Important Considerations for Sample Collection in Metabolomics Studies with a Special Focus on Applications to Liver Functions

Metabolomics and Lipidomics for Studying Metabolic Syndrome: Insights into Cardiovascular Diseases, Type 1 & 2 Diabetes, and Metabolic Dysfunction-Associated Steatotic Liver Disease

Metabolomics and lipidomics have emerged as tools in understanding the connections of metabolic syndrome (MetS) with cardiovascular diseases (CVD), type 1 and type 2 diabetes (T1D, T2D), and metabolic dysfunction-associated steatotic liver disease (MASLD). This review highlights the applications of these omics approaches in large-scale cohort studies, emphasizing their role in biomarker discovery and disease prediction. Integrating metabolomics and lipidomics has significantly advanced our understanding of MetS pathology by identifying unique metabolic signatures associated with disease progression. However, challenges such as standardizing analytical workflows, data interpretation, and biomarker validation remain critical for translating research findings into clinical practice. Future research should focus on optimizing these methodologies to enhance their clinical utility and address the global burden of MetS-related diseases.

Qi Wei Anti-burn Tincture Remodels Liver Metabolic Pathways and Treats Burn Wounds Efficiently

This work aims to elucidate the molecular mechanism of Qi Wei anti-burn Tincture (QW) on wound healing in burnt mice using metabolomics and molecular biology techniques. A scald model was first established in Kunming mice. After treatment, biochemical indicators for liver function and burnt skin tissues were then evaluated via biochemical detection and HE staining, respectively. Liver tissues were further analyzed for differential metabolites, inflammatory factors, and mRNA levels of cytokines using metabolomics and molecular biology techniques. Involved metabolic pathways were also identified using software. QW treatment did promote the healing of the burn wounds in Kunming mice with a downregulation of ALP, ALT, and AST to normal levels. In mouse liver tissue, the contents of glutamine, aspartic acid, and citrulline were significantly reduced, while the contents of 5-hydroxyproline, taurine, hypotaurine, and glutamic acid significantly increased. These major differential compounds are involved in the arginine metabolic pathway, nitrogen excretion, and the metabolism of taurine and hypotaurine, suggesting that QW reprogramed the above metabolic processes in the liver. Furthermore, the application of QW increased the expression of TGF-β1 and FGF-2 and reduced the levels of TNF-α, IL-1β, IL-6, and reactive oxygen species in the liver of mice induced by burn injury. This study found that QW treatment promoted metabolic pathway remodeling in the liver, which might be a potential mechanism for QW to treat burn wounds.

Exploring sample treatment strategies for untargeted metabolomics: A comparative study of solid phase microextraction (SPME) and homogenization with solid-liquid extraction (SLE) in renal tissue

BACKGROUND

The selection of the sample treatment strategy is a crucial step in the metabolomics workflow. Solid phase microextraction (SPME) is a sample processing methodology with great potential for use in untargeted metabolomics of tissue samples. However, its utilization is not as widespread as other standard protocols involving steps of tissue collection, metabolism quenching, homogenization, and extraction of metabolites by solvents. Since SPME allows us to perform all these steps in one action in tissue samples, in addition to other advantages, it is necessary to know whether this methodology produces similar or comparable metabolome and lipidome coverage and performance to classical methods.

RESULTS

SPME and homogenization with solid-liquid extraction (Homo-SLE) sample treatment methods were applied to healthy murine kidney tissue, followed by comprehensive metabolomics and lipidomics analyses. In addition, it has been tested whether freezing and storage of the tissue causes alterations in the renal metabolome and lipidome, so the analyses were performed on fresh and frozen tissue samples Lipidomics analysis revealed the exclusive presence of different structural membrane and intracellular lipids in the Homo-SLE group. Conversely, all annotated metabolites were detected in both groups. Notably, the freezing of the sample mainly causes a decrease in the levels of most lipid species and an increase in metabolites such as amino acids, purines, and pyrimidines. These alterations are principally detected in a statistically significant way by SPME methodology. Finally, the samples of both methodologies show a positive correlation in all the analyses.

SIGNIFICANCE

These results demonstrate that in SPME processing, as long as the fundamentals of non-exhaustive extraction in a pre-equilibrium kinetic regime, extraction in a tissue localized area, the chemistry of the fiber coating and non-homogenization of the tissue are taken into account, is an excellent method to use in kidney tissue metabolomics; since this methodology presents an easy-to-use, efficient, and less invasive approach that simplifies the different sample processing steps.

Fecal microbiota transplantation: current challenges and future landscapes

SUMMARYGiven the importance of gut microbial homeostasis in maintaining health, there has been considerable interest in developing innovative therapeutic strategies for restoring gut microbiota. One such approach, fecal microbiota transplantation (FMT), is the main "whole gut microbiome replacement" strategy and has been integrated into clinical practice guidelines for treating recurrent Clostridioides difficile infection (rCDI). Furthermore, the potential application of FMT in other indications such as inflammatory bowel disease (IBD), metabolic syndrome, and solid tumor malignancies is an area of intense interest and active research. However, the complex and variable nature of FMT makes it challenging to address its precise functionality and to assess clinical efficacy and safety in different disease contexts. In this review, we outline clinical applications, efficacy, durability, and safety of FMT and provide a comprehensive assessment of its procedural and administration aspects. The clinical applications of FMT in children and cancer immunotherapy are also described. We focus on data from human studies in IBD in contrast with rCDI to delineate the putative mechanisms of this treatment in IBD as a model, including colonization resistance and functional restoration through bacterial engraftment, modulating effects of virome/phageome, gut metabolome and host interactions, and immunoregulatory actions of FMT. Furthermore, we comprehensively review omics technologies, metagenomic approaches, and bioinformatics pipelines to characterize complex microbial communities and discuss their limitations. FMT regulatory challenges, ethical considerations, and pharmacomicrobiomics are also highlighted to shed light on future development of tailored microbiome-based therapeutics.

Challenges in the Metabolomics-Based Biomarker Validation Pipeline

As end-products of the intersection between the genome and environmental influences, metabolites represent a promising approach to the discovery of novel biomarkers for diseases. However, many potential biomarker candidates identified by metabolomics studies fail to progress beyond analytical validation for routine implementation in clinics. Awareness of the challenges present can facilitate the development and advancement of innovative strategies that allow improved and more efficient applications of metabolite-based markers in clinical settings. This minireview provides a comprehensive summary of the pre-analytical factors, required analytical validation studies, and kit development challenges that must be resolved before the successful translation of novel metabolite biomarkers originating from research. We discuss the necessity for strict protocols for sample collection, storage, and the regulatory requirements to be fulfilled for a bioanalytical method to be considered as analytically validated. We focus especially on the blood as a biological matrix and liquid chromatography coupled with tandem mass spectrometry as the analytical platform for biomarker validation. Furthermore, we examine the challenges of developing a commercially viable metabolomics kit for distribution. To bridge the gap between the research lab and clinical implementation and utility of relevant metabolites, the understanding of the translational challenges for a biomarker panel is crucial for more efficient development of metabolomics-based precision medicine.

A current review of U.S. beef flavor I: Measuring beef flavor

Historically, consumer acceptance of beef was determined by tenderness. Developments in genetics and management over the last couple of decades have improved tenderness to the point that it is secondary to other factors in beef's taste. Flavor, however, is an extraordinarily complex taste attribute dependent on biological sensors in the mouth, sinus cavity, and jaws. The culinary industry has recently focused on innovative ways to give consumers new products satisfying their curiosity about different foods, especially proteins. Competition from plant-based, cell-based, and even other animal-based proteins provides diversity in consumers' ability to select a protein that satisfies their desire to include unique products in their diet. Consequently, the beef industry has focused on flavor for the last 10 to 15 years to determine whether it can provide the guardrails for beef consumption in the future. The U.S. beef industry formed a Flavor Working Group in 2012 composed of the authors listed here to investigate new and innovative ways to manage and measure beef flavor. The results of this working group have resulted in dozens of papers, presentations, abstracts, and symposia. The objective of this manuscript is to summarize the research developed by this working group and by others worldwide that have investigated methodologies that measure beef flavor. This paper will describe the strengths of the research in beef flavor measurement and point out future needs that might be identified as technology advances.

