A validated multi-matrix platform for metabolomic fingerprinting of human urine, feces and plasma using ultra-high performance liquid-chromatography coupled to hybrid orbitrap high-resolution mass spectrometry

Optimization and validation of metabolomics methods for feline urine and serum towards application in veterinary medicine

BACKGROUND

Metabolomics is an emerging and powerful technology that offers a comprehensive view of an organism's physiological status. Although widely applied in human medicine, it is only recently making its introduction in veterinary medicine. As a result, validated metabolomics protocols in feline medicine are lacking at the moment. Since biological interpretation of metabolomics data can be misled by the extraction method used, species and matrix-specific optimized and validated metabolomic protocols are sorely needed.

RESULTS

Systematic optimization was performed using fractional factorial experiments for both serum (n = 57) and urine (n = 24), evaluating dilution for both matrices, and aliquot and solvent volume, protein precipitation time and temperature for serum. For the targeted (n = 76) and untargeted (n = 1949) validation of serum respectively, excellent instrumental, intra-assay and inter-day precision were observed (CV ≤ 15% or 30%, respectively). Linearity deemed sufficient both targeted and untargeted (R2 ≥ 0.99 or 0.90, respectively). An appropriate targeted recovery between 70 and 130% was achieved. For the targeted (n = 69) and untargeted (n = 2348) validation of the urinary protocol, excellent instrumental and intra-assay precision were obtained (CV ≤ 15% or 30%, respectively). Subsequently, the discriminative ability of our metabolomics methods was confirmed for feline chronic kidney disease (CKD) by univariate statistics (n = 41 significant metabolites for serum, and n = 55 for urine, p-value<0.05) and validated OPLS-DA models (R2(Y) > 0.95, Q2(Y) > 0.65, p-value<0.001 for both matrices).

SIGNIFICANCE

This study is the first to present an optimized and validated wholistic metabolomics methods for feline serum and urine using ultra-high performance liquid chromatography coupled to quadrupole-Orbitrap high-resolution mass spectrometry. This robust methodology opens avenues for biomarker panel selection and a deeper understanding of feline CKD pathophysiology and other feline applications.

Towards a better understanding of idiopathic epilepsy through metabolic fingerprinting of cerebrospinal fluid in dogs

Cerebrospinal fluid metabolomics is a promising research technology in the elucidation of nervous system disorders. Therefore, in this work, a cerebrospinal fluid (CSF) metabolomics method using liquid chromatography coupled to mass spectrometry was optimized and validated to cover a wide range of metabolites. An acceptable coefficient of variance regarding instrumental, within-lab and intra-assay precision was found for 95, 70 and 96 of 102 targeted metabolites, together with 1256, 676 and 976 untargeted compounds, respectively. Moreover, approximately 75% of targeted metabolites and 50% of untargeted compounds displayed good linearity across different dilution ranges. Consequently, metabolic alterations in CSF of dogs with idiopathic epilepsy (IE) were studied by comparing CSF of dogs diagnosed with IE (Tier II) to dogs with non-brain related disease. Targeted metabolome analysis revealed higher levels of cortisol, creatinine, glucose, hippuric acid, mannose, pantothenol, and 2-phenylethylamine (P values < 0.05) in CSF of dogs with IE, whereas CSF of dogs with IE showed lower levels of spermidine (P value = 0.02). Untargeted CSF metabolic fingerprints discriminated dogs with IE from dogs with non-brain related disease using Orthogonal Partial Least Squares Discriminant Analysis (R2(Y) = 0.997, Q2(Y) = 0.828), from which norepinephrine was putatively identified as an important discriminative metabolite.

Development and validation of a versatile non-invasive urinary steroidomics method for wildlife biomonitoring

Wildlife conservation is often challenged by a lack of knowledge about the reproduction biology and adaptability of endangered species. Although monitoring steroids and related molecules can increase this knowledge, the applicability of current techniques (e.g. immunoassays) is hampered by species-specific steroid metabolism and the requisite to avoid invasive sampling. This study presents a validated steroidomics method for the (un)targeted screening of a wide range of sex and stress steroids and related molecules in urine using ultra-high performance liquid chromatography coupled to high-resolution mass spectrometry (UHPLC-HRMS). In total, 50 steroids (conjugated and non-conjugated androgens, estrogens, progestogens and glucocorticoids) and 6 prostaglandins could be uniquely detected. A total of 45 out of 56 compounds demonstrated a detection limit below 0.01 ng μL-1. Excellent linearity (R2 > 0.99), precision (CV < 20 %), and recovery (80-120 %) were observed for 46, 41, and 39 compounds, respectively. Untargeted screening of pooled giant panda and human samples yielded 9691 and 8366 features with CV < 30 %, from which 84.1 % and 83.0 %, respectively, also demonstrated excellent linearity (R2 > 0.90). The biological validity of the method was investigated on male and female giant panda urine (n = 20), as well as pooled human samples (n = 10). A total of 24 different steroids were detected with clear qualitative and quantitative differences between human and giant panda samples. Furthermore, expected differences were revealed between female giant panda samples from different reproductive phases. In contrast to traditional biomonitoring techniques, the developed steroidomics method was able to screen a wide range of compounds and provide information on the putative identities of metabolites potentially important for reproductive monitoring in giant pandas. These results illustrate the advancements steroidomics brings to the field of wildlife biomonitoring in the pursuit to better understand the biology of endangered species.

Impact of Distinct Anti-Androgen Exposures on the Plasma Metabolome in Feminizing Gender-Affirming Hormone Therapy

CONTEXT

The plasma metabolome is a functional readout of metabolic activity and is associated with phenotypes exhibiting sexual dimorphism, such as cardiovascular disease. Sex hormones are thought to play a key role in driving sexual dimorphism.

OBJECTIVE

Gender-affirming hormone therapy (GAHT) is a cornerstone of transgender care, but longitudinal changes in the plasma metabolome with feminizing GAHT have not been described.

METHODS

Blood samples were collected at baseline and after three and six months of GAHT from transgender women (n = 53). Participants were randomized to different anti-androgens, cyproterone acetate or spironolactone. NMR-based metabolomics was used to measure 249 metabolic biomarkers in plasma. Additionally, we used metabolic biomarker data from an unrelated cohort of children and their parents (n = 3,748) to identify sex- and age-related metabolite patterns.

RESULTS

We identified 43 metabolic biomarkers altered after six months in both anti-androgen groups, most belonging to the very low- or low-density lipoprotein subclasses, with all but one showing a decrease. We observed a cyproterone acetate-specific decrease in glutamine, glycine, and alanine levels. Notably, of the metabolic biomarkers exhibiting the most abundant 'sex- and age-related' pattern (higher in assigned female children and lower in assigned female adults, relative to assigned males), 80% were significantly lowered after GAHT, reflecting a shift toward the adult female profile.

CONCLUSION

Our results suggest an anti-atherogenic signature in the plasma metabolome after the first six months of feminizing GAHT, with cyproterone acetate also reducing specific plasma amino acids. This study provides novel insight into the metabolic changes occurring across feminizing GAHT.

Integrated gut metabolome and microbiome fingerprinting reveals that dysbiosis precedes allergic inflammation in IgE-mediated pediatric cow's milk allergy

BACKGROUND

IgE-mediated cow's milk allergy (IgE-CMA) is one of the first allergies to arise in early childhood and may result from exposure to various milk allergens, of which β-lactoglobulin (BLG) and casein are the most important. Understanding the underlying mechanisms behind IgE-CMA is imperative for the discovery of novel biomarkers and the design of innovative treatment and prevention strategies.

METHODS

We report a longitudinal in vivo murine model, in which two mice strains (BALB/c and C57Bl/6) were sensitized to BLG using either cholera toxin or an oil emulsion (n = 6 per group). After sensitization, mice were challenged orally, their clinical signs monitored, antibody (IgE and IgG1) and cytokine levels (IL-4 and IFN-γ) measured, and fecal samples subjected to metabolomics. The results of the murine models were further extrapolated to fecal microbiome-metabolome data from our population of IgE-CMA (n = 22) and healthy (n = 23) children (Trial: NCT04249973), on which polar metabolomics, lipidomics and 16S rRNA metasequencing were performed. In vitro gastrointestinal digestions and multi-omics corroborated the microbial origin of proposed metabolic changes.

RESULTS

During mice sensitization, we observed multiple microbially derived metabolic alterations, most importantly bile acid, energy and tryptophan metabolites, that preceded allergic inflammation. We confirmed microbial dysbiosis, and its associated effect on metabolic alterations in our patient cohort, through in vitro digestions and multi-omics, which was accompanied by metabolic signatures of low-grade inflammation.

CONCLUSION

Our results indicate that gut dysbiosis precedes allergic inflammation and nurtures a chronic low-grade inflammation in children on elimination diets, opening important new opportunities for future prevention and treatment strategies.

