. Cancer stem cells (CSCs) have been identified as a crucial player in immunotherapy-related resistance. Ferroptosis, a form of cell death driven by iron-dependent lipid peroxidation, is highly regulated by cellular metabolism remolding and has been shown to have synergistic effects when combined with immunotherapy. Metabolic adaption of CSCs drives tumor resistance, yet the mechanisms of their ferroptosis defense in tumor immune evasion remain elusive. Here, through metabolomics, transcriptomics, a lung epithelial-specific Cpt1a-knockout mouse model, and clinical analysis, we demonstrate that CPT1A, a key rate-limiting enzyme of fatty acid oxidation, acts with L-carnitine, derived from tumor-associated macrophages to drive ferroptosis-resistance and CD8+ T cells inactivation in lung cancer. Mechanistically, CPT1A restrains ubiquitination and degradation of c-Myc, while c-Myc transcriptionally activates CPT1A expression. The CPT1A/c-Myc positive feedback loop further enhances the cellular antioxidant capacity by activating the NRF2/GPX4 system and reduces the amount of phospholipid polyunsaturated fatty acids through ACSL4 downregulating, thereby suppressing ferroptosis in CSCs. Significantly, targeting CPT1A enhances immune checkpoint blockade-induced anti-tumor immunity and tumoral ferroptosis in tumor-bearing mice. The results illustrate the potential of a mechanism-guided therapeutic strategy by targeting a metabolic vulnerability in the ferroptosis of CSCs to improve the efficacy of lung cancer immunotherapy.

A spectroscopic test suggests that fragment ion structure annotations in MS/MS libraries are frequently incorrect

Modern untargeted mass spectrometry (MS) analyses quickly detect and resolve thousands of molecular compounds. Although features are readily annotated with a molecular formula in high-resolution small-molecule MS applications, the large majority of them remains unidentified in terms of their full molecular structure. Collision-induced dissociation tandem mass spectrometry (CID-MS2) provides a diagnostic molecular fingerprint to resolve the molecular structure through a library search. However, for de novo identifications, one must often rely on in silico generated MS2 spectra as reference. The ability of different in silico algorithms to correctly predict MS2 spectra and thus to retrieve correct molecular structures is a topic of lively debate, for instance in the CASMI contest. Underlying the predicted MS2 spectra are the in silico generated product ion structures, which are normally not used in de novo identification, but which can serve to critically assess the fragmentation algorithms. Here we evaluate in silico generated MSn product ion structures by comparison with structures established experimentally by infrared ion spectroscopy (IRIS). For a set of three dozen product ion structures from five precursor molecules, we find that virtually all fragment ion structure annotations in three major in silico MS2 libraries (HMDB, METLIN, mzCloud) are incorrect and caution the reader against their use for structure annotation of MS/MS ions.

Riboflavin Crystals with Extremely High Water Solubility

New insights into the unique biochemical properties of riboflavin (Rf), also known as vitamin B2, are leading to the development of its use not only as a vitamin supplement but also as a potential anti-inflammatory, immunomodulatory, antioxidant, anticancer, and antiviral agent, where it may play a role as an inhibitor of viral proteinases. At the same time, the comparison of the pharmacoactivity of Rf with its known metabolites, namely, flavin mononucleotide (FMN) and flavin adenine dinucleotide (FAD), is very complicated due to its poor water solubility: 0.1-0.3 g/L versus 67 g/L for FMN and 50 g/L for FAD, which is the limiting factor for its administration in clinical practice. In this study, we report the recrystallization procedure of the type A Rf crystals into the slightly hydrophobic type B/C and a new hydrophilic crystal form that has been termed the P type. Our method of Rf crystal modification based on recrystallization from dilute alkaline solution provides an unprecedented extremely high water solubility of Rf, reaching 23.5 g/L. A comprehensive study of the physicochemical properties of type P riboflavin showed increased photodynamic therapeutic activity compared to the known types A and B/C against clinical isolates of Staphylococcus aureus, Pseudomonas aeruginosa, Escherichia coli, and Salmonella typhimurium. Importantly, our work not only demonstrates a simple and inexpensive method for the synthesis of riboflavin with high solubility, which should lead to increased bioactivity, but also opens up opportunities for improving both known and new therapeutic applications of vitamin B2.

Magnetstein: An Open-Source Tool for Quantitative NMR Mixture Analysis Robust to Low Resolution, Distorted Lineshapes, and Peak Shifts

1H NMR spectroscopy is a powerful tool for analyzing mixtures including determining the concentrations of individual components. When signals from multiple compounds overlap, this task requires computational solutions. They are typically based on peak-picking and the comparison of obtained peak lists with libraries of individual components. This can fail if peaks are not sufficiently resolved or when peak positions differ between the library and the mixture. In this paper, we present Magnetstein, a quantification algorithm rooted in the optimal transport theory that makes it robust to unexpected frequency shifts and overlapping signals. Thanks to this, Magnetstein can quantitatively analyze difficult spectra with the estimation trueness an order of magnitude higher than that of commercial tools. Furthermore, the method is easier to use than other approaches, having only two parameters with default values applicable to a broad range of experiments and requiring little to no preprocessing of the spectra.