Thyroid cancer cell metabolism: A glance into cell culture system-based metabolomics approaches

Thyroid cancer is the most common malignancy of the endocrine system and the seventh most prevalent cancer in women worldwide. It is a complex and diverse disease characterized by heterogeneity, underscoring the importance of understanding the underlying metabolic alterations within tumor cells. Metabolomics technologies offer a powerful toolset to explore and identify endogenous and exogenous biochemical reaction products, providing crucial insights into the intricate metabolic pathways and processes within living cells. Metabolism plays a central role in cell function, making metabolomics a valuable reflection of a cell's phenotype. In the OMICs era, metabolomics analysis of cells brings numerous advantages over existing methods, propelling cell metabolomics as an emerging field with vast potential for investigating metabolic pathways and their perturbation in pathophysiological conditions. This review article aims to look into recent developments in applying metabolomics for characterizing and interpreting the cellular metabolome in thyroid cancer cell lines, exploring their unique metabolic characteristics. Understanding the metabolic alterations in tumor cells can lead to the identification of critical nodes in the metabolic network that could be targeted for therapeutic intervention.

Metabolomics in Preclinical Drug Safety Assessment: Current Status and Future Trends

Metabolomics is emerging as a powerful systems biology approach for improving preclinical drug safety assessment. This review discusses current applications and future trends of metabolomics in toxicology and drug development. Metabolomics can elucidate adverse outcome pathways by detecting endogenous biochemical alterations underlying toxicity mechanisms. Furthermore, metabolomics enables better characterization of human environmental exposures and their influence on disease pathogenesis. Metabolomics approaches are being increasingly incorporated into toxicology studies and safety pharmacology evaluations to gain mechanistic insights and identify early biomarkers of toxicity. However, realizing the full potential of metabolomics in regulatory decision making requires a robust demonstration of reliability through quality assurance practices, reference materials, and interlaboratory studies. Overall, metabolomics shows great promise in strengthening the mechanistic understanding of toxicity, enhancing routine safety screening, and transforming exposure and risk assessment paradigms. Integration of metabolomics with computational, in vitro, and personalized medicine innovations will shape future applications in predictive toxicology.

Biomarker Identification in Liver Cancers Using Desorption Electrospray Ionization Mass Spectrometry (DESI-MS) Imaging: An Approach for Spatially Resolved Metabolomics

Liver cancers are characterized by interindividual and intratumoral heterogeneity, which makes early diagnosis and the development of therapies challenging. Desorption electrospray ionization mass spectrometry (DESI-MS) imaging is a potent and sensitive MS ionization technique for direct, unaltered 2D and 3D imaging of metabolites in complex biological samples. Indeed, DESI gently desorbs and ionizes analyte molecules from the sample surface using an electrospray source of highly charged aqueous spray droplets in ambient conditions. DESI-MS imaging of biological samples allows untargeted analysis and characterization of metabolites in liver cancers to identify new biomarkers of malignancy. In this chapter, we described a detailed protocol using liver cancer samples collected and stored for histopathology examination, either as frozen or as formalin-fixed, paraffin-embedded specimens. Such hepatocellular carcinoma samples can be subjected to DESI-MS analyses, illustrating the capacity of spatially resolved metabolomics to distinguish malignant lesions from adjacent normal liver tissue.

Effects of Dietary Protein Levels on Sheep Gut Metabolite Profiles during the Lactating Stage

Diet-associated characteristics such as dietary protein levels can modulate the gut's primary or secondary metabolites, leading to effects on the productive performance and overall health of animals. Whereas fecal metabolite changes are closely associated with gut metabolome, this study aimed to see changes in the rumen metabolite profile of lactating ewes fed different dietary protein levels. For this, eighteen lactating ewes (approximately 2 years old, averaging 38.52 ± 1.57 kg in their initial body weight) were divided into three groups (n = 6 ewes/group) by following the complete randomized design, and each group was assigned to one of three low-protein (D_I), medium-protein (D_m), and high-protein (D_h) diets containing 8.58%, 10.34%, and 13.93% crude protein contents on a dry basis, respectively. The fecal samples were subjected to untargeted metabolomics using ultra-performance liquid chromatography (UPLC). The metabolomes of the sheep fed to the high-protein-diet group were distinguished as per principal-component analysis from the medium- and low-protein diets. Fecal metabolite concentrations as well as their patterns were changed by feeding different dietary protein levels. The discriminating metabolites between groups of nursing sheep fed different protein levels were identified using partial least-squares discriminant analysis. The pathway enrichment revealed that dietary protein levels mainly influenced the metabolism-associated pathways (n = 63 and 39 in positive as well as negative ionic modes, respectively) followed by protein (n = 15 and 8 in positive as well as negative ionic modes, respectively) and amino-acid (n = 14 and 7 in positive as well as negative ionic modes, respectively) synthesis. Multivariate and univariate analyses showed comparative changes in the fecal concentrations of metabolites in both positive and negative ionic modes. Major changes were observed in protein metabolism, organic-acid biosynthesis, and fatty-acid oxidation. Pairwise analysis and PCA reveal a higher degree of aggregation within the D-h group than all other pairs. In both the PCA and PLS-DA plots, the comparative separation among the D_h/D_m, D_h/D_I, and D_m/D_I groups was superior in positive as well as negative ionic modes, which indicated that sheep fed higher protein levels had alterations in the levels of the metabolites. These metabolic findings provide insights into potentiated biomarker changes in the metabolism influenced by dietary protein levels. The target identification may further increase our knowledge of sheep gut metabolome, particularly regarding how dietary protein levels influence the molecular mechanisms of nutritional metabolism, growth performance, and milk synthesis of sheep.

Metabolomic-Based Approaches for Endometrial Cancer Diagnosis and Prognosis: A Review

Endometrial cancer, the most prevalent gynecological malignancy in developed countries, is experiencing a sustained rise in both its incidence and mortality rates, primarily attributed to extended life expectancy and lifestyle factors. Currently, the absence of precise diagnostic tools hampers the effective management of the expanding population of women at risk of developing this disease. Furthermore, patients diagnosed with endometrial cancer require precise risk stratification to align with optimal treatment planning. Metabolomics technology offers a unique insight into the molecular landscape of endometrial cancer, providing a promising approach to address these unmet needs. This comprehensive literature review initiates with an overview of metabolomic technologies and their intrinsic workflow components, aiming to establish a fundamental understanding for the readers. Subsequently, a detailed exploration of the existing body of research is undertaken with the objective of identifying metabolite biomarkers capable of enhancing current strategies for endometrial cancer diagnosis, prognosis, and recurrence monitoring. Metabolomics holds vast potential to revolutionize the management of endometrial cancer by providing accuracy and valuable insights into crucial aspects.