Saccharomyces cerevisiae derived postbiotic alters gut microbiome metabolism in the human distal colon resulting in immunomodulatory potential in vitro

The yeast-based postbiotic EpiCor is a well-studied formulation, consisting of a complex mixture of bioactive molecules. In clinical studies, EpiCor postbiotic has been shown to reduce intestinal symptoms in a constipated population and support mucosal defense in healthy subjects. Anti-inflammatory potential and butyrogenic properties have been reported in vitro, suggesting a possible link between EpiCor's gut modulatory activity and immunomodulation. The current study used a standardized in vitro gut model, the Simulator of the Human Intestinal Microbial Ecosystem (SHIME®), to obtain a deeper understanding on host-microbiome interactions and potential microbiome modulation following repeated EpiCor administration. It was observed that EpiCor induced a functional shift in carbohydrate fermentation patterns in the proximal colon environment. Epicor promoted an increased abundance of Bifidobacterium in both the proximal and distal colon, affecting overall microbial community structure. Co-occurrence network analysis at the phylum level provided additional evidence of changes in the functional properties of microbial community promoted by EpiCor, increasing positive associations between Actinobacteria with microbes belonging to the Firmicutes phylum. These results, together with a significant increase in butyrate production provide additional support of EpiCor benefits to gut health. Investigation of host-microbiome interactions confirmed the immunomodulatory potential of the applied test product. Specific microbial alterations were observed in the distal colon, with metabotyping indicating that specific metabolic pathways, such as bile acid and tryptophan metabolism, were affected following EpiCor supplementation. These results, especially considering many effects were seen distally, further strengthen the position of EpiCor as a postbiotic with health promoting functionality in the gut, which could be further assessed in vivo.

A comprehensive metabolite fingerprint of fibrostenosis in patients with Crohn's disease

Intestinal fibrostenosis in patients with Crohn's disease (CD) is a common and untreatable comorbidity that is notoriously difficult to monitor. We aimed to find metabolites associated with the presence of fibrostenosis in patients with CD using targeted and untargeted metabolomics analyses of serum and primary cell cultures using hyphenated ultra-high performance liquid chromatography high-resolution mass spectrometry. Targeted metabolomics revealed 11 discriminating metabolites in serum, which were enriched within the arginine and proline metabolism pathway. Based on untargeted metabolomics and discriminant analysis, 166 components showed a high predictive value. In addition, human intestinal fibroblasts isolated from stenotic tissue were characterized by differential levels of medium-chain dicarboxylic acids, which are proposed as an energy source through beta-oxidation, when oxidative phosphorylation is insufficient. Another energy providing pathway in such situations is anaerobic glycolysis, a theory supported by increased expression of hexokinase 2 and solute carrier family 16 member 1 in stenotic fibroblasts. Of interest, four (unannotated) metabolic components showed a negative correlation with hexokinase 2 gene expression. Together, this study provides a discriminative metabolic fingerprint in the serum and in intestinal fibroblasts of stenotic and non-stenotic patients with CD suggestive for increased production of building blocks for collagen synthesis and increased glycolysis.

Microbiome and metabolome dynamics during radiotherapy for prostate cancer

BACKGROUND

Prostate cancer patients treated with radiotherapy are susceptible to acute gastrointestinal (GI) toxicity due to substantial overlap of the intestines with the radiation volume. Due to their intimate relationship with GI toxicity, faecal microbiome and metabolome dynamics during radiotherapy were investigated.

MATERIAL & METHODS

This prospective study included 50 prostate cancer patients treated with prostate (bed) only radiotherapy (PBRT) (n = 28) or whole pelvis radiotherapy (WPRT) (n = 22) (NCT04638049). Longitudinal sampling was performed prior to radiotherapy, after 10 fractions, near the end of radiotherapy and at follow-up. Patient symptoms were dichotomized into a single toxicity score. Microbiome and metabolome fingerprints were analyzed by 16S rRNA gene sequencing and ultra-high-performance liquid chromatography hybrid high-resolution mass spectrometry, respectively.

RESULTS

The individual α-diversity did not significantly change over time. Microbiota composition (β-diversity) changed significantly over treatment (PERMANOVA p-value = 0.03), but there was no significant difference in stability when comparing PBRT versus WPRT. Levels of various metabolites were significantly altered during radiotherapy. Baseline α-diversity was not associated with any toxicity outcome. Based on the metabolic fingerprint, no natural clustering according to toxicity profile could be achieved.

CONCLUSIONS

Radiation dose and treatment volume demonstrated limited effects on microbiome and metabolome fingerprints. In addition, no distinctive signature for toxicity status could be established. There is an ongoing need for toxicity risk stratification tools for diagnostic and therapeutic purposes, but the current evidence implies that the translation of metabolic and microbial biomarkers into routine clinical practice remains challenging.

Molecular systems biology approaches to investigate mechanisms of gut-brain communication in neurological diseases

BACKGROUND

Whilst the incidence of neurological diseases is increasing worldwide, treatment remains mostly limited to symptom management. The gut-brain axis, which encompasses the communication routes between microbiota, gut and brain, has emerged as a crucial area of investigation for identifying new preventive and therapeutic targets in neurological disease.

METHODS

Due to the inter-organ, systemic nature of the gut-brain axis, together with the multitude of biomolecules and microbial species involved, molecular systems biology approaches are required to accurately investigate the mechanisms of gut-brain communication. High-throughput omics profiling, together with computational methodologies such as dimensionality reduction or clustering, machine learning, network inference and genome-scale metabolic models, allows novel biomarkers to be discovered and elucidates mechanistic insights.

RESULTS

In this review, the general concepts of experimental and computational methodologies for gut-brain axis research are introduced and their applications are discussed, mainly in human cohorts. Important aspects are further highlighted concerning rational study design, sampling procedures and data modalities relevant for gut-brain communication, strengths and limitations of methodological approaches and some future perspectives.

CONCLUSION

Multi-omics analyses, together with advanced data mining, are essential to functionally characterize the gut-brain axis and put forward novel preventive or therapeutic strategies in neurological disease.

Exploration and optimization of extraction, analysis and data normalization strategies for mass spectrometry-based DNA adductome mapping and modeling

Although interest in characterizing DNA damage by means of DNA adductomics has substantially grown, the field of DNA adductomics is still in its infancy, with room for optimization of methods for sample analysis, data processing and DNA adduct identification. In this context, the first objective of this study was to evaluate the use of hydrophilic interaction (HILIC) vs. reversed phase liquid chromatography (RPLC) coupled to high resolution mass spectrometry (HRMS) and thermal acidic vs. enzymatic hydrolysis of DNA followed by DNA adduct purification and enrichment using solid-phase extraction (SPE) or fraction collection for DNA adductome mapping. The second objective was to assess the use of total ion count (TIC) and median intensity (MedI) normalization compared to QC (quality control), iQC (internal QC) and quality control-based robust locally estimated scatterplot smoothing (LOESS) signal correction (QC-RLSC) normalization for processing of the acquired data. The results demonstrate that HILIC compared to RPLC allowed better modeling of the tentative DNA adductome, particularly in combination with thermal acidic hydrolysis and SPE (more valid models, with an average Q²(Y) and R²(Y) of 0.930 and 0.998, respectively). Regarding the need for data normalization and the management of (limited) system instability and signal drift, QC normalization outperformed TIC, MedI, iQC and LOESS normalization. As such, QC normalization can be put forward as the default data normalization strategy. In case of momentous signal drift and/or batch effects however, comparison to other normalization strategies (like e.g. LOESS) is recommended. In future work, further optimization of DNA adductomics may be achieved by merging of HILIC and RPLC datasets and/or application of 2D-LC, as well as the inclusion of Schiff base stabilization and/or fraction collection in the thermal acidic hydrolysis-SPE sample preparation workflow.

Biological differences underlying sex and gender disparities in bladder cancer: current synopsis and future directions

Sex and gender disparities in bladder cancer have long been a subject of interest to the cancer research community, wherein men have a 4 times higher incidence rate than women, and female patients often present with higher-grade disease and experience worse outcomes. Despite the known differences in disease incidence and clinical outcomes between male and female bladder cancer patients, clinical management remains the same. In this review, we critically analyze studies that report on the biological differences between men and women and evaluate how these differences contribute to sex and gender disparities in bladder cancer. Distinct characteristics of the male and female immune systems, differences in circulating hormone levels and hormone receptor expression, and different genetic and epigenetic alterations are major biological factors that all likely contribute to disparate incidence rates and outcomes for male and female bladder cancer patients. Future preclinical and clinical studies in this area should employ experimental approaches that account for and consider sex and gender disparities in bladder cancer, thereby facilitating the development of precision medicine for the effective treatment of bladder cancer in all patients.