Mitochondrial reverse electron transport in myeloid cells perpetuates neuroinflammation

Sustained smouldering, or low grade, activation of myeloid cells is a common hallmark of several chronic neurological diseases, including multiple sclerosis (MS) 1 . Distinct metabolic and mitochondrial features guide the activation and the diverse functional states of myeloid cells 2 . However, how these metabolic features act to perpetuate neuroinflammation is currently unknown. Using a multiomics approach, we identified a new molecular signature that perpetuates the activation of myeloid cells through mitochondrial complex II (CII) and I (CI) activity driving reverse electron transport (RET) and the production of reactive oxygen species (ROS). Blocking RET in pro-inflammatory myeloid cells protected the central nervous system (CNS) against neurotoxic damage and improved functional outcomes in animal disease models in vivo . Our data show that RET in myeloid cells is a potential new therapeutic target to foster neuroprotection in smouldering inflammatory CNS disorders 3 .

1H NMR-Based Metabolomics Profile of Green and Red Amaranthus Grown in Open Field versus Greenhouse Cultivation System

Traditionally, indigenous African leafy vegetables such as Amaranthus, blackjack, jute mallow, cleome monophyla, and spider plants have been conventionally and organically grown as weeds in open fields. However, the lack of land space due to the increase in population has resulted in unconventional, modern, and advanced agricultural farming. The introduction of a greenhouse has recently become the second most popular growing system alongside shade net and glasshouse to increase productivity and meet consumers' demand. Several studies on Amaranthus species have solely focused on physiological parameters and nutritional composition, leaving a huge gap on their metabolomic profile of the leaves which is crucial to comprehend when growing Amaranthus species in different cropping systems. Therefore, the study aimed to determine the influence of different cropping systems on the release of metabolites of two commonly consumed Amaranthus species in South Africa. H1 -Nuclear Magnetic Resonance (NMR) tool was used to profile the untargeted metabolites of green (Amaranthus graecizans L.) and red (Amaranthus cruentus L.) species. A total of 12 metabolites-trehalose, betaine, glutamine, choline, sucrose, caprate, adenosine, asparagine, carnitine, caffeine, aspartate, and alanine-were detected in green amaranth grown in open fields. Except for caffeine, aspartate, and caprate, which were found in the green amaranth grown in open fields, all the other metabolites were detected in the greenhouse grown once. Interestingly, allantoin, which serves as an allelochemical, was the sole distinct metabolite detected in greenhouse cultivated green amaranth. On the contrary, seven similar metabolites were quantified in red amaranth grown in both open fields and greenhouses, apart from caffeine, which was only detected in greenhouse-cultivated red amaranth.

The Effect of High-Pressure Homogenization Conditions on the Physicochemical Properties and Stability of Designed Fluconazole-Loaded Ocular Nanoemulsions

The growing interest in high-energy emulsification is a result of its scalability, which is important from an industrial perspective and allows for a more reproducible and efficient production of pharmaceutical formulations. The aim of this study was to evaluate the effect of composition, mainly a fixed surfactant/cosurfactant (Smix) ratio, their concentration, and the parameters of high-pressure homogenization (HPH) processing on the quality and stability of ophthalmic fluconazole-loaded nanoemulsions. After a physicochemical analysis of nanoemulsions containing 20% w/w of oil, as optimal conditions for the HPH process, three cycles at a pressure of 1000 bar were established, obtaining formulations with an average droplet diameter size in the range of 80.63-129.68 nm and PDI values below 0.25. While it was expected that an increasing cosurfactant concentration decreased the droplet size, in the case of formulations containing Tween 20 and 10% w/w of cosurfactants, "over-processing" was observed, identified by the droplet size and polydispersity index increase. Consecutively, the selected formulations were evaluated for in vitro drug release in Franz's cell, antifungal activity, and 30-day stability using NMR spectroscopy. An antifungal activity test showed no significant difference in the antifungal activity between optimal fluconazole-loaded nanoemulsions and a 0.3% aqueous drug solution, but previously, research showed that prepared formulations were characterized by a higher viscosity and satisfactory prolonged release compared to a control. In a 30-day stability study, it was observed that higher HLB values of the used surfactants decreased the stability of the formulations in the following order: Kolliphor EL, Tween 80, Tween 20. The NMR spectra confirmed that Kolliphor EL-based formulations ensured the higher stability of the nanoemulsion composition in comparison to Tween 80 and a better stabilizing effect of propylene glycol as a cosurfactant in comparison to PEG 200. Therefore, the optimization of HPH technology should be focused on the selection of Smix and the Smix:oil ratio in order to prepare stable formulations of high quality.

Non-targeted LC-MS/MS metabolomic profiling of human plasma uncovers a novel Mediterranean diet biomarker panel

INTRODUCTION

Consumption of a Mediterranean diet (MD) has established health benefits, and the identification of novel biomarkers could enable objective monitoring of dietary pattern adherence.

OBJECTIVES

The present investigation performed untargeted metabolomics on blood plasma from a controlled study of MD adherence, to identify novel blood-based metabolite biomarkers associated with the MD pattern, and to build a logistic regression model that could be used to characterise MD adherence.

METHODS

A hundred and thirty-five plasma samples from n = 58 patients collected at different time points were available. Using a 14-point scale MD Score (MDS) subjects were divided into 'high' or 'low' MDS adherence groups and liquid chromatography-mass spectrometry (LC-MS/MS) was applied for analysis.

