A global perspective on the status of clinical metabolomics in laboratory medicine - a survey by the IFCC metabolomics working group.

OBJECTIVES: Metabolomics aims for comprehensive characterization and measurement of small molecule metabolites (<1700 Da) in complex biological matrices. This study sought to assess the current understanding and usage of metabolomics in laboratory medicine globally and evaluate the perception of its promise and future implementation. METHODS: A survey was conducted by the IFCC metabolomics working group that queried 400 professionals from 79 countries. Participants provided insights into their experience levels, knowledge, and usage of metabolomics approaches, along with detailing the applications and methodologies employed. RESULTS: Findings revealed a varying level of experience among respondents, with varying degrees of familiarity and utilization of metabolomics techniques. Targeted approaches dominated the field, particularly liquid chromatography coupled to a triple quadrupole mass spectrometer, with untargeted methods also receiving significant usage. Applications spanned clinical research, epidemiological studies, clinical diagnostics, patient monitoring, and prognostics across various medical domains, including metabolic diseases, endocrinology, oncology, cardiometabolic risk, neurodegeneration and clinical toxicology. CONCLUSIONS: Despite optimism for the future of clinical metabolomics, challenges such as technical complexity, standardization issues, and financial constraints remain significant hurdles. The study underscores the promising yet intricate landscape of metabolomics in clinical practice, emphasizing the need for continued efforts to overcome barriers and realize its full potential in patient care and precision medicine.

E2F transcription factor-1 modulates expression of glutamine metabolic genes in mouse embryonic fibroblasts and uterine sarcoma cells.

Metabolic reprogramming is considered as a hallmark of cancer and is clinically exploited as a novel target for therapy. The E2F transcription factor-1 (E2F1) regulates various cellular processes, including proliferative and metabolic pathways, and acts, depending on the cellular and molecular context, as an oncogene or tumor suppressor. The latter is evident by the observation that E2f1-knockout mice develop spontaneous tumors, including uterine sarcomas. This dual role warrants a detailed investigation of how E2F1 loss impacts metabolic pathways related to cancer progression. Our data indicate that E2F1 binds to the promoter of several glutamine metabolism-related genes. Interestingly, the expression of genes in the glutamine metabolic pathway were increased in mouse embryonic fibroblasts (MEFs) lacking E2F1. In addition, we confirm that E2f1-/- MEFs are more efficient in metabolizing glutamine and producing glutamine-derived precursors for proliferation. Mechanistically, we observe a co-occupancy of E2F1 and MYC on glutamine metabolic promoters, increased MYC binding after E2F1 depletion and that silencing of MYC decreased the expression of glutamine-related genes in E2f1-/- MEFs. Analyses of transcriptomic profiles in 29 different human cancers identified uterine sarcoma that showed a negative correlation between E2F1 and glutamine metabolic genes. CRISPR/Cas9 knockout of E2F1 in the uterine sarcoma cell line SK-UT-1 confirmed elevated glutamine metabolic gene expression, increased proliferation and increased MYC binding to glutamine-related promoters upon E2F1 loss. Together, our data suggest a crucial role of E2F1 in energy metabolism and metabolic adaptation in uterine sarcoma cells.

PI5P4Kα supports prostate cancer metabolism and exposes a survival vulnerability during androgen receptor inhibition.

Phosphatidylinositol (PI)regulating enzymes are frequently altered in cancer and have become a focus for drug development. Here, we explore the phosphatidylinositol-5-phosphate 4-kinases (PI5P4K), a family of lipid kinases that regulate pools of intracellular PI, and demonstrate that the PI5P4Kα isoform influences androgen receptor (AR) signaling, which supports prostate cancer (PCa) cell survival. The regulation of PI becomes increasingly important in the setting of metabolic stress adaptation of PCa during androgen deprivation (AD), as we show that AD influences PI abundance and enhances intracellular pools of PI-4,5-P2. We suggest that this PI5P4Kα-AR relationship is mitigated through mTORC1 dysregulation and show that PI5P4Kα colocalizes to the lysosome, the intracellular site of mTORC1 complex activation. Notably, this relationship becomes prominent in mouse prostate tissue following surgical castration. Finally, multiple PCa cell models demonstrate marked survival vulnerability following stable PI5P4Kα inhibition. These results nominate PI5P4Kα as a target to disrupt PCa metabolic adaptation to castrate resistance.

Gut microbiota severely hampers the efficacy of NAD-lowering therapy in leukemia.