Point-of-care applicable metabotyping using biofluid-specific electrospun MetaSAMPs directly amenable to ambient LA-REIMS

In recent years, ambient ionization mass spectrometry (AIMS) including laser ablation rapid evaporation IMS, has enabled direct biofluid metabolome analysis. AIMS procedures are, however, still hampered by both analytical, i.e., matrix effects, and practical, i.e., sample transport stability, drawbacks that impede metabolome coverage. In this study, we aimed at developing biofluid-specific metabolome sampling membranes (MetaSAMPs) that offer a directly applicable and stabilizing substrate for AIMS. Customized rectal, salivary, and urinary MetaSAMPs consisting of electrospun (nano)fibrous membranes of blended hydrophilic (polyvinylpyrrolidone and polyacrylonitrile) and lipophilic (polystyrene) polymers supported metabolite absorption, adsorption, and desorption. Moreover, MetaSAMP demonstrated superior metabolome coverage and transport stability compared to crude biofluid analysis and was successfully validated in two pediatric cohorts (MetaBEAse, n = 234 and OPERA, n = 101). By integrating anthropometric and (patho)physiological with MetaSAMP-AIMS metabolome data, we obtained substantial weight-driven predictions and clinical correlations. In conclusion, MetaSAMP holds great clinical application potential for on-the-spot metabolic health stratification.

Dual UHPLC-HRMS Metabolomics and Lipidomics and Automated Data Processing Workflow for Comprehensive High-Throughput Gut Phenotyping

In recent years, feces has surfaced as the matrix of choice for investigating the gut microbiome-health axis because of its non-invasive sampling and the unique reflection it offers of an individual's lifestyle. In cohort studies where the number of samples required is large, but availability is scarce, a clear need exists for high-throughput analyses. Such analyses should combine a wide physicochemical range of molecules with a minimal amount of sample and resources and downstream data processing workflows that are as automated and time efficient as possible. We present a dual fecal extraction and ultra high performance liquid chromatography-high resolution-quadrupole-orbitrap-mass spectrometry (UHPLC-HR-Q-Orbitrap-MS)-based workflow that enables widely targeted and untargeted metabolome and lipidome analysis. A total of 836 in-house standards were analyzed, of which 360 metabolites and 132 lipids were consequently detected in feces. Their targeted profiling was validated successfully with respect to repeatability (78% CV < 20%), reproducibility (82% CV < 20%), and linearity (81% R² > 0.9), while also enabling holistic untargeted fingerprinting (15,319 features, CV < 30%). To automate targeted processing, we optimized an R-based targeted peak extraction (TaPEx) algorithm relying on a database comprising retention time and mass-to-charge ratio (360 metabolites and 132 lipids), with batch-specific quality control curation. The latter was benchmarked toward vendor-specific targeted and untargeted software and our isotopologue parameter optimization/XCMS-based untargeted pipeline in LifeLines Deep cohort samples (n = 97). TaPEx clearly outperformed the untargeted approaches (81.3 vs 56.7-66.0% compounds detected). Finally, our novel dual fecal metabolomics-lipidomics-TaPEx method was successfully applied to Flemish Gut Flora Project cohort (n = 292) samples, leading to a sample-to-result time reduction of 60%.

Metabolomic Analysis of Multiple Biological Specimens (Feces, Serum, and Urine) by 1H-NMR Spectroscopy from Dairy Cows with Clinical Mastitis

Due to huge economic losses to the dairy industry worldwide, mastitis can be considered as one of the most common diseases in dairy cows. This work aimed to study this disease by comparing multiple biological specimens (feces, serum, and urine) from individuals with or without clinical mastitis. This was performed by a single analytical platform, namely ¹H-NMR, through a multi-matrix strategy. Thanks to the high reproducibility of ¹H-NMR, we could characterize 120 molecules across dairy cow feces, serum, and urine. Among them, 23 molecules were in common across the three biofluids. By integrating the results of multi-matrix metabolomics, several pathways pertaining to energy metabolism and amino acid metabolism appeared to be affected by clinical mastitis. The present work wished to deepen the understanding of dairy cow mastitis in its clinical form. Simultaneous analysis of metabolome changes across several key biofluids could facilitate knowledge discovery and the reliable identification of potential biomarkers, which could be, in turn, used to shed light on the early diagnosis of dairy cow mastitis in its subclinical form.

Comprehensive metabolomics reveals correlation between sophorolipid biosynthesis and autophagy

Sophorolipids are biobased and biodegradable glycolipid surface-active agents contributing to the shift from petroleum to biobased surfactants, associated with clear environmental benefits. However, their production cost is currently too high to allow commercialisation. Therefore, a continuous sophorolipid production process was evaluated, i.e., a retentostat with an external filtration unit. Despite an initial increase in volumetric productivity, productivity eventually declined to almost 0 g L^-1 h^-1. Following comprehensive metabolomics on supernatant obtained from a standardised retentostat, we hypothesised exhaustion of the N-starvation-induced autophagy as the main mechanism responsible for the decline in bolaform sophorolipid productivity. Thirty-six metabolites that correlate with RNA/protein autophagy and high sophorolipid productivity were putatively identified. In conclusion, our results unveil a plausible cause of this bola sophorolipid productivity decline in an industrially relevant bioreactor set-up, which may thus impact majorly on future yeast biosurfactant regulation studies and the finetuning of bola sophorolipid production processes.

HILIC-MS for Untargeted Profiling of the Free Glycation Product Diversity

Glycation products produced by the non-enzymatic reaction between reducing carbohydrates and amino compounds have received increasing attention in both food- and health-related research. Although liquid chromatography mass spectrometry (LC-MS) methods for analyzing glycation products already exist, only a few common advanced glycation end products (AGEs) are usually covered by quantitative methods. Untargeted methods for comprehensively analyzing glycation products are still lacking. The aim of this study was to establish a method for simultaneously characterizing a wide range of free glycation products using the untargeted metabolomics approach. In this study, Maillard model systems consisting of a multitude of heterogeneous free glycation products were chosen for systematic method optimization, rather than using a limited number of standard compounds. Three types of hydrophilic interaction liquid chromatography (HILIC) columns (zwitterionic, bare silica, and amide) were tested due to their good retention for polar compounds. The zwitterionic columns showed better performance than the other two types of columns in terms of the detected feature numbers and detected free glycation products. Two zwitterionic columns were selected for further mobile phase optimization. For both columns, the neutral mobile phase provided better peak separation, whereas the acidic condition provided a higher quality of chromatographic peak shapes. The ZIC-cHILIC column operating under acidic conditions offered the best potential to discover glycation products in terms of providing good peak shapes and maintaining comparable compound coverage. Finally, the optimized HILIC-MS method can detect 70% of free glycation product features despite interference from the complex endogenous metabolites from biological matrices, which showed great application potential for glycation research and can help discover new biologically important glycation products.

Imputation of Missing Values for Multi-Biospecimen Metabolomics Studies: Bias and Effects on Statistical Validity

The analysis of high-throughput metabolomics mass spectrometry data across multiple biological sample types (biospecimens) poses challenges due to missing data. During differential abundance analysis, dropping samples with missing values can lead to severe loss of data as well as biased results in group comparisons and effect size estimates. However, the imputation of missing data (the process of replacing missing data with estimated values such as a mean) may compromise the inherent intra-subject correlation of a metabolite across multiple biospecimens from the same subject, which in turn may compromise the efficacy of the statistical analysis of differential metabolites in biomarker discovery. We investigated imputation strategies when considering multiple biospecimens from the same subject. We compared a novel, but simple, approach that consists of combining the two biospecimen data matrices (rows and columns of subjects and metabolites) and imputes the two biospecimen data matrices together to an approach that imputes each biospecimen data matrix separately. We then compared the bias in the estimation of the intra-subject multi-specimen correlation and its effects on the validity of statistical significance tests between two approaches. The combined approach to multi-biospecimen studies has not been evaluated previously even though it is intuitive and easy to implement. We examine these two approaches for five imputation methods: random forest, k nearest neighbor, expectation-maximization with bootstrap, quantile regression, and half the minimum observed value. Combining the biospecimen data matrices for imputation did not greatly increase efficacy in conserving the correlation structure or improving accuracy in the statistical conclusions for most of the methods examined. Random forest tended to outperform the other methods in all performance metrics, except specificity.

Increased inosine levels in drug-free individuals with at-risk mental state: A serum metabolomics study

AIM

At-risk mental state (ARMS) has been recently attracting attention with respect to the improvement of the management and outcome of psychiatric diseases, such as schizophrenia. Since only a few studies have reported on biological alterations in ARMS, serum metabolomics was carried out in ARMS subjects and healthy controls using liquid chromatography with high-resolution mass spectrometry.