RESULTS

The strongest association with MDS was pectenotoxin 2 seco acid (r = 0.53; ROC = 0.78), a non-toxic marine xenobiotic metabolite. Several lipids were useful biomarkers including eicosapentaenoic acid, the structurally related lysophospholipid (20:5(5Z,8Z,11Z,14Z,17Z)/0:0), a phosphatidylcholine (P-18:1(9Z)/16:0) and also xi-8-hydroxyhexadecanedioic acid. Two metabolites negatively correlated with MDS, these were the monoacylglycerides (0:0/16:1(9Z)/0:0) and (0:0/20:3(5Z,8Z,11Z)/0:0). By stepwise elimination we selected a panel of 3 highly discriminatory metabolites and developed a linear regression model which identified 'high MDS' individuals with high sensitivity and specificity [AUC (95% CI) 0.83 (0.76-0.97)].

CONCLUSION

Our study highlights the utility of metabolomics as an approach for developing novel panels of dietary biomarkers. Quantitative profiling of these metabolites is required to validate their utility for evaluating dietary adherence.

Synergistic effect rescue animal model from NASH caused by diet-inflammation inducer

Excessive intake of pro-inflammatory fatty acids is related to the development of insulin resistance, impaired oxidative stress enzymes, and lipid disorders, leading to inflammation and development of non-alcoholic steatohepatitis (NASH). Diet and physical exercise are considered to prevent and treat metabolic disorders caused by chronic inflammatory states (responsible for insulin resistance and diabetes type 2) in individuals with obesity and nonalcoholic fatty liver diseases (NAFLD). Our investigation tested the hypothesis that Hass avocado oil, a monounsaturated fatty acid and a source of phytosterol, may improve liver and metabolic parameters without adverse effects when combined with physical exercise. Rats ingested a high-fat diet for seven weeks and were then subjected to more six weeks with a standard diet, Hass avocado-oil ingestion, and swimming. The intervention showed significantly improvements by synergistic effect between Hass avocado-oil and swimming exercise (P < 0.05), including improving adiponectin, leptin, and fasting blood glucose levels, alleviating insulin resistance, reducing serum TNF-α, improving glutathione enzyme levels, and decreasing lipotoxicity in the liver and blood and serum triacylglycerides in blood (P < 0.05). Liver tissue markers of apoptosis and necrosis such as CK-18 filaments and dimethylamine (DMA) were significantly higher in the intervention group (P < 0.05). We were unable to fully confirm our hypothesis. Although the synergistic effects between Hass avocado-oil and the swimming regimen offer a promising chance of recovering liver health by improving 10 health biological markers, we must not ignore the cellular damage due to apoptosis and necrosis in liver cells and DMA. The data on metabolomic profile and avocado-oil-treated livers highlight the need for further investigation.

Application of segmented analysis via multivariate curve resolution with alternating least squares to 1H-nuclear magnetic resonance spectroscopy to identify different sugar sources

The different types of sugar employed in the food industry exhibit chemical similarity and are mostly dominated by sucrose. Owing to the sugar origin of and differences in production, the presence of certain minor organic compounds differs. To differentiate between sugars based on their botanical source, geographical origin, or storage conditions, commercial brown sugars and sugar beet extracts were analyzed by ¹H NMR spectroscopy applying a segmented analysis by means of multivariate curve resolution-alternating least squares (MCR-ALS). Principal component analysis and partial least squares-discriminant analysis yielded excellent differentiation between sugars from different sources after the application of this preprocessing strategy; without loss of chemical information and with direct interpretation of the results. By applying a segmented analysis via MCR-ALS to ¹H NMR sugar data, similar spectroscopic profiles could be differentiated. This improved the selectivity of ¹H NMR spectroscopy for sugar source differentiation which can be useful for industrial sugar authentication purposes.

Identification of potential biomarkers in malnutrition children with severity by 1H-NMR-based metabolomics: a preliminary study in the Chinese population

PURPOSE

Child malnutrition is a global public health problem, but the underlying pathophysiologic mechanisms with severity remain poorly understood, and the potential biomarkers served to the clinical diagnosis are still not available. This study aimed to identify the serum metabolic characteristics of malnourished children with severity.

METHODS

Fasted overnight serum samples were collected following clinical standard procedures among 275 malnourished and 199 healthy children from the Women and Children's Hospital, Xiamen University Child Health Department from July 2020 to May 2022. Nuclear magnetic resonance (NMR)-based metabolomics strategy was applied to identify the potential serum biomarkers of malnutrition from 275 malnourished children aged 4 to 84 months with mild (Mil, 199 cases), moderate (Mod, 101 cases), and severe (Sev, 7 cases) malnutrition.

RESULTS

Ten, fifteen, and fifteen differential metabolites were identified from the Mil, Mod, and Sev malnutrition groups, respectively. Eight common metabolites, including increased acetoacetate, acetone, ethanol, succinate, 3-hydroxybutyrate, and decreased alanine, methionine, and N-acetyl-glycoprotein, could be the potential biomarkers for malnourished children. The altered metabolic pathways were mainly related to energy metabolism and amino acid metabolism via the network-based pathway enrichment.