Pharmacokinetics in Pharmacometabolomics: Towards Personalized Medication

Indiscriminate drug administration may lead to drug therapy results with varying effects on patients, and the proposal of personalized medication can help patients to receive effective drug therapy. Conventional ways of personalized medication, such as pharmacogenomics and therapeutic drug monitoring (TDM), can only be implemented from a single perspective. The development of pharmacometabolomics provides a research method for the realization of precise drug administration, which integrates the environmental and genetic factors, and applies metabolomics technology to study how to predict different drug therapeutic responses of organisms based on baseline metabolic levels. The published research on pharmacometabolomics has achieved satisfactory results in predicting the pharmacokinetics, pharmacodynamics, and the discovery of biomarkers of drugs. Among them, the pharmacokinetics related to pharmacometabolomics are used to explore individual variability in drug metabolism from the level of metabolism of the drugs in vivo and the level of endogenous metabolite changes. By searching for relevant literature with the keyword "pharmacometabolomics" on the two major literature retrieval websites, PubMed and Web of Science, from 2006 to 2023, we reviewed articles in the field of pharmacometabolomics that incorporated pharmacokinetics into their research. This review explains the therapeutic effects of drugs on the body from the perspective of endogenous metabolites and pharmacokinetic principles, and reports the latest advances in pharmacometabolomics related to pharmacokinetics to provide research ideas and methods for advancing the implementation of personalized medication.

An epidemiological introduction to human metabolomic investigations

Metabolomics holds great promise for uncovering insights around biological processes impacting disease in human epidemiological studies. Metabolites can be measured across biological samples, including plasma, serum, saliva, urine, stool, and whole organs and tissues, offering a means to characterize metabolic processes relevant to disease etiology and traits of interest. Metabolomic epidemiology studies face unique challenges, such as identifying metabolites from targeted and untargeted assays, defining standards for quality control, harmonizing results across platforms that often capture different metabolites, and developing statistical methods for high-dimensional and correlated metabolomic data. In this review, we introduce metabolomic epidemiology to the broader scientific community, discuss opportunities and challenges presented by these studies, and highlight emerging innovations that hold promise to uncover new biological insights.

Untargeted hair lipidomics: comprehensive evaluation of the hair-specific lipid signature and considerations for retrospective analysis

Lipidomics investigates the composition and function of lipids, typically employing blood or tissue samples as the primary study matrices. Hair has recently emerged as a potential complementary sample type to identify biomarkers in early disease stages and retrospectively document an individual's metabolic status due to its long detection window of up to several months prior to the time of sampling. However, the limited coverage of lipid profiling presented in previous studies has hindered its exploitation. This study aimed to evaluate the lipid coverage of hair using an untargeted liquid chromatography-high-resolution mass spectrometry lipidomics platform. Two distinct three-step exhaustive extraction experiments were performed using a hair metabolomics one-phase extraction technique that has been recently optimized, and the two-phase Folch extraction method which is recognized as the gold standard for lipid extraction in biological matrices. The applied lipidomics workflow improved hair lipid coverage, as only 99 species could be annotated using the one-phase extraction method, while 297 lipid species across six categories were annotated with the Folch method. Several lipids in hair were reported for the first time, including N-acyl amino acids, diradylglycerols, and coenzyme Q10. The study suggests that hair lipids are not solely derived from de novo synthesis in hair, but are also incorporated from sebum and blood, making hair a valuable matrix for clinical, forensic, and dermatological research. The improved understanding of the lipid composition and analytical considerations for retrospective analysis offers valuable insights to contextualize untargeted hair lipidomic analysis and facilitate the use of hair in translational studies.

Metabolomics Approaches for the Diagnosis, Treatment, and Better Disease Management of Viral Infections

Metabolomics is an analytical approach that involves profiling and comparing the metabolites present in biological samples. This scoping review article offers an overview of current metabolomics approaches and their utilization in evaluating metabolic changes in biological fluids that occur in response to viral infections. Here, we provide an overview of metabolomics methods including high-throughput analytical chemistry and multivariate data analysis to identify the specific metabolites associated with viral infections. This review also focuses on data interpretation and applications designed to improve our understanding of the pathogenesis of these viral diseases.

A Scoping Review of Nutritional Biomarkers Associated with Food Security

Food insecurity affects more than 40 million individuals in the United States and is linked to negative health outcomes due, in part, to poor dietary quality. Despite the emergence of metabolomics as a modality to objectively characterize nutritional biomarkers, it is unclear whether food security is associated with any biomarkers of dietary quality. This scoping review aims to summarize studies that examined associations between nutritional biomarkers and food security, as well as studies that investigated metabolomic differences between people with and without food insecurity. PubMed, Embase, Scopus, and AGRICOLA were searched through August 2022 for studies describing food insecurity and metabolic markers in blood, urine, plasma, hair, or nails. The 78 studies included consisted of targeted assays quantifying lipids, dietary nutrients, heavy metals, and environmental xenobiotics as biochemical features associated with food insecurity. Among those biomarkers which were quantified in at least five studies, none showed a consistent association with food insecurity. Although three biomarkers of dietary quality have been assessed between food-insecure versus food-secure populations, no studies have utilized untargeted metabolomics to characterize patterns of small molecules that distinguish between these two populations. Further studies are needed to characterize the dietary quality profiles of individuals with and without food insecurity.

Optimization of fecal sample homogenization for untargeted metabolomics

INTRODUCTION

Fecal samples are highly complex and heterogeneous, containing materials at various stages of digestion. The heterogeneity and complexity of feces make stool metabolomics inherently challenging. The level of homogenization influences the outcome of the study, affecting the metabolite profiles and reproducibility; however, there is no consensus on how fecal samples should be prepared to overcome the topographical discrepancy and obtain data representative of the stool as a whole.

OBJECTIVES

Various combinations of homogenization conditions were compared to investigate the effects of bead size, addition of solvents and the differences between wet-frozen and lyophilized feces.

METHODS

The homogenization parameters were systematically altered to evaluate the solvent usage, bead size, and whether lyophilization is required in homogenization. The metabolic coverage and reproducibility were compared among the different conditions.

RESULTS

The current work revealed that a combination of mechanical and chemical lysis obtained by bead-beating with a mixture of big and small sizes of beads in an organic solvent is an effective way to homogenize fecal samples with adequate reproducibility and metabolic coverage. Lyophilization is required when bead-beating is not available.

CONCLUSIONS

A comprehensive and systematical evaluation of various fecal matter homogenization conditions provides a profound understanding for the effects of different homogenization methods. Our findings would be beneficial to assist with standardization of fecal sample homogenization protocol.

Untargeted metabonomic analysis of a cerebral stroke model in rats: a study based on UPLC-MS/MS

Introduction

Brain tissue damage caused by ischemic stroke can trigger changes in the body's metabolic response, and understanding the changes in the metabolic response of the gut after stroke can contribute to research on poststroke brain function recovery. Despite the increase in international research on poststroke metabolic mechanisms and the availability of powerful research tools in recent years, there is still an urgent need for poststroke metabolic studies. Metabolomic examination of feces from a cerebral ischemia-reperfusion rat model can provide new insights into poststroke metabolism and identify key metabolic pathways, which will help reveal diagnostic and therapeutic targets as well as inspire pathophysiological studies after stroke.

Methods

We randomly divided 16 healthy adult pathogen-free male Sprague-Dawley (SD) rats into the normal group and the study group, which received middle cerebral artery occlusion/reperfusion (MCAO/R). Ultra-performance liquid chromatography-tandem mass spectrometry (UPLCMS/MS) was used to determine the identities and concentrations of metabolites across all groups, and filtered high-quality data were analyzed for differential screening and differential metabolite functional analysis.

Results

After 1 and 14 days of modeling, compared to the normal group, rats in the study group showed significant neurological deficits (p < 0.001) and significantly increased infarct volume (day 1: p < 0.001; day 14: p = 0.001). Mass spectra identified 1,044 and 635 differential metabolites in rat feces in positive and negative ion modes, respectively, which differed significantly between the normal and study groups. The metabolites with increased levels identified in the study group were involved in tryptophan metabolism (p = 0.036678, p < 0.05), arachidonic acid metabolism (p = 0.15695), cysteine and methionine metabolism (p = 0.24705), and pyrimidine metabolism (p = 0.3413), whereas the metabolites with decreased levels were involved in arginine and proline metabolism (p = 0.15695) and starch and sucrose metabolism (p = 0.52256).