METHODS

Serum samples were collected from ARMS subjects (n = 24; male: 12; female 12) and age- and sex-matched healthy controls (n = 23 male: 11, female: 12). After serum pre-treatment, liquid chromatography with high-resolution mass spectrometry was performed. Multivariate analyses, such as orthogonal partial least-squares discriminant and volcano plot analyses, were performed.

RESULTS

Serum inosine, lactate, taurine, 2,3-dihydroxypropanoate and glutamate levels differed between the two groups. A significant increase in inosine levels was detected in the positive- and negative-ion modes; however, significant differences were not observed in the levels of other purine-related metabolites (hypoxanthine, xanthine and urate) between the two groups.

CONCLUSION

Increased inosine levels may serve as biological markers for ARMS, in addition to alterations in the levels of lactate and certain amino acids.

Differences in Metabolic Profiles of Healthy Dogs Fed a High-Fat vs. a High-Starch Diet

Obesity is a common problem in dogs and overconsumption of energy-rich foods is a key factor. This study compared the inflammatory response and fecal metabolome of dogs fed a high-fat vs. a high-starch diet. Ten healthy lean adult beagles were equally allocated into two groups in a cross-over design. Each group received two diets in which fat (horse fat) and starch (pregelatinized corn starch) were exchanged in an isocaloric way to compare high fat vs. high starch. There was a tendency to increase the glucose and glycine concentrations and the glucose/insulin ratio in the blood in dogs fed with the high-fat diet, whereas there was a decrease in the level of Non-esterified fatty acids and a tendency to decrease the alanine level in dogs fed with the high-starch diet. Untargeted analysis of the fecal metabolome revealed 10 annotated metabolites of interest, including L-methionine, which showed a higher abundance in dogs fed the high-starch diet. Five other metabolites were upregulated in dogs fed the high-fat diet, but could not be annotated. The obtained results indicate that a high-starch diet, compared to a high-fat diet, may promote lipid metabolism, anti-oxidative effects, protein biosynthesis and catabolism, mucosal barrier function, and immunomodulation in healthy lean dogs.

A multi-omics study to boost continuous bolaform sophorolipid production

Biodegradable and biobased surface active agents are renewable and environmentally friendly alternatives to petroleum derived or oleochemical surfactants. However, they are accompanied by relatively high production costs. In this study, the aim was to reduce the production costs for an innovative type of microbial biosurfactant: bolaform sophorolipids, produced by the yeast Starmerella bombicola ΔsbleΔat. A novel continuous retentostat set-up was performed whereby continuous broth microfiltration retained the biomass in the bioreactor while performing an in situ product separation of bolaform sophorolipids. Although a mean volumetric productivity of 0.56 g L^-1 h^-1 was achieved, it was not possible to maintain this productivity, which collapsed to almost 0 g L^-1 h^-1. Therefore, two process adaptations were evaluated, a sequential batch strategy and a phosphate limitation alleviation strategy. The sequential batch set-up restored the mean volumetric productivity to 0.66 g L^-1 h^-1 for an additional 132 h but was again followed by a productivity decline. A similar result was obtained with the phosphate limitation alleviation strategy where a mean volumetric productivity of 0.54 g L^-1 h^-1 was reached, but a productivity decline was also observed. Whole genome variant analysis uncovered no evidence for genomic variations for up to 1306 h of retentostat cultivation. Untargeted metabolomics analysis identified 8-hydroxyguanosine, a biomarker for oxidative RNA damage, as a key metabolite correlating with high bolaform sophorolipid productivity. This study showcases the application of a retentostat to increase bolaform sophorolipid productivity and lays the basis of a multi-omics platform for in depth investigation of microbial biosurfactant production with S. bombicola.

FLEXiGUT: Rationale for exposomics associations with chronic low-grade gut inflammation

FLEXiGUT is the first large-scale exposomics study focused on chronic low-grade inflammation. It aims to characterize human life course environmental exposure to assess and validate its impact on gut inflammation and related biological processes and diseases. The cumulative influences of environmental and food contaminants throughout the lifespan on certain biological responses related to chronic gut inflammation will be investigated in two Flemish prospective cohorts, namely the "ENVIRONAGE birth cohort", which provides follow-up from gestation to early childhood, and the "Flemish Gut Flora Project longitudinal cohort", a cohort of adults. The exposome will be characterised through biomonitoring of legacy and emerging contaminants, mycotoxins and markers of air pollution, by analysing the available metadata on nutrition, location and activity, and by applying state-of-the-art -omics techniques, including metagenomics, metabolomics and DNA adductomics, as well as the assessment of telomere length and measurement of inflammatory markers, to encompass both exposure and effect. Associations between exposures and health outcomes will be uncovered using an integrated -omics data analysis framework comprising data exploration, pre-processing, dimensionality reduction and data mining, combined with machine learning-based pathway analysis approaches. This is expected to lead to a more profound insight in mechanisms underlying disease progression (e.g. metabolic disorders, food allergies, gastrointestinal cancers) and/or accelerated biological ageing.

Paediatric obesity: a systematic review and pathway mapping of metabolic alterations underlying early disease processes

BACKGROUND

The alarming trend of paediatric obesity deserves our greatest awareness to hinder the early onset of metabolic complications impacting growth and functionality. Presently, insight into molecular mechanisms of childhood obesity and associated metabolic comorbidities is limited. This systematic review aimed at scrutinising what has been reported on putative metabolites distinctive for metabolic abnormalities manifesting at young age by searching three literature databases (Web of Science, Pubmed and EMBASE) during the last 6 years (January 2015-January 2021). Global metabolomic profiling of paediatric obesity was performed (multiple biological matrices: blood, urine, saliva and adipose tissue) to enable overarching pathway analysis and network mapping. Among 2792 screened Q1 articles, 40 met the eligibility criteria and were included to build a database on metabolite markers involved in the spectrum of childhood obesity. Differential alterations in multiple pathways linked to lipid, carbohydrate and amino acid metabolisms were observed. High levels of lactate, pyruvate, alanine and acetate marked a pronounced shift towards hypoxic conditions in children with obesity, and, together with distinct alterations in lipid metabolism, pointed towards dysbiosis and immunometabolism occurring early in life. Additionally, aberrant levels of several amino acids, most notably belonging to tryptophan metabolism including the kynurenine pathway and its relation to histidine, phenylalanine and purine metabolism were displayed. Moreover, branched-chain amino acids were linked to lipid, carbohydrate, amino acid and microbial metabolism, inferring a key role in obesity-associated insulin resistance.

CONCLUSIONS

This systematic review revealed that the main metabolites at the crossroad of dysregulated metabolic pathways underlying childhood obesity could be tracked down to one central disturbance, i.e. impending insulin resistance for which reference values and standardised measures still are lacking. In essence, glycolytic metabolism was evinced as driving energy source, coupled to impaired Krebs cycle flux and ß-oxidation. Applying metabolomics enabled to retrieve distinct metabolite alterations in childhood obesity(-related insulin resistance) and associated pathways at early age and thus could provide a timely indication of risk by elucidating early-stage biomarkers as hallmarks of future metabolically unhealthy phenotypes.

A Systematic Review of Metabolic Alterations Underlying IgE-Mediated Food Allergy in Children

SCOPE

Immunoglobulin E-mediated food allergies (IgE-FA) are characterized by an ever-increasing prevalence, currently reaching up to 10.4% of children in the European Union. Metabolomics has the potential to provide a deeper understanding of the pathogenic mechanisms behind IgE-FA.

METHODS AND RESULTS

In this work, literature is systematically searched using Web of Science, PubMed, Scopus, and Embase, from January 2010 until May 2021, including human and animal metabolomic studies on multiple biofluids (urine, blood, feces). In total, 15 studies on IgE-FA are retained and a dataset of 277 potential biomarkers is compiled for in-depth pathway mapping. Decreased indoleamine 2,3-dioxygenase-1 (IDO- 1) activity is hypothesized due to altered plasma levels of tryptophan and its metabolites in IgE-FA children. In feces of children prior to IgE-FA, aberrant metabolization of sphingolipids and histidine is noted. Decreased fecal levels of (branched) short chain fatty acids ((B)SCFAs) compel a shift towards aerobic glycolysis and suggest dysbiosis, associated with an immune system shift towards T-helper 2 (Th2) responses. During animal anaphylaxis, a similar switch towards glycolysis is observed, combined with increased ketogenic pathways. Additionally, altered histidine, purine, pyrimidine, and lipid pathways are observed.

CONCLUSION

To conclude, this work confirms the unprecedented opportunities of metabolomics and supports the in-depth pathophysiological qualification in the quest towards improved diagnostic and prognostic biomarkers for IgE-FA.