CONCLUSION

Eight potential biomarkers, including acetoacetate, acetone, ethanol, succinate, 3-hydroxybutyrate, alanine, methionine, and N-acetyl-glycoprotein, could characterize the child malnutrition. Child malnutrition-induced abnormal energy metabolism, impaired nutrition utilization and the reduced nutrient availability, and more metabolic disturbance will appear with the severity. Our results are valuable for further studies on the etiology and pathogenesis of malnutrition for clinical intervention and improvement.

Characterization of Metabolite Landscape Distinguishes Medicinal Fungus Cordyceps sinensis and other Cordyceps by UHPLC-Q Exactive HF-X Untargeted Metabolomics

Cordyceps represent a valuable class of medicinal fungi with potential utilization. The overexploitation and resource scarcity of Cordyceps sinensis (CS) have led to the emergence of Cordyceps such as Cordyceps militaris (CM) and Cordyceps cicadae (CC) as substitutes. The medicinal value of CS is often considered superior to other Cordyceps, potentially owing to differences in active ingredients. This study aimed to evaluate the differences in the composition and abundance of the primary and secondary metabolites of CS and its substitutes by untargeted metabolomics. A total of 4671 metabolites from 18 superclasses were detected. CS and its substitutes were rich in amino acids, lipids, organic acids, and their derivatives. We statistically analyzed the metabolites and found a total of 285 differential metabolites (3'-Adenylic acid, O-Adipoylcarnitine, L-Dopachrome, etc.) between CS and CC, CS and CM, and CM and CC, which are potential biomarkers. L-glutamate and glycerophospholipids were differential metabolites. A KEGG enrichment analysis indicated that the tyrosine metabolic pathway and tryptophan metabolism pathway are the most differentially expressed pathways among the three Cordyceps. In contrast, CS was enriched in a higher abundance of most lipid metabolites when compared to CM and CC, which may be an indispensable foundation for the pharmacological functions of CS. In conclusion, systematic, untargeted metabolomics analyses for CS and other Cordyceps have delivered a precious resource for insights into metabolite landscapes and predicted potential components of disease therapeutics.

Genome and transcriptome analysis of Enterococcus faecium from intestinal colonization and Enterococcus faecium from urinary tract infection

Introduction

Enterococcus faecium is a common pathogen responsible for urinary tract infections (UTIs) and often establishes extensive colonization within the intestinal tract. Our aim was to assess the genomic and transcriptomic differences between colonized E. faecium without UTI (only-colonization) and colonized E. faecium causing UTI (endogenous infections).

Method

We investigated the correlation between fecal isolates from the same patient and UTI-causing isolates using PFGE and WGS, and classified fecal isolates into two groups: those that solely colonized and those associated with endogenous urinary tract infections. We characterized the genomes of colonization-only and endogenously infected isolates by Scoary GWAS, and the transcriptomes of the isolates at 3 h urine exposure to assess pathogen-related changes.

Result

Based on PFGE and WGS, eight isolates of endogenously infected E. faecium and nine isolates of only-colonized E. faecium were characterized and carbon and nitrogen regulated metabolisms such as genes encoding the phosphotransferase (PTS) system were enriched in endogenously infected E. faecium. Transcriptome analysis revealed significant differences in gene expression in the PTS system, lysine synthesis, galactose metabolism and citrate import between endogenously infected and only-colonized E. faecium isolates, highlighting the important role of certain carbon regulatory genes in the colonization and survival of endogenously infected E. faecium.

Conclusion

In only-colonized and endogenously infected isolates, we observed differential expression patterns of genes related to carbon metabolism and amino acids, suggesting that metabolic diversity is a strategy for isolates leading to endogenous infection.

Recent Advances and Applications of Ambient Mass Spectrometry Imaging in Cancer Research: An Overview

Cancer metabolic variability has a significant impact on both diagnosis and treatment outcomes. The discovery of novel biological indicators and metabolic dysregulation, can significantly rely on comprehension of the modified metabolism in cancer, is a research focus. Tissue histology is a critical feature in the diagnostic testing of many ailments, such as cancer. To assess the surgical margin of the tumour on patients, frozen section histology is a tedious, laborious, and typically arbitrary method. Concurrent monitoring of ion images in tissues facilitated by the latest advancements in mass spectrometry imaging (MSI) is far more efficient than optical tissue image analysis utilized in conventional histopathology examination. This article focuses on the "desorption electrospray ionization (DESI)-MSI" technique's most recent advancements and uses in cancer research. DESI-MSI can provide wealthy information based on the variances in metabolites and lipids in normal and cancerous tissues by acquiring ion images of the lipid and metabolite variances on biopsy samples. As opposed to a systematic review, this article offers a synopsis of the most widely employed cutting-edge DESI-MSI techniques in cancer research.