Discussion

We determined that UPLC-MS/MS could be employed for untargeted metabolomics research. Moreover, tryptophan metabolic pathways may have been disordered in the study group. Alterations in the tryptophan metabolome may provide additional theoretical and data support for elucidating stroke pathogenesis and selecting pathways for intervention.

Spatial Metabolome Lipidome and Glycome from a Single brain Section

Metabolites, lipids, and glycans are fundamental biomolecules involved in complex biological systems. They are metabolically channeled through a myriad of pathways and molecular processes that define the physiology and pathology of an organism. Here, we present a blueprint for the simultaneous analysis of spatial metabolome, lipidome, and glycome from a single tissue section using mass spectrometry imaging. Complimenting an original experimental protocol, our workflow includes a computational framework called Spatial Augmented Multiomics Interface (Sami) that offers multiomics integration, high dimensionality clustering, spatial anatomical mapping with matched multiomics features, and metabolic pathway enrichment to providing unprecedented insights into the spatial distribution and interaction of these biomolecules in mammalian tissue biology.

Pharmacometabolomics for the Study of Lipid-Lowering Therapies: Opportunities and Challenges

Lipid-lowering therapies are widely used to prevent the development of atherosclerotic cardiovascular disease (ASCVD) and related mortality worldwide. "Omics" technologies have been successfully applied in recent decades to investigate the mechanisms of action of these drugs, their pleiotropic effects, and their side effects, aiming to identify novel targets for future personalized medicine with an improvement of the efficacy and safety associated with the treatment. Pharmacometabolomics is a branch of metabolomics that is focused on the study of drug effects on metabolic pathways that are implicated in the variation of response to the treatment considering also the influences from a specific disease, environment, and concomitant pharmacological therapies. In this review, we summarized the most significant metabolomic studies on the effects of lipid-lowering therapies, including the most commonly used statins and fibrates to novel drugs or nutraceutical approaches. The integration of pharmacometabolomics data with the information obtained from the other "omics" approaches could help in the comprehension of the biological mechanisms underlying the use of lipid-lowering drugs in view of defining a precision medicine to improve the efficacy and reduce the side effects associated with the treatment.

Sample Preparation in Microbial Metabolomics: Advances and Challenges

Microbial metabolomics has gained significant interest as it reflects the physiological state of microorganisms. Due to the great variability of biological organisms, in terms of physicochemical characteristics and variable range of concentration of metabolites, the choice of sample preparation methods is a crucial step in the metabolomics workflow and will reflect on the quality and reliability of the results generated. The procedures applied to the preparation of microbial samples will vary according to the type of microorganism studied, the metabolomics approach (untargeted or targeted), and the analytical platform of choice. This chapter aims to provide an overview of the sample preparation workflow for microbial metabolomics, highlighting the pre-analytical factors associated with cultivation, harvesting, metabolic quenching, and extraction. Discussions focus on obtaining intracellular and extracellular metabolites. Finally, we introduced advanced sample preparation methods based on automated systems.

The untargeted urine volatilome for biomedical applications: methodology and volatilome database

Chemically diverse in compounds, urine can give us an insight into metabolic breakdown products from foods, drinks, drugs, environmental contaminants, endogenous waste metabolites, and bacterial by-products. Hundreds of them are volatile compounds; however, their composition has never been provided in detail, nor has the methodology used for urine volatilome untargeted analysis. Here, we summarize key elements for the untargeted analysis of urine volatilome from a comprehensive compilation of literature, including the latest reports published. Current achievements and limitations on each process step are discussed and compared. 34 studies were found retrieving all information from the urine treatment to the final results obtained. In this report, we provide the first specific urine volatilome database, consisting of 841 compounds from 80 different chemical classes.

Evaluation of fresh, frozen, and lyophilized fecal samples by SPME and derivatization methods using GC×GC-TOFMS

INTRODUCTION

Feces is a highly complex matrix containing thousands of metabolites. It also contains live bacteria and enzymes, and does not have a static chemistry. Consequently, proper control of pre-analytical parameters is critical to minimize unwanted variations in the samples. However, no consensus currently exists on how fecal samples should be stored/processed prior to analysis.

OBJECTIVE

The effects of sample handling conditions on fecal metabolite profiles and abundances were examined using comprehensive two-dimensional gas chromatography coupled to time-of-flight mass spectrometry (GC×GC-TOFMS).

METHODS

Solid-phase microextraction (SPME) and derivatization via trimethylsilylation (TMS) were employed as complementary techniques to evaluate fresh, frozen, and lyophilized fecal samples with expanded coverage of the fecal metabolome. The total number of detected peaks and the signal intensities were compared among the different handling conditions.

RESULTS

Our analysis revealed that the metabolic profiles of fecal samples depend greatly on sample handling and processing conditions, which had a more pronounced effect on results obtained by SPME than by TMS derivatization. Overall, lyophilization resulted in a greater amount of total and class-specific metabolites, which may be attributed to cell lysis and/or membrane disintegration.

CONCLUSIONS

A comprehensive comparison of the sample handling conditions provides a deeper understanding of the physicochemical changes that occur within the samples during freezing and lyophilization. Based on our results, snap-freezing at -80 °C would be preferred over lyophilization for handling samples in the field of fecal metabolomics as this imparts the least change from the fresh condition.

Recent Analytical Approaches for the Study of Bioavailability and Metabolism of Bioactive Phenolic Compounds

The study of the bioavailability of bioactive compounds is a fundamental step for the development of applications based on them, such as nutraceuticals, functional foods or cosmeceuticals. It is well-known that these compounds can undergo metabolic reactions before reaching therapeutic targets, which may also affect their bioactivity and possible applications. All recent studies that have focused on bioavailability and metabolism of phenolic and terpenoid compounds have been developed because of the advances in analytical chemistry and metabolomics approaches. The purpose of this review is to show the role of analytical chemistry and metabolomics in this field of knowledge. In this context, the different steps of the analytical chemistry workflow (design study, sample treatment, analytical techniques and data processing) applied in bioavailability and metabolism in vivo studies are detailed, as well as the most relevant results obtained from them.

A Checklist for Reproducible Computational Analysis in Clinical Metabolomics Research

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

Evaluation of ELISA for the analysis of imidacloprid in biological matrices: Cross-reactivities, matrix interferences, and comparison to LC-MS/MS

Imidacloprid is among the most used pesticides worldwide and there are toxicity concerns for nontarget organisms. Accurate and sensitive methods are necessary to quantitate imidacloprid concentrations in biological matrices to better understand their fate and effects. Here we evaluated an enzyme-linked immunosorbent assay (ELISA) kit for the analysis of imidacloprid in biological samples. Following the dosing of Japanese quail (Coturnix japonica) with imidacloprid-treated wheat seeds, plasma, liver, and fecal matter samples were analyzed by ELISA and compared to previous analyses that employed liquid chromatography-tandem mass spectrometry (LC-MS/MS). Imidacloprid metabolites-5-OH-imidacloprid, imidacloprid-olefin, imidacloprid-urea, desnitro-imidacloprid, and 6-chloronicotinic acid-were tested for their cross-reactivity to antibodies within the commercial imidacloprid ELISA kit. The two major metabolites, 5-OH-imidacloprid and imidacloprid-olefin, showed cross-reactivities of 0.93-26 %. ELISA and LC-MS/MS results were positively correlated but there was poor agreement in concentrations: plasma and fecal matter imidacloprid concentrations were higher by ELISA, whereas liver imidacloprid concentrations were higher by LC-MS/MS. Matrix interferences observed in analyses were minimized by the application of matrix-matched calibration curves. ELISA provided an effective screening tool for imidacloprid in these biological matrices, but the presence of cross-reactants confounded results. Confirmation of ELISA results by more selective techniques (e.g., LC-MS/MS) is suggested for complex samples.