Development and validation of a liquid chromatography high-resolution mass spectrometry orbitrap method for the sensitive quantification of amoxicillin, piperacillin, tazobactam and meropenem in human faeces

Beta-lactam antibiotics are of vital importance for the treatment of infections in a broad range of patients. Although most systemically administered antibiotics will be excreted renally, a fraction will reach the gastro-intestinal tract, affecting the intestinal microbiome by eradicating a wide range of bacterial species while facilitating the growth of antimicrobial-resistant species. A better understanding of the kinetics of beta-lactam antibiotics in the gastro-intestinal tract is essential to study their role in the development of antibiotic resistance in bacteria and to help develop future therapies to prevent damage to, or restore, the intestinal microbiome. Analysis of beta-lactam antibiotics in faeces is particularly challenging due to the heterogeneous nature of the matrix, rapid degradation of some beta-lactam antibiotics in faeces and very strong ion suppression when using mass spectrometry. Sample preparation was optimized using a sequential strategy of experimental designs. It resulted in lyophilization, a MOPS buffer system and the addition of the beta-lactamase inhibitor avibactam to minimize degradation of antibiotics allowing sensitive quantification. The developed liquid chromatography method with high-resolution mass spectrometric detection was successfully validated according to bioanalytical EMA guidelines and had a linear range of 1-200 μg g^-1 lyophilized faeces for amoxicillin, piperacillin and meropenem; and 0.5-100 μg g^-1 lyophilized faeces for tazobactam. Despite the highly complex and heterogeneous composition of faeces, the accuracy (0.1-15%) and precision (1.7-12.1%) were in line with those obtained for quantification methods of beta-lactam antibiotics in plasma, the golden standard matrix for therapeutic drug monitoring. The applicability of the method was illustrated by successful quantification of piperacillin and tazobactam in faeces from an intensive care unit patient receiving piperacillin/tazobactam in a continuous intravenous infusion. Both piperacillin and tazobactam were still present six days after discontinuation of the therapy.

Triangulation of microbial fingerprinting in anaerobic digestion reveals consistent fingerprinting profiles

The anaerobic digestion microbiome has been puzzling us since the dawn of molecular methods for mixed microbial community analysis. Monitoring of the anaerobic digestion microbiome can either take place via a non-targeted holistic evaluation of the microbial community through fingerprinting or by targeted monitoring of selected taxa. Here, we compared four different microbial community fingerprinting methods, i.e., amplicon sequencing, metaproteomics, metabolomics and cytomics, in their ability to characterise the full-scale anaerobic digestion microbiome. Cytometric fingerprinting through cytomics reflects a, for anaerobic digestion, novel, single cell-based approach of direct microbial community fingerprinting by flow cytometry. Three different digester types, i.e., sludge digesters, digesters treating agro-industrial waste and dry anaerobic digesters, each reflected different operational parameters. The α-diversity analysis yielded inconsistent results, especially for richness, across the different methods. In contrast, β-diversity analysis resulted in comparable profiles, even when translated into phyla or functions, with clear separation of the three digester types. In-depth analysis of each method's features i.e., operational taxonomic units, metaproteins, metabolites, and cytometric traits, yielded certain similar features, yet, also some clear differences between the different methods, which was related to the complexity of the anaerobic digestion process. In conclusion, cytometric fingerprinting through flow cytometry is a reliable, fast method for holistic monitoring of the anaerobic digestion microbiome, and the complementary identification of key features through other methods could give rise to a direct interpretation of anaerobic digestion process performance.

Comprehensive polar metabolomics and lipidomics profiling discriminates the transformed from the non-transformed state in colon tissue and cell lines

Colorectal cancer (CRC) is the fourth most lethal disease worldwide. Despite an urgent need for therapeutic advance, selective target identification in a preclinical phase is hampered by molecular and metabolic variations between cellular models. To foster optimal model selection from a translational perspective, we performed untargeted ultra-high performance liquid chromatography coupled to high-resolution mass spectrometry-based polar metabolomics and lipidomics to non-transformed (CCD841-CON and FHC) and transformed (HCT116, HT29, Caco2, SW480 and SW948) colon cell lines as well as tissue samples from ten colorectal cancer patients. This unveiled metabolic signatures discriminating the transformed from the non-transformed state. Metabolites involved in glutaminolysis, tryptophan catabolism, pyrimidine, lipid and carnitine synthesis were elevated in transformed cells and cancerous tissue, whereas those involved in the glycerol-3-phosphate shuttle, urea cycle and redox reactions were lowered. The degree of glutaminolysis and lipid synthesis was specific to the colon cancer cell line at hand. Thus, our study exposed pathways that are specifically associated with the transformation state and revealed differences between colon cancer cell lines that should be considered when targeting cancer-associated pathways.

Disparities in the gut metabolome of post-operative Hirschsprung's disease patients

Hirschsprung's disease (HD) is a congenital structural abnormality of the colon seen in approximately 1 to 5000 live births. Despite surgical correction shortly after presentation, up to 60% of patients will express long-term gastrointestinal complaints, including potentially life-threatening Hirschsprung-associated enterocolitis (HAEC). In this study fecal samples from postoperative HD patients (n = 38) and their healthy siblings (n = 21) were analysed using high-resolution liquid chromatography-mass spectrometry aiming to further unravel the nature of the chronic gastrointestinal disturbances. Furthermore, within the patient group, we compared the faecal metabolome between patients with and without a history of HAEC as well as those diagnosed with short or long aganglionic segment. Targeted analysis identified several individual metabolites characteristic for all HD patients as well as those with a history of HAEC and long segment HD. Moreover, multivariate models based on untargeted data established statistically significant (p < 0.05) differences in comprehensive faecal metabolome in the patients' cohort as a whole and in patients with a history of HAEC. Pathway analysis revealed the most impact on amino sugar, lysine, sialic acid, hyaluronan and heparan sulphate metabolism in HD, as well as impaired tyrosine metabolism in HAEC group. Those changes imply disruption of intestinal mucosal barrier due to glycosaminoglycan breakdown and dysbiosis as major metabolic changes in patients' group and should be further explored for potential diagnostic or treatment targets.

Rapid ex vivo molecular fingerprinting of biofluids using laser-assisted rapid evaporative ionization mass spectrometry

Of the many metabolites involved in any clinical condition, only a narrow range of biomarkers is currently being used in the clinical setting. A key to personalized medicine would be to extend this range. Metabolic fingerprinting provides a more comprehensive insight, but many methods used for metabolomics analysis are too complex and time-consuming to be diagnostically useful. Here, a rapid evaporative ionization mass spectrometry (REIMS) system for direct ex vivo real-time analysis of biofluids with minor sample pretreatment is detailed. The REIMS can be linked to various laser wavelength systems (such as optical parametric oscillator or CO₂ laser) and with automation for high-throughput analysis. Laser-induced sample evaporation occurs within seconds through radiative heating with the plume guided to the MS instrument. The presented procedure includes (i) laser setup with automation, (ii) analysis of biofluids (blood/urine/stool/saliva/sputum/breast milk) and (iii) data analysis. We provide the optimal settings for biofluid analysis and quality control, enabling sensitive, precise and robust analysis. Using the automated setup, 96 samples can be analyzed in ~35-40 min per ionization mode, with no intervention required. Metabolic fingerprints are made up of 2,000-4,000 features, for which relative quantification can be achieved at high repeatability when total ion current normalization is applied. With saliva and feces as example matrices, >70% of features had a coefficient of variance ≤30%. However, to achieve acceptable long-term reproducibility, additional normalizations by, e.g., LOESS are recommended, especially for positive ionization.

Maternal Rat Metabolomics: Amniotic Fluid and Placental Metabolic Profiling Workflows

Studying the metabolome of specific gestational compartments is of growing interest in the context of fetus developmental disorders. However, the metabolomes of the placenta and amniotic fluid (AF) are poorly characterized. Therefore, we present the validation of a fingerprinting methodology. Using pregnant rats, we performed exhaustive and robust extractions of metabolites in the AF and lipids and more polar metabolites in the placenta. For the AF, we compared the extraction capabilities of methanol (MeOH), acetonitrile (ACN), and a mixture of both. For the placenta, we compared (i) the extraction capabilities of dichloromethane, methyl t-butyl ether (MTBE), and butanol, along with (ii) the impact of lyophilization of the placental tissue. Analyses were performed on a C18 and hydrophilic interaction liquid chromatography combined with high-resolution mass spectrometry. The efficiency and the robustness of the extractions were compared based on the number of the features or metabolites (for untargeted or targeted approach, respectively), their mean total intensity, and their coefficient of variation (% CV). The extraction capabilities of MeOH and ACN on the AF metabolome were equivalent. Lyophilization also had no significant impact and usefulness on the placental tissue metabolome profiling. Considering the placental lipidome, MTBE extraction was more informative because it allowed extraction of a slightly higher number of lipids, in higher concentration. This proof-of-concept study assessing the metabolomics and lipidomics of the AF and the placenta revealed changes in both metabolisms, at two different stages of rat gestation, and allowed a detailed prenatal metabolic fingerprinting.