MS/MS fingerprint comparison between adjacent generations enables substructure identification: Flavonoid glycosides as cases

MS/MS spectrum matching currently serves as a favored means to identify the concerned metabolites attributing to the accessibility of several famous databases. However, the rule that takes the entire structure into account frequently leads to "0 hit" when inquiring MS/MS (usually MS2) spectrum in the databases. Conjugation plays an important role for the high-level structural diversity of metabolites in all organisms, and a given conjugate usually consists of two or more substructures. If MS3 spectra participate in database retrieval, the structural annotation potential of those databases should be dramatically expanded via identifying substructures. Attributing to the ubiquitous distribution pattern, flavonoid glycosides were deployed as the representative family to justify whether the primary fragment ion termed as Y0+, resulted from neutral loss of glycosyl residue(s), generated identical MS3 spectrum with MS2 spectrum of the aglycone cation namely [A+H]+. Because of owning unique ability to measure MS/MS spectrum with the exactly desired exciting energy, linear ion trap chamber of Qtrap-MS was responsible for generating the desired MS3 and MS2 spectra. When taking both m/z and ion intensity features into consideration, the findings included: 1) glycosides sharing identical aglycones produced the same MS3 spectra for Y0+; 2) different MS3 spectra for Y0+ occurred amongst glycosides bearing distinct, even isomeric, aglycones; 3) isomeric aglycones generated different MS2 spectra; and 4) MS3 spectra for Y0+ agreed with MS2 spectra of [A+H]+ when comparing paired glycoside and aglycone. Together, fingerprint comparison between MS3 and MS2 spectra could structurally annotate the substructures and further advance MS/MS spectrum matching towards the identification of, but not limited to, aglycones for flavonoid glycosides.

Neurochemical Differences between 1p/19q Codeleted and Noncodeleted IDH-mutant Gliomas by in Vivo MR Spectroscopy

Background Noninvasive identification of glioma subtypes is important for optimizing treatment strategies. Purpose To compare the in vivo neurochemical profiles between isocitrate dehydrogenase (IDH) 1-mutant 1p/19q codeleted gliomas and their noncodeleted counterparts measured by MR spectroscopy at 3.0 T with a point-resolved spectroscopy (PRESS) sequence optimized for D-2-hydroxyglutarate (2HG) detection. Materials and Methods Adults with IDH1-mutant gliomas were retrospectively included for this study from two university hospitals (inclusion period: January 2015 to July 2016 and September 2019 to June 2021, respectively) based on availability of 1p/19q codeletion status and a PRESS acquisition optimized for 2HG detection (echo time, 97 msec) at 3.0 T before any treatment. Spectral analysis was performed using LCModel and a simulated basis set. Metabolite quantification was performed using the water signal as a reference and correcting for water and metabolite longitudinal and transverse relaxation time constants. Concentration ratios were computed using total creatine (tCr) and total choline. A two-tailed unpaired t test was used to compare metabolite concentrations obtained in codeleted versus noncodeleted gliomas, accounting for multiple comparisons. Results Thirty-one adults (mean age, 39 years ± 8 [SD]; 19 male) were included, and 19 metabolites were quantified. Cystathionine concentration was higher in codeleted (n = 13) than noncodeleted (n = 18) gliomas when quantification was performed using the water signal or tCr as references (2.33 mM ± 0.98 vs 0.93 mM ± 0.94, and 0.34 mM ± 0.14 vs 0.14 mM ± 0.14, respectively; both P < .001). The sensitivity and specificity of PRESS to detect codeletion by means of cystathionine quantification were 92% and 61%, respectively. Other metabolites did not show evidence of a difference between groups (P > .05). Conclusion Higher cystathionine levels were detected in IDH1-mutant 1p/19q codeleted gliomas than in their noncodeleted counterparts with use of a PRESS sequence optimized for 2HG detection. Of 19 metabolites quantified, only cystathionine showed evidence of a difference in concentration between groups. Clinical trial registry no. NCT01703962 © RSNA, 2023 See also the editorial by Lin in this issue.

Omics approaches for the assessment of biological responses to nanoparticles

Nanotechnology has enabled the development of innovative therapeutics, diagnostics, and drug delivery systems. Nanoparticles (NPs) can influence gene expression, protein synthesis, cell cycle, metabolism, and other subcellular processes. While conventional methods have limitations in characterizing responses to NPs, omics approaches can analyze complete sets of molecular entities that change upon exposure to NPs. This review discusses key omics approaches, namely transcriptomics, proteomics, metabolomics, lipidomics and multi-omics, applied to the assessment of biological responses to NPs. Fundamental concepts and analytical methods used for each approach are presented, as well as good practices for omics experiments. Bioinformatics tools are essential to analyze, interpret and visualize large omics data, and to correlate observations in different molecular layers. The authors envision that conducting interdisciplinary multi-omics analyses in future nanomedicine studies will reveal integrated cell responses to NPs at different omics levels, and the incorporation of omics into the evaluation of targeted delivery, efficacy, and safety will improve the development of nanomedicine therapies.

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.

Applications of Solution NMR Spectroscopy in Quality Assessment and Authentication of Bovine Milk

Nuclear magnetic resonance (NMR) spectroscopy is emerging as a promising technique for the analysis of bovine milk, primarily due to its non-destructive nature, minimal sample preparation requirements, and comprehensive approach to untargeted milk analysis. These inherent strengths of NMR make it a formidable complementary tool to mass spectrometry-based techniques in milk metabolomic studies. This review aims to provide a comprehensive overview of the applications of NMR techniques in the quality assessment and authentication of bovine milk. It will focus on the experimental setup and data processing techniques that contribute to achieving accurate and highly reproducible results. The review will also highlight key studies that have utilized commonly used NMR methodologies in milk analysis, covering a wide range of application fields. These applications include determining milk animal species and feeding regimes, as well as assessing milk nutritional quality and authenticity. By providing an overview of the diverse applications of NMR in milk analysis, this review aims to demonstrate the versatility and significance of NMR spectroscopy as an invaluable tool for milk and dairy metabolomics research and hence, for assessing the quality and authenticity of bovine milk.