Most cancer cells have high need for nicotinamide adenine dinucleotide (NAD+) to sustain their survival. This led to the development of inhibitors of nicotinamide (NAM) phosphoribosyltransferase (NAMPT), the rate-limiting NAD+ biosynthesis enzyme from NAM. Such inhibitors kill cancer cells in preclinical studies but failed in clinical ones. To identify parameters that could negatively affect the therapeutic efficacy of NAMPT inhibitors and propose therapeutic strategies to circumvent such failure, we performed metabolomics analyses in tumor environment and explored the effect of the interaction between microbiota and cancer cells. Here we show that tumor environment enriched in vitamin B3 (NAM) or nicotinic acid (NA) significantly lowers the anti-tumor efficacy of APO866, a prototypic NAMPT inhibitor. Additionally, bacteria (from the gut, or in the medium) can convert NAM into NA and thus fuel an alternative NAD synthesis pathway through NA. This leads to the rescue from NAD depletion, prevents reactive oxygen species production, preserves mitochondrial integrity, blunts ATP depletion, and protects cancer cells from death.Our data in an in vivo preclinical model reveal that antibiotic therapy down-modulating gut microbiota can restore the anti-cancer efficacy of APO866. Alternatively, NAphosphoribosyltransferase inhibition may restore anti-cancer activity of NAMPT inhibitors in the presence of gut microbiota and of NAM in the diet.

PERK is a critical metabolic hub for immunosuppressive function in macrophages.

Chronic inflammation triggers compensatory immunosuppression to stop inflammation and minimize tissue damage. Studies have demonstrated that endoplasmic reticulum (ER) stress augments the suppressive phenotypes of immune cells; however, the molecular mechanisms underpinning this process and how it links to the metabolic reprogramming of immunosuppressive macrophages remain elusive. In the present study, we report that the helper T cell 2 cytokine interleukin-4 and the tumor microenvironment increase the activity of a protein kinase RNA-like ER kinase (PERK)-signaling cascade in macrophages and promote immunosuppressive M2 activation and proliferation. Loss of PERK signaling impeded mitochondrial respiration and lipid oxidation critical for M2 macrophages. PERK activation mediated the upregulation of phosphoserine aminotransferase 1 (PSAT1) and serine biosynthesis via the downstream transcription factor ATF-4. Increased serine biosynthesis resulted in enhanced mitochondrial function and α-ketoglutarate production required for JMJD3-dependent epigenetic modification. Inhibition of PERK suppressed macrophage immunosuppressive activity and could enhance the efficacy of immune checkpoint programmed cell death protein 1 inhibition in melanoma. Our findings delineate a previously undescribed connection between PERK signaling and PSAT1-mediated serine metabolism critical for promoting immunosuppressive function in M2 macrophages.

Tumor-induced reshuffling of lipid composition on the endoplasmic reticulum membrane sustains macrophage survival and pro-tumorigenic activity.

Tumor-associated macrophages (TAMs) display pro-tumorigenic phenotypes for supporting tumor progression in response to microenvironmental cues imposed by tumor and stromal cells. However, the underlying mechanisms by which tumor cells instruct TAM behavior remain elusive. Here, we uncover that tumor-cell-derived glucosylceramide stimulated unconventional endoplasmic reticulum (ER) stress responses by inducing reshuffling of lipid composition and saturation on the ER membrane in macrophages, which induced IRE1-mediated spliced XBP1 production and STAT3 activation. The cooperation of spliced XBP1 and STAT3 reinforced the pro-tumorigenic phenotype and expression of immunosuppressive genes. Ablation of XBP1 expression with genetic manipulation or ameliorating ER stress responses by facilitating LPCAT3-mediated incorporation of unsaturated lipids to the phosphatidylcholine hampered pro-tumorigenic phenotype and survival in TAMs. Together, we uncover the unexpected roles of tumor-cell-produced lipids that simultaneously orchestrate macrophage polarization and survival in tumors via induction of ER stress responses and reveal therapeutic targets for sustaining host antitumor immunity.

The metabolic signature of cardiorespiratory fitness: a protocol for a systematic review and meta-analysis.