Oral anserine supplementation does not attenuate type-2 diabetes or diabetic nephropathy in BTBR ob/ob mice

Carnosine, a naturally occurring dipeptide present in an omnivorous diet, has been shown to ameliorate the development of metabolic syndrome, type-2 diabetes (T2D) and early- and advanced-stage diabetic nephropathy in different rodent models. Anserine, its methylated analogue, is more bio-available in humans upon supplementation without affecting its functionality. In this work, we investigated the effect of oral supplementation with anserine or carnosine on circulating and tissue anserine and carnosine levels and on the development of T2D and diabetic nephropathy in BTBR ob/ob mice. BTBR ob/ob mice were either supplemented with carnosine or anserine in drinking water (4 mM) for 18 weeks and compared with non-supplemented BTBR ob/ob and wild-type (WT) mice. Circulating and kidney, but not muscle, carnosine, and anserine levels were enhanced by supplementation with the respective dipeptides in ob/ob mice compared to non-treated ob/ob mice. The evolution of fasting blood glucose, insulin, fructosamine, triglycerides, and cholesterol was not affected by the supplementation regimens. The albumin/creatine ratio, glomerular hypertrophy, and mesangial matrix expansion were aggravated in ob/ob vs. WT mice, but not alleviated by supplementation. To conclude, long-term supplementation with anserine elevates circulating and kidney anserine levels in diabetic mice. However, anserine supplementation was not able to attenuate the development of T2D or diabetic nephropathy in BTBR ob/ob mice. Further research will have to elucidate whether anserine can attenuate milder forms of T2D or metabolic syndrome.

Optimization of Sample Preparation for Metabolomics Exploration of Urine, Feces, Blood and Saliva in Humans Using Combined NMR and UHPLC-HRMS Platforms

Currently, most clinical studies in metabolomics only consider a single type of sample such as urine, plasma, or feces and use a single analytical platform, either NMR or MS. Although some studies have already investigated metabolomics data from multiple fluids, the information is limited to a unique analytical platform. On the other hand, clinical studies investigating the human metabolome that combine multi-analytical platforms have focused on a single biofluid. Combining data from multiple sample types for one patient using a multimodal analytical approach (NMR and MS) should extend the metabolome coverage. Pre-analytical and analytical phases are time consuming. These steps need to be improved in order to move into clinical studies that deal with a large number of patient samples. Our study describes a standard operating procedure for biological specimens (urine, blood, saliva, and feces) using multiple platforms (¹H-NMR, RP-UHPLC-MS, and HILIC-UHPLC-MS). Each sample type follows a unique sample preparation procedure for analysis on a multi-platform basis. Our method was evaluated for its robustness and was able to generate a representative metabolic map.

Influence of Age, Sex, and Diet on the Human Fecal Metabolome Investigated by 1H NMR Spectroscopy

The human fecal metabolome is increasingly studied to explore the impact of diet and lifestyle on health and the gut microbiome. However, systematic differences and confounding factors related to age, sex, and diet remain largely unknown. In this study, absolute concentrations of fecal metabolites from 205 healthy Danes (105 males and 100 females, 49 ± 31 years old) were quantified using ¹H NMR spectroscopy and the newly developed SigMa software. The largest systemic variation was found to be highly related to age. Fecal concentrations of short-chain fatty acids (SCFA) were higher in the 18 years old group, while amino acids (AA) were higher in the elderly. Sex-related metabolic differences were weak but significant and mainly related to changes in SCFA. The concentrations of butyric, valeric, propionic, and isovaleric acids were found to be higher in males compared to females. Sex differences were associated with a stronger, possibly masking, effect from differential intake of macronutrients. Dietary fat intake decreased levels of SCFA and AA of both sexes, while carbohydrate intake showed weak correlations with valeric and isovaleric acids in females. This study highlights some possible demographic confounders linked to diet, disease, lifestyle, and microbiota that have to be taken into account when analyzing fecal metabolome data.

Indolic Structure Metabolites as Potential Biomarkers of Non-infectious Diseases

Interest in indolic structure metabolites, including a number of products of microbial biotransformation of the aromatic amino acid tryptophan, is increasingly growing. The review prepared by a team of authors is based on in-depthscrutiny of data available in PubMed, Scopus, Cyberleninka, Clinical Trials, and Cochrane Library, eventually narrowing the search to a set of keywords such as tryptophan metabolites; plasma metabolomics profiling; metabolomics fingerprinting; gas-, liquid chromatography mass spectrometry; serotonin; melatonin; tryptamine; indoxyl sulfate; indole-3-acetic acid; indole-3-propionic acid; 5-hydroxyindole-3-acetic acid; gut microbiota and microbial metabolites. It provides a summary that outlines the pattern of changes in the level of indolic structure metabolites in a number of diseases and deals with the data from the field of human microbiota metabolites. In modern experimental studies, including the use of gnotobiological (germ-free) animals, it has been convincingly proved that the formation of tryptophan metabolites such as indole-3-acetic acid, indole-3-propionic acid, tryptamine, and indoxyl sulfate is associated with gut bacteria. Attention to some concentration changes of indolic compounds is due to the fact that pronounced deviations and a significant decrease of these metabolites in the blood were found in a number of serious cardiovascular, brain or gastrointestinal diseases. The literature-based analysis allowed the authors to conclude that a constant (normal) level of the main metabolites of the indolic structure in the human body is maintained by a few strict anaerobic bacteria from the gut of a healthy body belonging to the species of Clostridium, Bacteroides, Peptostreptococcus, Eubacteria, etc. The authors focus on several metabolites of the indolic structure that can be called clinically significant in certain diseases, such as schizophrenia, depression, atherosclerosis, colorectal cancer, etc. Determining the level of indole metabolites in the blood can be used to diagnose and monitor the effectiveness of a comprehensive treatment approach.

The Bee Hemolymph Metabolome: A Window into the Impact of Viruses on Bumble Bees

State-of-the-art virus detection technology has advanced a lot, yet technology to evaluate the impacts of viruses on bee physiology and health is basically lacking. However, such technology is sorely needed to understand how multi-host viruses can impact the composition of the bee community. Here, we evaluated the potential of hemolymph metabolites as biomarkers to identify the viral infection status in bees. A metabolomics strategy based on ultra-high-performance liquid chromatography coupled to high-resolution mass spectrometry was implemented. First, we constructed a predictive model for standardized bumble bees, in which non-infected bees were metabolically differentiated from an overt Israeli acute paralysis virus (IAPV) infection (R²Y = 0.993; Q² = 0.906), as well as a covert slow bee paralysis virus (SBPV) infection (R²Y = 0.999; Q² = 0.875). Second, two sets of potential biomarkers were identified, being descriptors for the metabolomic changes in the bee's hemolymph following viral infection. Third, the biomarker sets were evaluated in a new dataset only containing wild bees and successfully discriminated virus infection versus non-virus infection with an AUC of 0.985. We concluded that screening hemolymph metabolite markers can underpin physiological changes linked to virus infection dynamics, opening promising avenues to identify, monitor, and predict the effects of virus infection in a bee community within a specific environment.

Untargeted Metabolomics Reveals Elevated L-Carnitine Metabolism in Pig and Rat Colon Tissue Following Red Versus White Meat Intake

SCOPE

The consumption of red and processed meat, and not white meat, associates with the development of various Western diseases such as colorectal cancer and type 2 diabetes. This work aims at unraveling novel meat-associated mechanisms that are involved in disease development.

METHODS AND RESULTS

A non-hypothesis driven strategy of untargeted metabolomics is applied to assess colon tissue from rats (fed a high dose of beef vs. white meat) and from pigs (fed red/processed meat vs. white meat), receiving a realistic human background diet. An increased carnitine metabolism is observed, which is reflected by higher levels of acylcarnitines and 3-dehydroxycarnitine (rats and pigs) and trimethylamine-N-oxide (rats). While 3-dehydroxycarnitine is higher in HT29 cells, incubated with colonic beef digests, acylcarnitine levels are reduced. This suggests an altered response from colon cancer cell line towards meat-induced oxidative stress. Moreover, metabolic differences between rat and pigs are observed in N-glycolylneuraminic acid incorporation, prostaglandin, and fatty acid synthesis.

CONCLUSION

This study demonstrates elevated (acyl)carnitine metabolism in colon tissue of animals that follow a red meat-based diet, providing mechanistic insights that may aid in explaining the nutritional-physiological correlation between red/processed meat and Western diseases.

A rapid multiclass method for antibiotic residues in goat dairy products by UPLC-quadrupole/electrostatic field orbitrap high-resolution mass spectrometry

Background

Sulfanilamides, quinolones, nitroimidazoles, tetracyclines, cephalosporins, macrolides, and β-lactam are common tools in agriculture and can be found in animal-based foods such as goat milk and goat dried milk. To evaluate the risk of these species, reliable analytical methods are needed for accurate concentration determination, especially in goat milk and goat dried milk.