Lipidomic signature of stroke recurrence after transient ischemic attack

While TIA patients have transient symptoms, they should not be underestimated, as they could have an underlying pathology that may lead to a subsequent stroke: stroke recurrence (SR). Previously, it has been described the involvement of lipids in different vascular diseases. The aim of the current study was to perform a lipidomic analysis to identify differences in the lipidomic profile between patients with SR and patients without. Untargeted lipidomic analysis was performed in plasma samples of 460 consecutive TIA patients recruited < 24 h after the onset of symptoms. 37 (8%) patients suffered SR at 90 days. Lipidomic profiling disclosed 7 lipid species differentially expressed between groups: 5 triacylglycerides (TG), 1 diacylglyceride (DG), and 1 alkenyl-PE (plasmalogen) [specifically, TG(56:1), TG(63:0), TG(58:2), TG(50:5), TG(53:7, DG(38:5)) and PE(P-18:0/18:2)]. 6 of these 7 lipid species belonged to the glycerolipid family and a plasmalogen, pointing to bioenergetics pathways, as well as oxidative stress response. In this context, it was proposed the PE(P-18:0/18:2) as potential biomarker of SR condition.The observed changes in lipid patterns suggest pathophysiological mechanisms associated with lipid droplets metabolism and antioxidant protection that is translated to plasma level as consequence of a more intensive or high-risk ischemic condition related to SR.

The Urine Metabolome of R6/2 and zQ175DN Huntington's Disease Mouse Models

Huntington's disease (HD) is caused by the expansion of a polyglutamine (polyQ)-encoding tract in exon 1 of the huntingtin gene to greater than 35 CAG repeats. It typically has a disease course lasting 15-20 years, and there are currently no disease-modifying therapies available. Thus, there is a need for faithful mouse models of HD to use in preclinical studies of disease mechanisms, target validation, and therapeutic compound testing. A large variety of mouse models of HD were generated, none of which fully recapitulate human disease, complicating the selection of appropriate models for preclinical studies. Here, we present the urinary liquid chromatography-high-resolution mass spectrometry analysis employed to identify metabolic alterations in transgenic R6/2 and zQ175DN knock-in mice. In R6/2 mice, the perturbation of the corticosterone metabolism and the accumulation of pyrraline, indicative of the development of insulin resistance and the impairment of pheromone excretion, were observed. Differently from R6/2, zQ175DN mice showed the accumulation of oxidative stress metabolites. Both genotypes showed alterations in the tryptophan metabolism. This approach aims to improve our understanding of the molecular mechanisms involved in HD neuropathology, facilitating the selection of appropriate mouse models for preclinical studies. It also aims to identify potential biomarkers specific to HD.

Desorption electrospray ionization mass spectrometry imaging (DESI-MSI) in disease diagnosis: an overview

Tissue analysis, which is essential to histology and is considered the benchmark for the diagnosis and prognosis of many illnesses, including cancer, is significant. During surgery, the surgical margin of the tumor is assessed using the labor-intensive, challenging, and commonly subjective technique known as frozen section histopathology. In the biopsy section, large numbers of molecules can now be visualized at once (ion images) following recent developments in [MSI] mass spectrometry imaging under atmospheric conditions. This is vastly superior to and different from the single optical tissue image processing used in traditional histopathology. This review article will focus on the advancement of desorption electrospray ionization mass spectrometry imaging [DESI-MSI] technique, which is label-free and requires little to no sample preparation. Since the proportion of molecular species in normal and abnormal tissues is different, DESI-MSI can capture ion images of the distributions of lipids and metabolites on biopsy sections, which can provide rich diagnostic information. This is not a systematic review but a summary of well-known, cutting-edge and recent DESI-MSI applications in cancer research between 2018 and 2023.

Integrative multi-omics and systems bioinformatics in translational neuroscience: A data mining perspective

Bioinformatic analysis of large and complex omics datasets has become increasingly useful in modern day biology by providing a great depth of information, with its application to neuroscience termed neuroinformatics. Data mining of omics datasets has enabled the generation of new hypotheses based on differentially regulated biological molecules associated with disease mechanisms, which can be tested experimentally for improved diagnostic and therapeutic targeting of neurodegenerative diseases. Importantly, integrating multi-omics data using a systems bioinformatics approach will advance the understanding of the layered and interactive network of biological regulation that exchanges systemic knowledge to facilitate the development of a comprehensive human brain profile. In this review, we first summarize data mining studies utilizing datasets from the individual type of omics analysis, including epigenetics/epigenomics, transcriptomics, proteomics, metabolomics, lipidomics, and spatial omics, pertaining to Alzheimer's disease, Parkinson's disease, and multiple sclerosis. We then discuss multi-omics integration approaches, including independent biological integration and unsupervised integration methods, for more intuitive and informative interpretation of the biological data obtained across different omics layers. We further assess studies that integrate multi-omics in data mining which provide convoluted biological insights and offer proof-of-concept proposition towards systems bioinformatics in the reconstruction of brain networks. Finally, we recommend a combination of high dimensional bioinformatics analysis with experimental validation to achieve translational neuroscience applications including biomarker discovery, therapeutic development, and elucidation of disease mechanisms. We conclude by providing future perspectives and opportunities in applying integrative multi-omics and systems bioinformatics to achieve precision phenotyping of neurodegenerative diseases and towards personalized medicine.

