Hippurate: The Natural History of a Mammalian–Microbial Cometabolite

Gut microbiota may modify the association between dietary polyphenol intake and circulating levels of hippuric acid: results from a 1-year longitudinal study in China

BACKGROUND

Hippuric acid (HA), a host-microbe co-metabolite, normally derives from gut microbial catabolism of dietary polyphenols.

OBJECTIVES

We investigated the potential interplay between dietary polyphenols and gut microbiota on circulating HA levels, and examined the associations between serum concentrations of HA and cardiometabolic risk markers.

METHODS

In a 1-year cohort of 754 community-dwelling adults, serum HA and its precursor [benzoic acid (BA)] and fecal microbiota were assayed using liquid chromatography-tandem mass spectrometry and 16S ribosomal RNA sequencing, respectively. Diet, blood pressure, blood glucose and lipids were measured twice, 1-year apart. Arterial stiffness [indicated by brachial-ankle pulse wave velocity (baPWV) and ankle-brachial index] and liver fat accumulation [indicated by controlled attenuation parameter (CAP)] were measured after 1 year.

RESULTS

We identified 27 microbial genera whose relative abundance was positively associated with serum HA concentrations (PFDR<0.05) and constructed a microbial score to reflect the overall HA-producing potential. In multivariate-adjusted linear models, dietary intake of catechins and chlorogenic acids was positively associated with serum HA concentrations among participants with a higher microbial score (β=0.26, P=0.03), but not among those with a lower score (β=-0.13, P=0.30, Pinteraction=0.03). Participants with higher intake of dietary catechins and chlorogenic acids had lower triglyceride (Percentage change = -5.9%, P<0.05). Each 1 μmol/L increase in serum HA, but not in BA, was associated with 5.7%, 1.5%, 1.7%, 1.7%, and 1.7% decrease in triglyceride, systolic blood pressure, diastolic blood pressure, baPWV, and CAP, respectively (all P<0.05).

CONCLUSIONS

The gut microbial genera that predicted circulating HA levels may modify the association between dietary polyphenol intake and circulating HA levels, and elevated serum HA concentrations are favorably associated with multiple cardiometabolic risk markers.

Influential articles in autism and gut microbiota: bibliometric profile and research trends

Objective

Autism spectrum disorder (ASD) is a common neurodevelopmental disorder. Increasing evidence suggests that it is potentially related to gut microbiota, but no prior bibliometric analysis has been performed to explore the most influential works in the relationships between ASD and gut microbiota. In this study, we conducted an in-depth analysis of the most-cited articles in this field, aiming to provide insights to the existing body of research and guide future directions.

Methods

A search strategy was constructed and conducted in the Web of Science database to identify the 100 most-cited papers in ASD and gut microbiota. The Biblioshiny package in R was used to analyze and visualize the relevant information, including citation counts, country distributions, authors, journals, and thematic analysis. Correlation and comparison analyses were performed using SPSS software.

Results

The top 100 influential manuscripts were published between 2000 and 2021, with a total citation of 40,662. The average number of citations annually increased over the years and was significantly correlated to the year of publication (r = 0.481, p < 0.01, Spearman's rho test). The United States was involved in the highest number of publications (n = 42). The number of publications in the journal was not significantly related to the journal's latest impact factor (r = 0.016, p > 0.05, Spearman's rho test). Co-occurrence network and thematic analysis identified several important areas, such as microbial metabolites of short-chain fatty acids and overlaps with irritable bowel syndrome.

Conclusion

This bibliometric analysis provides the key information of the most influential studies in the area of ASD and gut microbiota, and suggests the hot topics and future directions. The findings of this study can serve as a valuable reference for researchers and policymakers, guiding the development and implementation of the scientific research strategies in this area.

Intrahepatic levels of microbiome-derived hippurate associates with improved metabolic dysfunction-associated steatotic liver disease

OBJECTIVE

Metabolic dysfunction-associated steatotic liver disease (MASLD) is characterised by lipid accumulation in the liver and is often associated with obesity and type 2 diabetes. The gut microbiome recently emerged as a significant player in liver metabolism and health. Hippurate, a host-microbial co-metabolite has been associated with human gut microbial gene richness and with metabolic health. However, its role on liver metabolism and homeostasis is poorly understood.

METHODS

We characterised liver biospies from 318 patients with obesity using RNAseq and metabolomics in liver and plasma to derive associations among hepatic hippurate, hepatic gene expression and MASLD and phenotypes. To test a potential beneficial role for hippurate in hepatic insulin resistance, we profile the metabolome of (IHH) using ultra-high-performance liquid chromatography coupled to high-resolution tandem mass spectrometry (UHPLC-MS/MS), and characterised intracellular triglyceride accumulation and glucose internalisation after a 24 h insulin exposure.