Method

We describe a method based on PRiME extraction coupled with UPLC-quadrupole/electrostatic field orbitrap high-resolution mass spectrometry to accomplish this task.

Result

Under optimal conditions, the limit of quantification for all antibiotics was 0.5–100 μg/L in goat milk and goat dried milk samples. The recoveries were 60.6–110.0% for goat milk and 60.1–109.6% for goat dried milk with a coefficient of variation less than 15%. The detection limits were 0.5–1.0 μg/kg. The limits of quantification for the analytes were 5.0–10.0 μg/kg. Finally, the method was used to screen veterinary antibiotics in 50 local goat milk and goat dried milk samples; metronidazole and enrofloxacin were detected in goat milk.

Conclusion

This method offers good reliability and the capacity for simultaneous detection can be used to detect residual contents and evaluate health risks in goat milk and goat dried milk.

Metabolic Fingerprinting of Feces from Calves, Subjected to Gram-Negative Bacterial Endotoxin

Gram-negative bacteria have a well-known impact on the disease state of neonatal calves and their mortality. This study was the first to implement untargeted metabolomics on calves’ fecal samples to unravel the effect of Gram-negative bacterial endotoxin lipopolysaccharide (LPS). In this context, calves were challenged with LPS and administered with fish oil, nanocurcumin, or dexamethasone to evaluate treatment effects. Ultra-high-performance liquid-chromatography high-resolution mass spectrometry (UHPLC-HRMS) was employed to map fecal metabolic fingerprints from the various groups before and after LPS challenge. Based on the generated fingerprints, including 9650 unique feature ions, significant separation according to LPS group was achieved through orthogonal partial least squares discriminant analysis (Q² of 0.57 and p-value of 0.022), which allowed the selection of 37 metabolites as bacterial endotoxin markers. Tentative identification of these markers suggested that the majority belonged to the subclass of the carboxylic acid derivatives—amino acids, peptides, and analogs—and fatty amides, with these subclasses playing a role in the metabolism of steroids, histidine, glutamate, and folate. Biological interpretations supported the revealed markers’ potential to aid in disease diagnosis, whereas beneficial effects were observed following dexamethasone, fish oil, and nanocurcumin treatment.

Investigating a human pesticide intoxication incident: The importance of robust analytical approaches

A human intoxication incident attributed to pesticide abuse was investigated using cutting-edge analytical methodologies. An LC-ESI-MS/MS method, based on a hybrid solid-phase extraction protocol (hybrid-SPE), was applied for the detection and quantification of several pesticides and metabolites in human biological fluids. Concomitantly, an UHPLC-HRMS method was applied to investigate potential metabolites, assisted by a complementary GC-MS method to elucidate the presence of plausible pesticides co-formulants. The LC-ESI-MS/MS method exhibited acceptable mean recoveries at the lower limit of quantification (LLOQ) and three additional levels, varying from 85 to 106% for all analytes and matrices. In serum, urine, and gastric fluid samples, the suspect compounds, namely chlorpyrifos and myclobutanil, predominated. Gastric fluid samples contained the highest concentrations of chlorpyrifos (39,800 ng/mL) and myclobutanil (18,800 ng/mL), while the neonicotinoid imidacloprid was also quantified, below 30 ng/mL. Notwithstanding, the UHPLC-HRMS analysis unveiled several metabolites of chlorpyrifos and myclobutanil. In parallel, GC-MS analysis, corroborated the presence of several co-formulants in gastric fluid samples, exemplified by m- and o-xylene, and cyclohexanone. Overall, three analytical methods were implemented to elucidate the chemical causality of a human intoxication incident. The presence of suspected active substances, one additional, and several metabolites and co-formulants were documented.

Mass spectrometry-based untargeted metabolomics approach for differentiation of beef of different geographic origins

Beef is a common staple food in many countries, and there is a growing concern over misinformation of beef products, such as false claims of origin, species and production methods. In this study, we used a mass spectrometry-based metabolomics approach to study the metabolite profiles of beef samples purchased from local retailers in Hong Kong. Using multivariate analysis, beef samples from different a) geographical origins, namely the United States (US), Japan and Australia, and b) feeding regimes could be differentiated. We identified twenty-four metabolites to distinguish beef samples from different countries, ten metabolites to identify Angus beef samples from others and seven metabolites to discriminate Australian beef produced by the organic farming from that produced using other farming modes. Based on results of this study, it is concluded that metabolomics provides an efficient strategy for tracing and authenticating beef products to ensure their quality and to protect consumer rights.

Advances in lipidomics

The present article examines recently published literature on lipids, mainly focusing on research involving glycero-, glycerophospho- and sphingo-lipids. The primary aim is identification of distinct profiles in biologic lipidomic systems by ultra-high-performance liquid chromatography (UHPLC) coupled with mass spectrometry (MS, tandem MS) with multivariate data analysis. This review specifically targets lipid biomarkers and disease pathway mechanisms in humans and artificial targets. Different specimen matrices such as primary blood derivatives (plasma, serum, erythrocytes, and blood platelets), faecal matter, urine, as well as biologic tissues (liver, lung and kidney) are highlighted.

A review of strategies for untargeted urinary metabolomic analysis using gas chromatography-mass spectrometry

BACKGROUND

Human urine gives evidence of the metabolism in the body and contains different metabolites at various concentrations. A number of analytical techniques including mass spectrometry (MS) and nuclear magnetic resonance (NMR) have been used to obtain metabolites levels in urine samples. However, gas chromatography-mass spectrometry (GC-MS) is one of the most widely used techniques for urinary metabolomics studies due to its higher sensitivity, resolution, reproducibility, reliability, relatively low cost and ease of operation compared to liquid chromatography-mass spectrometry and NMR.

AIM OF REVIEW

This review looks at various aspects of urine preparation prior to analysis by GC-MS including sample storage, urease pretreatment, derivatization, use of internal standard and quality control samples for data correction. In addition, most common types of inlet liners, ionization techniques and columns are discussed and a summary of mass analyzers are also highlighted. Lastly, the role of retention index in metabolite identification and data normalization methods are presented.

KEY SCIENTIFIC CONCEPTS OF REVIEW

The purpose of this review is summarizing methods of sample storage, pretreatment, and GC-MS analysis that are mostly used in urine metabolomics studies. Specific emphasis is given to the critical steps within the GC-MS urine metabolomics that those new to this field need to be aware of and the remaining challenges that require further attention and studies.

Untargeted Metabolomics to Reveal Red versus White Meat-Associated Gut Metabolites in a Prudent and Western Dietary Context

SCOPE

To improve understanding of the epidemiological link between red and processed meat consumption and chronic diseases, more insight into the formation of metabolites during meat digestion is warranted.

METHODS AND RESULTS

Untargeted mass-spectrometry-based metabolomics is applied to explore the impact of red and processed meat consumption (compared to chicken), combined with a prudent or Western dietary pattern. A pig feeding study (n = 32), as a sentinel for humans, is conducted in a 2 × 2 factorial design for 4 weeks. The luminal content of the small intestine and colon are collected to determine their metabolic fingerprints. Seventy-six metabolites (38 in the small intestine, 32 in the colon, and 6 in both intestinal compartments) contributing to the distinct gut metabolic profiles of pigs fed either chicken or red and processed meat are (tentatively) identified. Consumption of red and processed meat results in higher levels of short- and medium-chain acylcarnitines and 3-dehydroxycarnitine, irrespective of dietary context, whereas long-chain acylcarnitines and monoacylglycerols are associated with the red and processed Western diet.

CONCLUSION

The identification of red and processed meat-associated gut metabolites in this study contributes to the understanding of meat digestion in a complex but controlled dietary context and its potential health effects.