Metabolomic Biomarkers to Predict and Diagnose Cystic Fibrosis Pulmonary Exacerbations: A Systematic Review

INTRODUCTION

Metabolomics is an emerging area of research and has the potential to identify clinical biomarkers for predicting or diagnosing cystic fibrosis (CF) pulmonary exacerbations (PEx).

OBJECTIVE

To identify clinically promising metabolites across different sample sources that can be used to predict or diagnose PEx in CF.

EVIDENCE REVIEW

Searches for original literature were completed through EMBASE, MEDLINE, and all databases on the Web of Science with no restrictions on language or publication date. Gray literature was collected through Google Scholar. Additional studies were obtained by contacting authors and searching reference lists of candidate papers. The patient population included individuals with CF. Studies involving patients who underwent lung transplantation were excluded. The outcome was the prediction or diagnosis of pulmonary exacerbations from metabolites directly measured from biological samples. Search results were downloaded and imported into Covidence and duplicates were removed automatically. Any remaining duplicates were manually tagged and excluded. Two independent reviewers screened each abstract for eligibility and repeated this process for full texts. Risk of bias was conducted using QUADAS-2 by two independent reviewers. A third author resolved any remaining conflicts.

RESULTS

A combined 3974 relevant abstracts were identified and 115 full texts were assessed for eligibility. The final 25 studies underwent data extraction for study design, patient demographics, studied metabolites, concentration values, and diagnostic accuracy values. Included studies differed considerably in methodologies, sample specimen types (exhaled breath condensate [EBC], sputum, saliva, plasma, urine), and disease states. We identified 19 unique metabolites that were measured by two or more studies of which 2 have the potential to predict PEx (EBC 4-hydroxycyclohexylcarboxylic acid [4-HCHC] and lactic acid) and 6 to diagnose PEx (EBC 4-HCHC and lactic acid, sputum lactic acid and nitrate, and plasma arginine and methionine).

CONCLUSION AND RELEVANCE

This systematic review has identified promising metabolites for further study in CF. Certain metabolites may provide clinical potential in predicting or diagnosing PEx, but further validation studies are required. With better tools to aid in the earlier identification of PEx, clinicians can implement preventative measures to mitigate airway damage.Systematic Review Registration: https://www.crd.york.ac.uk/prospero/.

Human metabolite detection by surface-enhanced Raman spectroscopy

Metabolites are important biomarkers in human body fluids, conveying direct information of cellular activities and physical conditions. Metabolite detection has long been a research hotspot in the field of biology and medicine. Surface-enhanced Raman spectroscopy (SERS), based on the molecular “fingerprint” of Raman spectrum and the enormous signal enhancement (down to a single-molecule level) by plasmonic nanomaterials, has proven to be a novel and powerful tool for metabolite detection. SERS provides favorable properties such as ultra-sensitive, label-free, rapid, specific, and non-destructive detection processes. In this review, we summarized the progress in recent 10 years on SERS-based sensing of endogenous metabolites at the cellular level, in tissues, and in biofluids, as well as drug metabolites in biofluids. We made detailed discussions on the challenges and optimization methods of SERS technique in metabolite detection. The combination of SERS with modern biomedical technology were also anticipated.

Inferring early-life host and microbiome functions by mass spectrometry-based metaproteomics and metabolomics

Humans have a long-standing coexistence with microorganisms. In particular, the microbial community that populates the human gastrointestinal tract has emerged as a critical player in governing human health and disease. DNA and RNA sequencing techniques that map taxonomical composition and genomic potential of the gut community have become invaluable for microbiome research. However, deriving a biochemical understanding of how activities of the gut microbiome shape host development and physiology requires an expanded experimental design that goes beyond these approaches. In this review, we explore advances in high-throughput techniques based on liquid chromatography-mass spectrometry. These omics methods for the identification of proteins and metabolites have enabled direct characterisation of gut microbiome functions and the crosstalk with the host. We discuss current metaproteomics and metabolomics workflows for producing functional profiles, the existing methodological challenges and limitations, and recent studies utilising these techniques with a special focus on early life gut microbiome.

Metabolic Fluctuations in the Human Stool Obtained from Blastocystis Carriers and Non-Carriers

Blastocystis is an obligate anaerobic microbial eukaryote that frequently inhabits the gastrointestinal tract. Despite this prevalence, very little is known about the extent of its genetic diversity, pathogenicity, and interaction with the rest of the microbiome and its host. Although the organism is morphologically static, it has no less than 28 genetically distinct subtypes (STs). Reports on the pathogenicity of Blastocystis are conflicting. The association between Blastocystis and intestinal bacterial communities is being increasingly explored. Nonetheless, similar investigations extending to the metabolome are non-existent.Using established NMR metabolomics protocols in 149 faecal samples from individuals from South Korea (n = 38), Thailand (n = 44) and Turkey (n = 69), we have provided a snapshot of the core metabolic compounds present in human stools with (B+) and without (B−) Blastocystis. Samples included hosts with gastrointestinal symptoms and asymptomatics. A total of nine, 62 and 98 significant metabolites were associated with Blastocystis carriage in the South Korean, Thai and Turkish sample sets respectively, with a number of metabolites increased in colonised groups. The metabolic profiles of B+ and B− samples from all countries were distinct and grouped separately in the partial least squares-discriminant analysis (PLS-DA). Typical inflammation-related metabolites negatively associated with Blastocystis positive samples. This data will assist in directing future studies underlying the involvement of Blastocystis in physiological processes of both the gut microbiome and the host. Future studies using metabolome and microbiome data along with host physiology and immune responses information will contribute significantly towards elucidating the role of Blastocystis in health and disease.

Comparison of metabolic fate, target organs, and microbiota interactions of free and bound dietary advanced glycation end products

Increased intake of Western diets and ultra-processed foods is accompanied by increased intake of advanced glycation end products (AGEs). AGEs can be generated exogenously in the thermal processing of food and endogenously in the human body, which associated with various chronic diseases. In food, AGEs can be divided into free and bound forms, which differ in their bioavailability, digestion, absorption, gut microbial interactions and untargeted metabolites. We summarized the measurements and contents of free and bound AGE in foods. Moreover, the ingestion, digestion, absorption, excretion, gut microbiota interactions, and metabolites and metabolic pathways between free and bound AGEs based on animal and human studies were compared. Bound AGEs were predominant in most of the selected foods, while beer and soy sauce were rich in free AGEs. Only 10%-30% of AGEs were absorbed into the systemic circulation when orally administered. The excretion of ingested free and bound AGEs was approximately 90% and 60%, respectively. Dietary free CML has a detrimental effect on gut microbiota composition, while bound AGEs have both detrimental and beneficial impacts. Free and bound dietary AGEs changed amino acid metabolism, energy metabolism and carbohydrate metabolism. And besides, bound dietary AGEs altered vitamin metabolism, and glycerolipid metabolism.

Toxicometabolomics: Small Molecules to Answer Big Toxicological Questions

Given the high biological impact of classical and emerging toxicants, a sensitive and comprehensive assessment of the hazards and risks of these substances to organisms is urgently needed. In this sense, toxicometabolomics emerged as a new and growing field in life sciences, which use metabolomics to provide new sets of susceptibility, exposure, and/or effects biomarkers; and to characterize in detail the metabolic responses and altered biological pathways that various stressful stimuli cause in many organisms. The present review focuses on the analytical platforms and the typical workflow employed in toxicometabolomic studies, and gives an overview of recent exploratory research that applied metabolomics in various areas of toxicology.