INTRODUCTION: A low cardiorespiratory fitness (CRF) is a strong and independent predictor of cardiometabolic, cancer and all-cause mortality. To date, the mechanisms linking CRF with reduced mortality remain largely unknown. Metabolomics, which is a powerful metabolic phenotyping technology to unravel molecular mechanisms underlying complex phenotypes, could elucidate how CRF fosters human health. METHODS AND ANALYSIS: This study aims at systematically reviewing and meta-analysing the literature on metabolites of any human tissue sample, which are positively or negatively associated with CRF. Studies reporting estimated CRF will not be considered. No restrictions will be placed on the metabolomics technology used to measure metabolites. PubMed, Web of Science and EMBASE will be searched for relevant articles published until the date of the last search. Two authors will independently screen full texts of selected abstracts. References and citing articles of included articles will be screened for additional relevant publications. Data regarding study population, tissue samples, analytical technique, quality control, data processing, metabolites associated to CRF, cardiopulmonary exercise test protocol and exercise exhaustion criteria will be extracted. Methodological quality will be assessed using a modified version of QUADOMICS. Narrative synthesis as well as tabular/charted presentation of the extracted data will be included. If feasible, meta-analyses will be used to investigate the associations between identified metabolites and CRF. Potential sources of heterogeneity will be explored in meta-regressions. ETHICS AND DISSEMINATION: No ethics approval is required. The results will be published in a peer-reviewed journal and as conference presentation. PROSPERO REGISTRATION NUMBER: CRD42020214375.

Metabolomics meets lipidomics: Assessing the small molecule component of metabolism.

Metabolomics, including lipidomics, is emerging as a quantitative biology approach for the assessment of energy flow through metabolism and information flow through metabolic signaling; thus, providing novel insights into metabolism and its regulation, in health, healthy ageing and disease. In this forward-looking review we provide an overview on the origins of metabolomics, on its role in this postgenomic era of biochemistry and its application to investigate metabolite role and (bio)activity, from model systems to human population studies. We present the challenges inherent to this analytical science, and approaches and modes of analysis that are used to resolve, characterize and measure the infinite chemical diversity contained in the metabolome (including lipidome) of complex biological matrices. In the current outbreak of metabolic diseases such as cardiometabolic disorders, cancer and neurodegenerative diseases, metabolomics appears to be ideally situated for the investigation of disease pathophysiology from a metabolite perspective.

Molecular Profiling and Functional Analysis of Macrophage-Derived Tumor Extracellular Vesicles.

Extracellular vesicles (EVs), including exosomes, modulate multiple aspects of cancer biology. Tumor-associated macrophages (TAMs) secrete EVs, but their molecular features and functions are poorly characterized. Here, we report methodology for the enrichment, quantification, and proteomic and lipidomic analysis of EVs released from mouse TAMs (TAM-EVs). Compared to source TAMs, TAM-EVs present molecular profiles associated with a Th1/M1 polarization signature, enhanced inflammation and immune response, and a more favorable patient prognosis. Accordingly, enriched TAM-EV preparations promote T cell proliferation and activation ex vivo. TAM-EVs also contain bioactive lipids and biosynthetic enzymes, which may alter pro-inflammatory signaling in the cancer cells. Thus, whereas TAMs are largely immunosuppressive, their EVs may have the potential to stimulate, rather than limit, anti-tumor immunity.

Autonomous Multimodal Metabolomics Data Integration for Comprehensive Pathway Analysis and Systems Biology.

Comprehensive metabolomic data can be achieved using multiple orthogonal separation and mass spectrometry (MS) analytical techniques. However, drawing biologically relevant conclusions from this data and combining it with additional layers of information collected by other omic technologies present a significant bioinformatic challenge. To address this, a data processing approach was designed to automate the comprehensive prediction of dysregulated metabolic pathways/networks from multiple data sources. The platform autonomously integrates multiple MS-based metabolomics data types without constraints due to different sample preparation/extraction, chromatographic separation, or MS detection method. This multimodal analysis streamlines the extraction of biological information from the metabolomics data as well as the contextualization within proteomics and transcriptomics data sets. As a proof of concept, this multimodal analysis approach was applied to a colorectal cancer (CRC) study, in which complementary liquid chromatography-mass spectrometry (LC-MS) data were combined with proteomic and transcriptomic data. Our approach provided a highly resolved overview of colon cancer metabolic dysregulation, with an average 17% increase of detected dysregulated metabolites per pathway and an increase in metabolic pathway prediction confidence. Moreover, 95% of the altered metabolic pathways matched with the dysregulated genes and proteins, providing additional validation at a systems level. The analysis platform is currently available via the XCMS Online ( XCMSOnline.scripps.edu ).

Metabolomics as a Tool to Understand Pathophysiological Processes.

Multiple diseases have a strong metabolic component, and metabolomics as a powerful phenotyping technology, in combination with orthogonal biological and clinical approaches, will undoubtedly play a determinant role in accelerating the understanding of mechanisms that underlie these complex diseases determined by a set of genetic, lifestyle, and environmental exposure factors. Here, we provide several examples of valuable findings from metabolomics-led studies in diabetes and obesity metabolism, neurodegenerative disorders, and cancer metabolism and offer a longer term vision toward personalized approach to medicine, from population-based studies to pharmacometabolomics.