Rapid LA-REIMS and comprehensive UHPLC-HRMS for metabolic phenotyping of feces

Ambient ionization-based techniques hold great potential for rapid point-of-care applicable metabolic fingerprinting of tissue and fluids. Hereby, feces represents a unique biospecimen as it integrates the complex interactions between the diet, gut microbiome and host, and is therefore ideally suited to study the involvement of the diet-gut microbiome axis in metabolic diseases and their treatments at a molecular level. We present a new method for rapid (<10 s) metabolic fingerprinting of feces, i.e. laser-assisted rapid evaporative ionization mass spectrometry (LA-REIMS) with an Nd:YAG laser (2940 nm) and quadrupole Time-of-Flight mass spectrometer as main components. The LA-REIMS method was implemented on mimicked crude feces samples from individuals that were assigned a state of type 2 diabetes or euglycaemia. Based on the generated fingerprints, enclosing 4923 feature ions, significant segregation according to disease classification was achieved through orthogonal partial least squares discriminant analysis (Q²(Y) of 0.734 and p-value of 1.93e^-17) and endorsed by a general classification accuracy of 90.5%. A comparison between the discriminative performance of the novel LA-REIMS and our established ultra-high performance liquid-chromatography high-resolution MS (UHPLC-HRMS) metabolomics and lipidomics methodologies for fingerprinting of stool was performed. Based on the supervised modelling results upon UHPLC-HRMS (Q²(Y) ≥ 0.655 and p-value ≤ 4.11 e^-5), equivalent or better discriminative performance of LA-REIMS fingerprinting was concluded. Eventually, comprehensive UHPLC-HRMS was employed to assess metabolic alterations as observed for the defined classes, whereby metformin treatment of the type 2 diabetes patients was considered a relevant study factor to acquire new mechanistic insights. More specifically, ten metabolization products of metformin were identified, with (hydroxylated) triazepinone and metformin-cholesterol reported for the first time in vivo.In conclusion, LA-REIMS was established as an expedient strategy for rapid metabolic fingerprinting of feces, whereby potential implementations may relate, but are not limited to differential diagnosis and treatment efficacy evaluation of metabolic diseases. Yet, LC-HRMS remains essential for in-depth biological interpretation.

Metabolomic Analysis of Cricket paralysis virus Infection in Drosophila S2 Cells Reveals Divergent Effects on Central Carbon Metabolism as Compared with Silkworm Bm5 Cells

High-throughput approaches have opened new opportunities for understanding biological processes such as persistent virus infections, which are widespread. However, the potential of persistent infections to develop towards pathogenesis remains to be investigated, particularly with respect to the role of host metabolism. To explore the interactions between cellular metabolism and persistent/pathogenic virus infection, we performed untargeted and targeted metabolomic analysis to examine the effects of Cricket paralysis virus (CrPV, Dicistroviridae) in persistently infected silkworm Bm5 cells and acutely infected Drosophila S2 cells. Our previous study (Viruses 2019, 11, 861) established that both glucose and glutamine levels significantly increased during the persistent period of CrPV infection of Bm5 cells, while they decreased steeply during the pathogenic stages. Strikingly, in this study, an almost opposite pattern in change of metabolites was observed during different stages of acute infection of S2 cells. More specifically, a significant decrease in amino acids and carbohydrates was observed prior to pathogenesis, while their abundance significantly increased again during pathogenesis. Our study illustrates the occurrence of diametrically opposite changes in central carbon mechanisms during CrPV infection of S2 and Bm5 cells that is possibly related to the type of infection (acute or persistent) that is triggered by the virus.

Validated Ultra-High-Performance Liquid Chromatography Hybrid High-Resolution Mass Spectrometry and Laser-Assisted Rapid Evaporative Ionization Mass Spectrometry for Salivary Metabolomics

Whereas urine and blood are typically targeted in clinical research, saliva represents an interesting alternative because its intrinsic metabolome is chemically diverse and reflective for various biological processes. Moreover, saliva collection is easy and noninvasive, which is especially valuable for cohorts in which sample collection is challenging, for example, infants and children. With this rationale, we established a validated ultra-high-performance liquid chromatography high-resolution mass spectrometry (UHPLC-HRMS) method for salivary metabolic profiling and fingerprinting. Hereby, 450 μL of saliva was centrifuged and passed over a 0.45-μm polyamide membrane filter, after which the extract was subjected to chromatographic analysis (HSS T3 column) and Q-Exactive Orbitrap-MS. For the majority of the profiled metabolites, good linearity (R² ≥ 0.99) and precision (coefficient of variance ≤ 15%) was achieved. The fingerprinting performance was evaluated based on the complete metabolome (11 385 components), whereby 76.8% was found compliant with the criteria for precision (coefficient of variance ≤ 30%) and 82.7% with linearity (R² ≥ 0.99). In addition, the method was proven fit-for-purpose for a cohort of 140 adolescents (6-16 years, stratified according to weight), yielding relevant profiles (45 obesity-related metabolites) and discriminative fingerprints (Q² of 0.784 for supervised discriminant analysis). Alternatively, laser-assisted rapid evaporative ionization mass spectrometry (LA-REIMS) was established for rapid fingerprinting of saliva, thereby using a Nd:YAG laser and Xevo G2-XS QToF-MS. With an acquisition time of 0.5 min per sample, LA-REIMS offers unique opportunities for point-of-care applications. In conclusion, this work presents a platform of UHPLC-HRMS and LA-REIMS, complementing each other to perform salivary metabolomics.

Impact of storage conditions on the human stool metabolome and lipidome: Preserving the most accurate fingerprint

Faecal metabolomics markedly emerged in clinical as well as analytical chemistry through the unveiling of aberrations in metabolic signatures as reflection of variance in gut (patho)physiology and beyond. Logistic hurdles, however, hinder the analysis of stool samples immediately following collection, inferring the need of biobanking. Yet, the optimum way of storing stool material remains to be determined, in order to conserve an accurate snapshot of the metabolome and circumvent artifacts regarding the disease and parameter(s) under observation. To address this problem, this study scrutinised the impact of freeze-thaw cycling, storage duration, temperature and aerobicity, thereby using ultra-high performance liquid chromatography-high-resolution mass spectrometry (UPLC-HRMS)-based polar metabolomics and lipidomics methodologies for faecal metabolomics. Both targeted (n > 400) and untargeted approaches were implemented to assess storage effects on individual chemical classes of metabolites as well as the faecal fingerprint. In general, recommendations are that intact stool samples should be divided into aliquots, lyophilised and stored at -80 °C for a period no longer than 18 weeks, and avoiding any freeze-thawing. The first preservation week exerted the most decisive impact regarding storage temperature, i.e. 12.1% and 6.4% of the polar metabolome experienced a shift at -20 °C and at -80 °C, respectively, whereas 8.6% and 7.9% was observed to be changed significantly for the lipidome. In addition, aside from the negligible impact of aerobicity, the polar metabolome appeared to be more dependent on the storage conditions applied compared to the lipidome, which emerged as the more stable fraction when assessing the storage duration for 25 weeks. If the interest would greatly align with particular chemical classes, such as branched-chain amino acids or short-chain fatty acids, specific storage duration recommendations are reported. The provided insights on the stability of the faecal metabolome may contribute to a more reasoned design of experiments in biomarker detection or pathway elucidation within the field of faecal metabolomics.

Describing the fecal metabolome in cryogenically collected samples from healthy participants

The chemical composition of feces plays an important role in human metabolism. Metabolomics and lipidomics are valuable tools for screening the metabolite composition in feces. Here we set out to describe fecal metabolite composition in healthy participants in frozen stools. Frozen stool samples were collected from 10 healthy volunteers and cryogenically drilled in four areas along the specimen. Polar metabolites were analyzed using derivatization followed by two-dimensional gas chromatography and time of flight mass spectrometry. Lipids were detected using ultra high-performance liquid chromatography coupled with quadruple time-of-flight mass spectrometry. 2326 metabolic features were detected. Out of a total of 298 metabolites that were annotated we report here 185 that showed a technical variation of x < 30%. These metabolites included amino acids, fatty acid derivatives, carboxylic acids and phenolic compounds. Lipids predominantly belonged to the groups of diacylglycerols, triacylglycerols and ceramides. Metabolites varied between sampling areas, some were broadly homogeneous, others varied 80%. A LASSO-computed network using metabolites present in all areas showed two main clusters describing the system, DAG lipids and phenyllactic acid. In feces from healthy participants, the main groups detected were phenolic compounds, ceramides, diacylglycerols and triacylglycerols.

A Metabolomics Approach to Unravel Cricket Paralysis Virus Infection in Silkworm Bm5 Cells

How a host metabolism responds to infection with insect viruses and how it relates to pathogenesis, is little investigated. Our previous study observed that Cricket paralysis virus (CrPV, Dicistroviridae) causes short term persistence in silkworm Bm5 cells before proceeding to acute infection. In this study, a metabolomics approach based on high resolution mass spectrometry was applied to investigate how a host metabolism is altered during the course of CrPV infection in Bm5 cells and which changes are characteristic for the transition from persistence to pathogenicity. We observed that CrPV infection led to significant and stage-specific metabolic changes in Bm5 cells. Differential metabolites abundance and pathway analysis further identified specific metabolic features at different stages in the viral life cycle. Notably, both glucose and glutamine levels significantly increased during CrPV persistent infection followed by a steep decrease during the pathogenic stages, suggesting that the central carbon metabolism was significantly modified during CrPV infection in Bm5 cells. In addition, dynamic changes in levels of polyamines were detected. Taken together, this study characterized for the first time the metabolic dynamics of CrPV infection in insect cells, proposing a central role for the regulation of both amino acid and carbohydrate metabolism during the period of persistent infection of CrPV in Bm5 cells.