Metabolomic Studies for Metabolic Alterations Induced by Non-Steroidal Anti-Inflammatory Drugs: Mini Review

Non-steroidal anti-inflammatory drugs (NSAIDs) are Food and Drug Administration (FDA) approved antipyretic, anti-inflammatory, and analgesic drugs to mitigate pain, however it is associated with gastrointestinal injury and cardiovascular disease in some individuals. Metabolomics has the potential to understand the interaction of host and the drugs, such as NSAIDs administration. This discipline has been used by many researchers to understand the serious side effects of NSAIDs. We highlighted (1) the potential of metabolomics in understanding the pathogenesis of adverse events due to NSAIDs administration; (2) choice of metabolomics techniques, bio sample handling; (3) review of metabolomics studies in the front of NSAIDs in different biofluids and tissues; (4) pathway analysis of the data presented in the published literature. In our analysis we find tricarboxylic acid cycle (TCA), "glycine serine and threonine metabolism," "alanine, aspartate, and glutamate metabolism," and fatty acid metabolism to be altered by the NSAIDs like ibuprofen, indomethacin, naproxen, aspirin, and celecoxib. In conclusion, metabolomics allows the use of biological samples to identify useful pathways involved in disease progression, and subsequently inform a greater understanding of the disease pathogenesis. A further in-depth investigation of the associated pathways mentioned above holds the potential for drug targets for side effects mitigation.

Chronic Kidney Disease Cohort Studies: A Guide to Metabolome Analyses

Kidney diseases still pose one of the biggest challenges for global health, and their heterogeneity and often high comorbidity load seriously hinders the unraveling of their underlying pathomechanisms and the delivery of optimal patient care. Metabolomics, the quantitative study of small organic compounds, called metabolites, in a biological specimen, is gaining more and more importance in nephrology research. Conducting a metabolomics study in human kidney disease cohorts, however, requires thorough knowledge about the key workflow steps: study planning, sample collection, metabolomics data acquisition and preprocessing, statistical/bioinformatics data analysis, and results interpretation within a biomedical context. This review provides a guide for future metabolomics studies in human kidney disease cohorts. We will offer an overview of important a priori considerations for metabolomics cohort studies, available analytical as well as statistical/bioinformatics data analysis techniques, and subsequent interpretation of metabolic findings. We will further point out potential research questions for metabolomics studies in the context of kidney diseases and summarize the main results and data availability of important studies already conducted in this field.

Impact of acute lymphoblastic leukemia induction therapy: findings from metabolomics on non-fasted plasma samples from a biorepository

INTRODUCTION

Acute lymphoblastic leukemia (ALL) is among the most common cancers in children. With improvements in combination chemotherapy regimens, the overall survival has increased to over 90%. However, the current challenge is to mitigate adverse events resulting from the complex therapy. Several chemotherapies intercept cancer metabolism, but little is known about their collective role in altering host metabolism.

OBJECTIVES

We profiled the metabolomic changes in plasma of ALL patients initial- and post- induction therapy.

METHODS

We exploited a biorepository of non-fasted plasma samples derived from the Dana Farber Cancer Institute ALL Consortium; these samples were obtained from 50 ALL patients initial- and post-induction therapy. Plasma metabolites and complex lipids were analyzed by high resolution tandem mass spectrometry and differential mobility tandem mass spectrometry. Data were analyzed using a covariate-adjusted regression model with multiplicity adjustment. Pathway enrichment analysis and co-expression network analysis were performed to identify unique clusters of molecules.

RESULTS

More than 1200 metabolites and complex lipids were identified in the total of global metabolomics and lipidomics platforms. Over 20% of those molecules were significantly altered. In the pathway enrichment analysis, lipids, particularly phosphatidylethanolamines (PEs), were identified. Network analysis indicated that the bioactive fatty acids, docosahexaenoic acid (DHA)-containing (22:6) triacylglycerols (TAGs), were decreased in the post-induction therapy.

CONCLUSION

Metabolomic profiling in ALL patients revealed a large number of alterations following induction chemotherapy. In particular, lipid metabolism was substantially altered. The changes in metabolites and complex lipids following induction therapy could provide insight into the adverse events experienced by ALL patients.

Elevated levels of urine isocitrate, hydroxymethylglutarate, and formiminoglutamate are associated with arterial stiffness in Korean adults

Recent evidence suggests that cellular perturbations play an important role in the pathogenesis of cardiovascular diseases. Therefore, we analyzed the association between the levels of urinary metabolites and arterial stiffness. Our cross-sectional study included 330 Korean men and women. The brachial-ankle pulse wave velocity was measured as a marker of arterial stiffness. Urinary metabolites were evaluated using a high-performance liquid chromatograph-mass spectrometer. The brachial-ankle pulse wave velocity was found to be positively correlated with l-lactate, citrate, isocitrate, succinate, malate, hydroxymethylglutarate, α-ketoisovalerate, α-keto-β-methylvalerate, methylmalonate, and formiminoglutamate among men. Whereas, among women, the brachial-ankle pulse wave velocity was positively correlated with cis-aconitate, isocitrate, hydroxymethylglutarate, and formiminoglutamate. In the multivariable regression models adjusted for conventional cardiovascular risk factors, three metabolite concentrations (urine isocitrate, hydroxymethylglutarate, and formiminoglutamate) were independently and positively associated with brachial-ankle pulse wave velocity. Increased urine isocitrate, hydroxymethylglutarate, and formiminoglutamate concentrations were associated with brachial-ankle pulse wave velocity and independent of conventional cardiovascular risk factors. Our findings suggest that metabolic disturbances in cells may be related to arterial stiffness.

The Effects of Sampling and Storage Conditions on the Metabolite Profile of the Marine Sponge Geodia barretti

Geodia barretti is a deep-sea marine sponge common in the north Atlantic and waters outside of Norway and Sweden. The sampling and subsequent treatment as well as storage of sponges for metabolomics analyses can be performed in different ways, the most commonly used being freezing (directly upon collection or later) or by storage in solvent, commonly ethanol, followed by freeze-drying. In this study we therefore investigated different sampling protocols and their effects on the detected metabolite profiles in liquid chromatography-mass spectrometry (LC-MS) using an untargeted metabolomics approach. Sponges (G. barretti) were collected outside the Swedish west coast and pieces from three sponge specimens were either flash frozen in liquid nitrogen, frozen later after the collection cruise, stored in ethanol or stored in methanol. The storage solvents as well as the actual sponge pieces were analyzed, all samples were analyzed with hydrophilic interaction liquid chromatography as well as reversed phase liquid chromatography with high resolution mass spectrometry using full-scan in positive and negative ionization mode. The data were evaluated using multivariate data analysis. The highest metabolite intensities were found in the frozen samples (flash frozen and frozen after sampling cruise) as well as in the storage solvents (methanol and ethanol). Metabolites extracted from the sponge pieces that had been stored in solvent were found in very low intensity, since the majority of metabolites were extracted to the solvents to a high degree. The exception being larger peptides and some lipids. The lowest variation between replicates were found in the flash frozen samples. In conclusion, the preferred method for sampling of sponges for metabolomics was found to be immediate freezing in liquid nitrogen. However, freezing the sponge samples after some time proved to be a reliable method as well, albeit with higher variation between the replicates. The study highlights the importance of saving ethanol extracts after preservation of specimens for biology studies; these valuable extracts could be further used in studies of natural products, chemosystematics or metabolomics.

Metabolomic Biomarkers of Healthy Dietary Patterns and Cardiovascular Outcomes

PURPOSE OF REVIEW

Healthy dietary patterns are recommended for prevention of CVD. Recently, metabolomics has been used to identify biomarkers of healthy dietary patterns and elucidate mechanisms underlying diet-disease associations. This review provides an overview of approaches to define healthy dietary patterns, discusses important issues related to using metabolomics to describe healthy dietary patterns, and summarizes studies identifying blood metabolites associated with hypothesis-driven healthy dietary patterns and cardiovascular risk factors and incident CVD.