α-ketoglutarate orchestrates macrophage activation through metabolic and epigenetic reprogramming.

Glutamine metabolism provides synergistic support for macrophage activation and elicitation of desirable immune responses; however, the underlying mechanisms regulated by glutamine metabolism to orchestrate macrophage activation remain unclear. Here we show that the production of α-ketoglutarate (αKG) via glutaminolysis is important for alternative (M2) activation of macrophages, including engagement of fatty acid oxidation (FAO) and Jmjd3-dependent epigenetic reprogramming of M2 genes. This M2-promoting mechanism is further modulated by a high αKG/succinate ratio, whereas a low ratio strengthens the proinflammatory phenotype in classically activated (M1) macrophages. As such, αKG contributes to endotoxin tolerance after M1 activation. This study reveals new mechanistic regulations by which glutamine metabolism tailors the immune responses of macrophages through metabolic and epigenetic reprogramming.

Thermal Degradation of Small Molecules: A Global Metabolomic Investigation.

Thermal processes are widely used in small molecule chemical analysis and metabolomics for derivatization, vaporization, chromatography, and ionization, especially in gas chromatography mass spectrometry (GC/MS). In this study the effect of heating was examined on a set of 64 small molecule standards and, separately, on human plasma metabolite extracts. The samples, either derivatized or underivatized, were heated at three different temperatures (60, 100, and 250 °C) at different exposure times (30 s, 60 s, and 300 s). All the samples were analyzed by liquid chromatography coupled to electrospray ionization mass spectrometry (LC/MS) and the data processed by XCMS Online ( xcmsonline.scripps.edu ). The results showed that heating at an elevated temperature of 100 °C had an appreciable effect on both the underivatized and derivatized molecules, and heating at 250 °C created substantial changes in the profile. For example, over 40% of the molecular peaks were altered in the plasma metabolite analysis after heating (250 °C, 300s) with a significant formation of degradation and transformation products. The analysis of 64 small molecule standards validated the temperature-induced changes observed on the plasma metabolites, where most of the small molecules degraded at elevated temperatures even after minimal exposure times (30 s). For example, tri- and diorganophosphates (e.g., adenosine triphosphate and adenosine diphosphate) were readily degraded into a mono-organophosphate (e.g., adenosine monophosphate) during heating. Nucleosides and nucleotides (e.g., inosine and inosine monophosphate) were also found to be transformed into purine derivatives (e.g., hypoxanthine). A newly formed transformation product, oleoyl ethyl amide, was identified in both the underivatized and derivatized forms of the plasma extracts and small molecule standard mixture, and was likely generated from oleic acid. Overall these analyses show that small molecules and metabolites undergo significant time-sensitive alterations when exposed to elevated temperatures, especially those conditions that mimic sample preparation and analysis in GC/MS experiments.

Metabolism links bacterial biofilms and colon carcinogenesis.

Bacterial biofilms in the colon alter the host tissue microenvironment. A role for biofilms in colon cancer metabolism has been suggested but to date has not been evaluated. Using metabolomics, we investigated the metabolic influence that microbial biofilms have on colon tissues and the related occurrence of cancer. Patient-matched colon cancers and histologically normal tissues, with or without biofilms, were examined. We show the upregulation of polyamine metabolites in tissues from cancer hosts with significant enhancement of N(1), N(12)-diacetylspermine in both biofilm-positive cancer and normal tissues. Antibiotic treatment, which cleared biofilms, decreased N(1), N(12)-diacetylspermine levels to those seen in biofilm-negative tissues, indicating that host cancer and bacterial biofilm structures contribute to the polyamine metabolite pool. These results show that colonic mucosal biofilms alter the cancer metabolome to produce a regulator of cellular proliferation and colon cancer growth potentially affecting cancer development and progression.

Metabolomic profiling reveals deep chemical divergence between two morphotypes of the zoanthid Parazoanthus axinellae.

Metabolomics has recently proven its usefulness as complementary tool to traditional morphological and genetic analyses for the classification of marine invertebrates. Among the metabolite-rich cnidarian order Zoantharia, Parazoanthus is a polyphyletic genus whose systematics and phylogeny remain controversial. Within this genus, one of the most studied species, Parazoanthus axinellae is prominent in rocky shallow waters of the Mediterranean Sea and the NE Atlantic Ocean. Although different morphotypes can easily be distinguished, only one species is recognized to date. Here, a metabolomic profiling approach has been used to assess the chemical diversity of two main Mediterranean morphotypes, the "slender" and "stocky" forms of P. axinellae. Targeted profiling of their major secondary metabolites revealed a significant chemical divergence between the morphotypes. While zoanthoxanthin alkaloids and ecdysteroids are abundant in both morphs, the "slender" morphotype is characterized by the presence of additional and bioactive 3,5-disubstituted hydantoin derivatives named parazoanthines. The absence of these specific compounds in the "stocky" morphotype was confirmed by spatial and temporal monitoring over an annual cycle. Moreover, specimens of the "slender" morphotype are also the only ones found as epibionts of several sponge species, particularly Cymbaxinella damicornis thus suggesting a putative ecological link.