Plasma lipid metabolites as potential biomarkers for identifying individuals at risk of obesity-induced metabolic complications

Lipidomics studies have indicated an association between obesity and lipid metabolism dysfunction. This study aimed to evaluate and compare cardiometabolic risk factors, and the lipidomic profile in adults and older people. A cross-sectional study was conducted with 72 individuals, divided into two sex and age-matched groups: obese (body mass index-BMI ≥ 30 kg/m2; n = 36) and non-obese (BMI < 30 kg/m2; n = 36). The lipidomic profiles were evaluated in plasma using 1H nuclear magnetic resonance (1H-NMR) spectroscopy. Obese individuals had higher waist circumference (p < 0.001), visceral adiposity index (p = 0.029), homeostatic model assessment insulin resistance (HOMA-IR) (p = 0.010), and triacylglycerols (TAG) levels (p = 0.018). 1H-NMR analysis identified higher amounts of saturated lipid metabolite fragments, lower levels of unsaturated lipids, and some phosphatidylcholine species in the obese group. Two powerful machine learning (ML) models-k-nearest neighbors (kNN) and XGBoost (XGB) were employed to characterize the lipidomic profile of obese individuals. The results revealed metabolic alterations associated with obesity in the NMR signals. The models achieved high accuracy of 86% and 81%, respectively. The feature importance analysis identified signal at 1.50-1.60 ppm (-CO-CH2-CH2-, Cholesterol and fatty acid in TAG, Phospholipids) to have the highest importance in the two models.

Urinary Metabolomic Analysis of Prostate Cancer by UPLC-FTMS and UPLC-Ion Trap MSn

Accumulative evidence suggests metabolic disorders correlate with prostate cancer. Metabolic profiling of urine allows the measurement of numerous metabolites simultaneously. This study set up a metabolomic platform consisting of UPLC-FTMS and UPLC-ion trap MSⁿ for urine metabolome analysis. The platform improved retention time, mass accuracy, and signal stability. Additionally, the product ion spectrum obtained from ion trap MSⁿ facilitated structure elucidation of candidate metabolites, especially when authentic standards were not available. Urine samples from six hernia patients and six BPH patients were used for the initial establishment of the analytic platform. This platform was further employed to analyze the urine samples of 27 PCa and 49 BPH patients. Choosing the upper and lower 16% of metabolites, 258 metabolite candidates were selected. Twenty-four of them with AUC values larger than 0.65 were further selected. Eighteen of the twenty-four features can be matched in METLIN and HMDB. Eleven of the eighteen features can be interpreted by MSⁿ experiments. They were used for the combination achieving the best differential power. Finally, four metabolites were combined to reach the AUC value of 0.842 (CI 95, 0.7559 to 0.9279). This study demonstrates the urinary metabolomic analysis of prostate cancer and sheds light on future research.

Statistical considerations and database limitations in NMR-based metabolic profiling studies

INTRODUCTION

Interpretation and analysis of NMR-based metabolic profiling studies is limited by substantially incomplete commercial and academic databases. Statistical significance tests, including p-values, VIP scores, AUC values and FC values, can be largely inconsistent. Data normalization prior to statistical analysis can cause erroneous outcomes.

OBJECTIVES

The objectives were (1) to quantitatively assess consistency among p-values, VIP scores, AUC values and FC values in representative NMR-based metabolic profiling datasets, (2) to assess how data normalization can impact statistical significance outcomes, (3) to determine resonance peak assignment completion potential using commonly used databases and (4) to analyze intersection and uniqueness of metabolite space in these databases.

METHODS

P-values, VIP scores, AUC values and FC values, and their dependence on data normalization, were determined in orthotopic mouse model of pancreatic cancer and two human pancreatic cancer cell lines. Completeness of resonance assignments were evaluated using Chenomx, the human metabolite database (HMDB) and the COLMAR database. The intersection and uniqueness of the databases was quantified.

RESULTS

P-values and AUC values were strongly correlated compared to VIP or FC values. Distributions of statistically significant bins depended strongly on whether or not datasets were normalized. 40-45% of peaks had either no or ambiguous database matches. 9-22% of metabolites were unique to each database.

CONCLUSIONS

Lack of consistency in statistical analyses of metabolomics data can lead to misleading or inconsistent interpretation. Data normalization can have large effects on statistical analysis and should be justified. About 40% of peak assignments remain ambiguous or impossible with current databases. 1D and 2D databases should be made consistent to maximize metabolite assignment confidence and validation.