RECENT FINDINGS

We identified 17 studies which reported on blood metabolomic signatures of 5 healthy dietary patterns (Healthy Eating Index, Alternative Healthy Eating Index, the Dietary Approaches to Stop Hypertension diet, Mediterranean diet, vegetarian diet). Four of these studies evaluated associations between diet-related metabolites and cardiovascular outcomes. Many metabolites replicated across different healthy dietary patterns, which suggest that they may represent biomarkers of generally healthy diets. Unsaturated lipids positively associated with healthy dietary patterns were inversely associated with incident CVD, suggesting that they may be a pathway through which diet is associated with a lower risk of CVD. Although many metabolites replicated across cross-sectional studies, few metabolites identified as candidate biomarkers of healthy diets in feeding studies replicated in observational studies. Additionally, limited evidence exists on the ability of diet-related metabolites to predict cardiovascular outcomes. Replication of candidate biomarkers of dietary patterns in different study designs and more studies evaluating the associations between diet-related metabolites and cardiovascular outcomes are needed.

Approaches in metabolomics for regulatory toxicology applications

Innovative methodological approaches are needed to conduct human health and environmental risk assessments on a growing number of marketed chemicals. Metabolomics is progressively proving its value as an efficient strategy to perform toxicological evaluations of new and existing substances, and it will likely become a key tool to accelerate chemical risk assessments. However, additional guidance with widely accepted and harmonized procedures is needed before metabolomics can be routinely incorporated in decision-making for regulatory purposes. The aim of this review is to provide an overview of metabolomic strategies that have been successfully employed in toxicity assessment as well as the most promising workflows in a regulatory context. First, we provide a general view of the different steps of regulatory toxicology-oriented metabolomics. Emphasis is put on three key elements: robustness of experimental design, choice of analytical platform, and use of adapted data treatment tools. Then, examples in which metabolomics supported regulatory toxicology outputs in different scenarios are reviewed, including chemical grouping, elucidation of mechanisms of toxicity, and determination of points of departure. The overall intention is to provide insights into why and how to plan and conduct metabolomic studies for regulatory toxicology purposes.

Applications of Omics Technologies for Three-Dimensional In Vitro Disease Models

Omics technologies, such as genomics, epigenomics, transcriptomics, proteomics, metabolomics, lipidomics, multiomics, and integrated modalities, have greatly contributed to our understanding of various diseases by enabling researchers to probe the molecular wiring of cellular systems in a high-throughput and precise manner. With the development of tissue-engineered three-dimensional (3D) in vitro disease models, such as organoids and spheroids, there is potential of integrating omics technologies with 3D disease models to elucidate the complex links between genotype and phenotype. These 3D disease models have been used to model cancer, infectious disease, toxicity, neurological disorders, and others. In this review, we provide an overview of omics technologies, highlight current and emerging studies, discuss the associated experimental design considerations, barriers and challenges of omics technologies, and provide an outlook on the future applications of omics technologies with 3D models. Overall, this review aims to provide a valuable resource for tissue engineers seeking to leverage omics technologies for diving deeper into biological discovery. Impact statement With the emergence of three-dimensional (3D) in vitro disease models, tissue engineers are increasingly interested to investigate these systems to address biological questions related to disease mechanism, drug target discovery, therapy resistance, and more. Omics technologies are a powerful and high-throughput approach, but their application for 3D disease models is not maximally utilized. This review illustrates the achievements and potential of using omics technologies to leverage the full potential of 3D in vitro disease models. This will improve the quality of such models, advance our understanding of disease, and contribute to therapy development.

High-coverage quantitative liver metabolomics using perfused and non-perfused liver tissues

Comprehensive analysis of the liver metabolome can be very useful for discovering disease biomarkers and studying diseases, especially liver-related diseases. However, the presence of a relatively large amount of blood in liver tissue may have a profound effect on liver tissue metabolome analysis. We designed a study to address this issue in order to develop a liver metabolomics workflow based on high-coverage quantitative metabolome analysis using differential chemical isotope labeling (CIL) LC-MS. In the first set of experiments, we compared the metabolomes of mouse serum, non-perfused liver, and perfused liver without and with varying amounts of blood added. We found that there was a significant metabolome difference between the perfused liver and non-perfused liver. To illustrate the effects of perfusion conditions on tissue metabolome analysis, we analyzed the mouse livers that were subjected to perfusion under two different conditions. We found that ice-cold temperature perfusion led to less change of the liver metabolome, compared to room temperature perfusion; however, there was still a significant metabolome difference between the ice-cold-perfused liver and the non-perfused liver. Finally, we applied the method to a chemical (carbon tetrachloride) exposure liver injury model to examine the effects of blood in liver on the detection of significantly changed metabolites in two comparative groups of mice. Using multivariate and univariate analyses of the serum and liver metabolomes of control and diseased mice, we detected many unique significant metabolites in serum as well as in liver. This work demonstrates that perfusion can alter the liver metabolome significantly. Therefore, we recommend the use of non-perfused liver for high-coverage liver metabolomics.

On the Variability of Microbial Populations and Bacterial Metabolites within the Canine Stool. An in-Depth Analysis

Simple Summary

The present study investigated for the first time the impact that different sampling points have on the abundance of microbial populations and metabolites within the canine stool. We found that inner stool subsamples resulted in higher concentrations of bacterial metabolites but not of microbial populations. These findings suggest that stool subsampling is unlikely to represent the canine microbiota and metabolome uniformly. We believe that complete homogenisation of the whole stool prior to analysis may improve the final outcome when investigating the canine gut microbiome.

Abstract

Canine faecal microbial populations and metabolome are being increasingly studied to understand the interplay between host and gut microbiome. However, the distribution of bacterial taxa and microbial metabolites throughout the canine stool is understudied and currently no guidelines for the collection, storage and preparation of canine faecal samples have been proposed. Here, we assessed the effects that different sampling points have on the abundance of selected microbial populations and bacterial metabolites within the canine stool. Whole fresh faecal samples were obtained from five healthy adult dogs. Stool subsamples were collected from the surface to the inner part and from three equally sized areas (cranial, central, caudal) along the length axis of the stool log. All samples were finally homogenised and compared before and after homogenisation. Firmicutes, Bacteroidetes, Clostridium cluster I, Lactobacillus spp., Bifidobacterium spp. and Enterococcus spp. populations were analysed, as well as pH, ammonia and short-chain fatty acids (SCFA) concentrations. Compared to the surface of the stool, inner subsamples resulted in greater concentrations of SCFA and ammonia, and lower pH values. qPCR assay of microbial taxa did not show any differences between subsamples. Homogenisation of faeces does not affect the variability of microbial and metabolome data. Although the distribution patterns of bacterial populations and metabolites are still unclear, we found that stool subsampling yielded contradictory result and biases that can affect the final outcome when investigating the canine microbiome. Complete homogenisation of the whole stool is therefore recommended.