Brain region mapping using global metabolomics.

Historically, studies of brain metabolism have been based on targeted analyses of a limited number of metabolites. Here we present an untargeted mass spectrometry-based metabolomic strategy that has successfully uncovered differences in a broad array of metabolites across anatomical regions of the mouse brain. The NSG immunodeficient mouse model was chosen because of its ability to undergo humanization leading to numerous applications in oncology and infectious disease research. Metabolic phenotyping by hydrophilic interaction liquid chromatography and nanostructure imaging mass spectrometry revealed both water-soluble and lipid metabolite patterns across brain regions. Neurochemical differences in metabolic phenotypes were mainly defined by various phospholipids and several intriguing metabolites including carnosine, cholesterol sulfate, lipoamino acids, uric acid, and sialic acid, whose physiological roles in brain metabolism are poorly understood. This study helps define regional homeostasis for the normal mouse brain to give context to the reaction to pathological events.

Interactive XCMS Online: simplifying advanced metabolomic data processing and subsequent statistical analyses.

XCMS Online (xcmsonline.scripps.edu) is a cloud-based informatic platform designed to process and visualize mass-spectrometry-based, untargeted metabolomic data. Initially, the platform was developed for two-group comparisons to match the independent, "control" versus "disease" experimental design. Here, we introduce an enhanced XCMS Online interface that enables users to perform dependent (paired) two-group comparisons, meta-analysis, and multigroup comparisons, with comprehensive statistical output and interactive visualization tools. Newly incorporated statistical tests cover a wide array of univariate analyses. Multigroup comparison allows for the identification of differentially expressed metabolite features across multiple classes of data while higher order meta-analysis facilitates the identification of shared metabolic patterns across multiple two-group comparisons. Given the complexity of these data sets, we have developed an interactive platform where users can monitor the statistical output of univariate (cloud plots) and multivariate (PCA plots) data analysis in real time by adjusting the threshold and range of various parameters. On the interactive cloud plot, metabolite features can be filtered out by their significance level (p-value), fold change, mass-to-charge ratio, retention time, and intensity. The variation pattern of each feature can be visualized on both extracted-ion chromatograms and box plots. The interactive principal component analysis includes scores, loadings, and scree plots that can be adjusted depending on scaling criteria. The utility of XCMS functionalities is demonstrated through the metabolomic analysis of bacterial stress response and the comparison of lymphoblastic leukemia cell lines.

Toward 'omic scale metabolite profiling: a dual separation-mass spectrometry approach for coverage of lipid and central carbon metabolism.

Although the objective of any 'omic science is broad measurement of its constituents, such coverage has been challenging in metabolomics because the metabolome is comprised of a chemically diverse set of small molecules with variable physical properties. While extensive studies have been performed to identify metabolite isolation and separation methods, these strategies introduce bias toward lipophilic or water-soluble metabolites depending on whether reversed-phase (RP) or hydrophilic interaction liquid chromatography (HILIC) is used, respectively. Here we extend our consideration of metabolome isolation and separation procedures to integrate RPLC/MS and HILIC/MS profiling. An aminopropyl-based HILIC/MS method was optimized on the basis of mobile-phase additives and pH, followed by evaluation of reproducibility. When applied to the untargeted study of perturbed bacterial metabolomes, the HILIC method enabled the accurate assessment of key, dysregulated metabolites in central carbon pathways (e.g., amino acids, organic acids, phosphorylated sugars, energy currency metabolites), which could not be retained by RPLC. To demonstrate the value of the integrative approach, bacterial cells, human plasma, and cancer cells were analyzed by combined RPLC/HILIC separation coupled to ESI positive/negative MS detection. The combined approach resulted in the observation of metabolites associated with lipid and central carbon metabolism from a single biological extract, using 80% organic solvent (ACN:MeOH:H2O 2:2:1). It enabled the detection of more than 30,000 features from each sample type, with the highest number of uniquely detected features by RPLC in ESI positive mode and by HILIC in ESI negative mode. Therefore, we conclude that when time and sample are limited, the maximum amount of biological information related to lipid and central carbon metabolism can be acquired by combining RPLC ESI positive and HILIC ESI negative mode analysis.