The effect of inhibition of receptor tyrosine kinase AXL on DNA damage response in ovarian cancer

AXL is a receptor tyrosine kinase that is often overexpressed in cancers. It contributes to pathophysiology in cancer progression and therapeutic resistance, making it an emerging therapeutic target. The first-in-class AXL inhibitor bemcentinib (R428/BGB324) has been granted fast track designation by the U.S. Food and Drug Administration (FDA) in STK11-mutated advanced metastatic non-small cell lung cancer and was also reported to show selective sensitivity towards ovarian cancers (OC) with a Mesenchymal molecular subtype. In this study, we further explored AXL's role in mediating DNA damage responses by using OC as a disease model. AXL inhibition using R428 resulted in the increase of DNA damage with the concurrent upregulation of DNA damage response signalling molecules. Furthermore, AXL inhibition rendered cells more sensitive to the inhibition of ATR, a crucial mediator for replication stress. Combinatory use of AXL and ATR inhibitors showed additive effects in OC. Through SILAC co-immunoprecipitation mass spectrometry, we identified a novel binding partner of AXL, SAM68, whose loss in OC cells harboured phenotypes in DNA damage responses similar to AXL inhibition. In addition, AXL- and SAM68-deficiency or R428 treatment induced elevated levels of cholesterol and upregulated genes in the cholesterol biosynthesis pathway. There might be a protective role of cholesterol in shielding cancer cells against DNA damage induced by AXL inhibition or SMA68 deficiency.

Jujube Fruit Metabolomic Profiles Reveal Cultivar Differences and Function as Cultivar Fingerprints

Jujube is a nutritious fruit, and is high in vitamin C, fiber, phenolics, flavonoids, nucleotides, and organic acids. It is both an important food and a source of traditional medicine. Metabolomics can reveal metabolic differences between Ziziphus jujuba fruits from different jujube cultivars and growth sites. In the fall of 2022, mature fresh fruit of eleven cultivars from replicated trials at three sites in New Mexico-Leyendecker, Los Lunas, and Alcalde-were sampled from September to October for an untargeted metabolomics study. The 11 cultivars were Alcalde 1, Dongzao, Jinsi (JS), Jinkuiwang (JKW), Jixin, Kongfucui (KFC), Lang, Li, Maya, Shanxi Li, and Zaocuiwang (ZCW). Based on the LC-MS/MS analysis, there were 1315 compounds detected with amino acids and derivatives (20.15%) and flavonoids (15.44%) as dominant categories. The results reveal that the cultivar was the dominant factor in metabolite profiles, while the location was secondary. A pairwise comparison of cultivar metabolomes revealed that two pairs had fewer differential metabolites (i.e., Li/Shanxi Li and JS/JKW) than all the other pairs, highlighting that pairwise metabolic comparison can be applied for cultivar fingerprinting. Differential metabolite analysis also showed that half of drying cultivars have up-regulated lipid metabolites compared to fresh or multi-purpose fruit cultivars and that specialized metabolites vary significantly between cultivars from 35.3% (Dongzao/ZCW) to 56.7% (Jixin/KFC). An exemplary analyte matching sedative cyclopeptide alkaloid sanjoinine A was only detected in the Jinsi and Jinkuiwang cultivars. Overall, our metabolic analysis of the jujube cultivar's mature fruits provides the largest resource of jujube fruit metabolomes to date and will inform cultivar selection for nutritional and medicinal research and for fruit metabolic breeding.

Resveratrol Mitigates Metabolism in Human Microglia Cells

The recognition of the role of microglia cells in neurodegenerative diseases has steadily increased over the past few years. There is growing evidence that the uncontrolled and persisting activation of microglial cells is involved in the progression of diseases such as Alzheimer's or Parkinson's disease. The inflammatory activation of microglia cells is often accompanied by a switch in metabolism to higher glucose consumption and aerobic glycolysis. In this study, we investigate the changes induced by the natural antioxidant resveratrol in a human microglia cell line. Resveratrol is renowned for its neuroprotective properties, but little is known about its direct effect on human microglia cells. By analyzing a variety of inflammatory, neuroprotective, and metabolic aspects, resveratrol was observed to reduce inflammasome activity, increase the release of insulin-like growth factor 1, decrease glucose uptake, lower mitochondrial activity, and attenuate cellular metabolism in a ¹H NMR-based analysis of whole-cell extracts. To this end, studies were mainly performed by analyzing the effect of exogenous stressors such as lipopolysaccharide or interferon gamma on the metabolic profile of microglial cells. Therefore, this study focuses on changes in metabolism without any exogenous stressors, demonstrating how resveratrol might provide protection from persisting neuroinflammation.

Decrease in the Ratio proBDNF/BDNF in the Urine of Aging Female Patients with OAB

Imbalance in the levels of neurotrophins, growth factors crucial in the development, function, and survival of neurons is commonly observed in many pathological states. Concentrations of brain-derived neurotrophic factor (BDNF) and its precursor (proBDNF) were measured in the urine of a cohort of aging female patients with overactive bladder disease (OAB). When reported to creatinine, levels were similar between OAB patients and healthy controls. However, the ratio proBDNF/BDNF was significantly decreased in the OAB group. Receiver operating characteristic (ROC) curve analysis of the ratio proBDNF/BDNF displayed a good diagnostic value for OAB (AUC = 0.729). Clinical questionnaires of symptom severity (OABSS and IIQ-7) were negatively correlated with this ratio. On the other hand, microRNAs (miRNA) involved in proBDNF gene translation were expressed at comparable levels between groups. However, urinary enzymatic activity of matrix metalloproteinase-9 (MMP-9), the enzyme that cleaves proBDNF into BDNF, was increased in OAB compared to controls. Levels of miR-491-5p, the main miRNA that downregulates MMP-9 synthesis, were greatly decreased in urine from OAB patients. These results suggest that the ratio proBDNF/BDNF could be useful in the phenotyping of OAB in an aging population, and the difference could originate from enhanced MMP-9 enzymatic activity rather than translational control.