In vivo toxicometabolomics reveals multi-organ and urine metabolic changes in mice upon acute exposure to human-relevant doses of 3,4-methylenedioxypyrovalerone (MDPV)

3,4-Methylenedioxypyrovalerone (MDPV) is consumed worldwide, despite its potential to cause toxicity in several organs and even death. There is a recognized need to clarify the biological pathways through which MDPV elicits general and target-organ toxicity. In this work, a comprehensive untargeted GC-MS-based metabolomics analysis was performed, aiming to detect metabolic changes in putative target organs (brain, heart, kidneys and liver) but also in urine of mice after acute exposure to human-relevant doses of MDPV. Male CD-1 mice received binge intraperitoneal administrations of saline or MDPV (2.5 mg/kg or 5 mg/kg) every 2 h, for a total of three injections. Twenty-four hours after the first administration, target organs, urine and blood samples were collected for metabolomics, biochemical and histological analysis. Hepatic and renal tissues of MDPV-treated mice showed moderate histopathological changes but no significant differences were found in plasma and tissue biochemical markers of organ injury. In contrast, the multivariate analysis significantly discriminated the organs and urine of MDPV-treated mice from the control (except for the lowest dose in the brain), allowing the identification of a panoply of metabolites. Those levels were significantly deviated in relation to physiological conditions and showed an organ specific response towards the drug. Kidneys and liver showed the greatest metabolic changes. Metabolites related with energetic metabolism, antioxidant defenses and inflammatory response were significantly changed in the liver of MDPV-dosed animals, while the kidneys seem to have developed an adaptive response against oxidative stress caused by MDPV. On the other hand, the dysregulation of metabolites that contribute to metabolic acidosis was also observed in this organ. The heart showed an increase of fatty acid biosynthesis, possibly as an adaptation to maintain the cardiac energy homeostasis. In the brain, changes in 3-hydroxybutyric acid levels may reflect the activation of a neurotoxic pathway. However, the increase in metabolites with neuroprotective properties seems to counteract this change. Metabolic profiling of urine from MDPV-treated mice suggested that glutathione-dependent antioxidant pathways may be particularly involved in the compensatory mechanism to counteract oxidative stress induced by MDPV. Overall, this study reports, for the first time, the metabolic profile of liver, kidneys, heart, brain, and urine of MDPV-dosed mice, providing unique insights into the biological pathways of toxicity. Our findings also underline the value of toxicometabolomics as a robust and sensitive tool for detecting adaptive/toxic cellular responses upon exposure to a physiologically relevant dose of a toxic agent, earlier than conventional toxicity tests.

Individualizing pharmacogenomic test results in the context of the microbiome

The field of pharmacogenetic testing was hailed as one of the early successful clinical applications arising from the personalized (or precision) medicine revolution. Substantial progress has been made to identify genes and genetic variants involved in drug response and establish clinical implementation programs. Yet, drug response is a complex trait and recent work has highlighted the key role played by the gut microbiome. As the study of the gut microbiome and pharmacogenetics converge, it may be possible to generate more precise predictions of drug response and improve health outcomes to treatments. Substantial effort will be needed to understand the dynamic impact of the microbiome and the interplay with host genetics and how to implement expanded pharmacogenetic testing.

A Review of GC-Based Analysis of Non-Invasive Biomarkers of Colorectal Cancer and Related Pathways

Colorectal cancer (CRC) is the third most commonly diagnosed cancer in the world. In Europe, it is the second most common cause of cancer-related deaths. With the advent of metabolomics approaches, studies regarding the investigation of metabolite profiles related to CRC have been conducted, aiming to serve as a tool for early diagnosis. In order to provide further information about the current status of this field of research, 21 studies were systematically reviewed, regarding their main findings and analytical aspects. A special focus was given to the employment of matrices obtained non-invasively and the use of gas chromatography as the analytical platform. The relationship between the reported volatile and non-volatile biomarkers and CRC-related metabolic alterations was also explored, demonstrating that many of these metabolites are connected with biochemical pathways proven to be involved in carcinogenesis. The most commonly reported CRC indicators were hydrocarbons, aldehydes, amino acids and short-chain fatty acids. These potential biomarkers can be associated with both human and bacterial pathways and the analysis based on such species has the potential to be applied in the clinical practice as a low-cost screening method.

Metabolomic Approaches to Study Chemical Exposure-Related Metabolism Alterations in Mammalian Cell Cultures

Biological organisms are constantly exposed to an immense repertoire of molecules that cover environmental or food-derived molecules and drugs, triggering a continuous flow of stimuli-dependent adaptations. The diversity of these chemicals as well as their concentrations contribute to the multiplicity of induced effects, including activation, stimulation, or inhibition of physiological processes and toxicity. Metabolism, as the foremost phenotype and manifestation of life, has proven to be immensely sensitive and highly adaptive to chemical stimuli. Therefore, studying the effect of endo- or xenobiotics over cellular metabolism delivers valuable knowledge to apprehend potential cellular activity of individual molecules and evaluate their acute or chronic benefits and toxicity. The development of modern metabolomics technologies such as mass spectrometry or nuclear magnetic resonance spectroscopy now offers unprecedented solutions for the rapid and efficient determination of metabolic profiles of cells and more complex biological systems. Combined with the availability of well-established cell culture techniques, these analytical methods appear perfectly suited to determine the biological activity and estimate the positive and negative effects of chemicals in a variety of cell types and models, even at hardly detectable concentrations. Metabolic phenotypes can be estimated from studying intracellular metabolites at homeostasis in vivo, while in vitro cell cultures provide additional access to metabolites exchanged with growth media. This article discusses analytical solutions available for metabolic phenotyping of cell culture metabolism as well as the general metabolomics workflow suitable for testing the biological activity of molecular compounds. We emphasize how metabolic profiling of cell supernatants and intracellular extracts can deliver valuable and complementary insights for evaluating the effects of xenobiotics on cellular metabolism. We note that the concepts and methods discussed primarily for xenobiotics exposure are widely applicable to drug testing in general, including endobiotics that cover active metabolites, nutrients, peptides and proteins, cytokines, hormones, vitamins, etc.

The role of gut microbiota (GM) and GM-related metabolites in diabetes and obesity. A review of analytical methods used to measure GM-related metabolites in fecal samples with a focus on metabolites' derivatization step

Disruption of gut microbiota (GM) composition is increasingly related to the pathogenesis of various metabolic diseases. Additionally, GM is responsible for the production and transformation of metabolites involved in the development of metabolic disorders, such as obesity and type 2 diabetes mellitus (T2DM). The current state of knowledge regarding the composition of GM and GM-related metabolites in relation to the progress and development of obesity and T2DM is presented in this review. To understand the relationships between GM-related metabolites and the development of metabolic disorders, their accurate qualitative and quantitative measurement in biological samples is needed. Feces represent a valuable biological matrix which composition may reflect the health status of the lower gastrointestinal tract and the whole organism. Mass spectrometry (MS), mainly in combination with gas chromatography (GC) or liquid chromatography (LC), is commonly used to measure fecal metabolites. However, profiling metabolites in such a complex matrix as feces is challenging from both analytical chemistry and biochemistry standpoints. Chemical derivatization is one of the most effective methods used to overcome these problems. In this review, we provide a comprehensive summary of the derivatization methods of GM-related metabolites prior to GC-MS or LC-MS analysis, which have been published in the last five years (2015-2020). Additionally, analytical methods used for the analysis of GM-related metabolites without the derivatization step are also presented.

An Optimized Dual Extraction Method for the Simultaneous and Accurate Analysis of Polar Metabolites and Lipids Carried out on Single Biological Samples

The functional understanding of metabolic changes requires both a significant investigation into metabolic pathways, as enabled by global metabolomics and lipidomics approaches, and the comprehensive and accurate exploration of specific key pathways. To answer this pivotal challenge, we propose an optimized approach, which combines an efficient sample preparation, aiming to reduce the variability, with a biphasic extraction method, where both the aqueous and organic phases of the same sample are used for mass spectrometry analyses. We demonstrated that this double extraction protocol allows working with one single sample without decreasing the metabolome and lipidome coverage. It enables the targeted analysis of 40 polar metabolites and 82 lipids, together with the absolute quantification of 32 polar metabolites, providing comprehensive coverage and quantitative measurement of the metabolites involved in central carbon energy pathways. With this method, we evidenced modulations of several lipids, amino acids, and energy metabolites in HepaRG cells exposed to fenofibrate, a model hepatic toxicant, and metabolic modulator. This new protocol is particularly relevant for experiments involving limited amounts of biological material and for functional metabolic explorations and is thus of particular interest for studies aiming to decipher the effects and modes of action of metabolic disrupting compounds.