RESULTS

We first report significant associations among MASLD traits, plasma and hepatic hippurate. Further analysis of the hepatic transcriptome shows that liver and plasma hippurate are inversely associated with MASLD, implicating lipid metabolism and regulation of inflammatory responses pathways. Hippurate treatment inhibits lipid accumulation and rescues insulin resistance induced by 24-hour chronic insulin in IHH. Hippurate also improves hepatocyte metabolic profiles by increasing the abundance of metabolites involved in energy homeostasis that are depleted by chronic insulin treatment while decreasing those involved in inflammation.

CONCLUSIONS

Altogether, our results further highlight hippurate as a mechanistic marker of metabolic health, by its ability to improve metabolic homeostasis as a postbiotic candidate.

Blood metabolomic profiling reveals new targets in the management of psychological symptoms associated with severe alcohol use disorder

Background

Alcohol use disorder (AUD) is a global health problem with limited therapeutic options. The biochemical mechanisms that lead to this disorder are not yet fully understood, and in this respect, metabolomics represents a promising approach to decipher metabolic events related to AUD. The plasma metabolome contains a plethora of bioactive molecules that reflects the functional changes in host metabolism but also the impact of the gut microbiome and nutritional habits.

Methods

In this study, we investigated the impact of severe AUD (sAUD), and of a 3-week period of alcohol abstinence, on the blood metabolome (non-targeted LC-MS metabolomics analysis) in 96 sAUD patients hospitalized for alcohol withdrawal.

Results

We found that the plasma levels of different lipids ((lyso)phosphatidylcholines, long-chain fatty acids), short-chain fatty acids (i.e. 3-hydroxyvaleric acid) and bile acids were altered in sAUD patients. In addition, several microbial metabolites, including indole-3-propionic acid, p-cresol sulfate, hippuric acid, pyrocatechol sulfate, and metabolites belonging to xanthine class (paraxanthine, theobromine and theophylline) were sensitive to alcohol exposure and alcohol withdrawal. 3-Hydroxyvaleric acid, caffeine metabolites (theobromine, paraxanthine, and theophylline) and microbial metabolites (hippuric acid and pyrocatechol sulfate) were correlated with anxiety, depression and alcohol craving. Metabolomics analysis in postmortem samples of frontal cortex and cerebrospinal fluid of those consuming a high level of alcohol revealed that those metabolites can be found also in brain tissue.

Conclusions

Our data allow the identification of neuroactive metabolites, from interactions between food components and microbiota, which may represent new targets arising in the management of neuropsychiatric diseases such as sAUD.

Funding

Gut2Behave project was initiated from ERA-NET NEURON network (Joint Transnational Call 2019) and was financed by Academy of Finland, French National Research Agency (ANR-19-NEUR-0003-03) and the Fonds de la Recherche Scientifique (FRS-FNRS; PINT-MULTI R.8013.19, Belgium). Metabolomics analysis of the TSDS samples was supported by grant from the Finnish Foundation for Alcohol Studies.

Alcohol use-associated alterations in the circulating metabolite profile in the general population and in individuals with major depressive disorder

Our aim was to evaluate whether alcohol use is associated with changes in the circulating metabolite profile similar to those present in persons with depression. If so, these findings could partially explain the link between alcohol use and depression. We applied a targeted liquid chromatography mass spectrometry method to evaluate correlates between concentrations of 86 circulating metabolites and self-reported alcohol use in a cohort of the non-depressed general population (GP) (n = 247) and a cohort of individuals with major depressive disorder (MDD) (n = 99). Alcohol use was associated with alterations in circulating concentrations of metabolites in both cohorts. Our main finding was that self-reported alcohol use was negatively correlated with serum concentrations of hippuric acid in the GP cohort. In the GP cohort, consumption of six or more doses per week was associated with low hippuric acid concentrations, similar to those observed in the MDD cohort, but in these individuals it was regardless of their level of alcohol use. Reduced serum concentrations of hippuric acid suggest that already-moderate alcohol use is associated with depression-like changes in the serum levels of metabolites associated with gut microbiota and liver function; this may be one possible molecular level link between alcohol use and depression.

Decoding polyphenol metabolism in patients with Crohn's disease: Insights from diet, gut microbiota, and metabolites

Crohn's disease (CD) is a chronic and progressive inflammatory disease that can involve any part of the gastrointestinal tract. The protective role of dietary polyphenols has been documented in preclinical models of CD. Gut microbiota mediates the metabolism of polyphenols and affects their bioactivity and physiological functions. However, it remains elusive the capacity of microbial polyphenol metabolism in CD patients and healthy controls (HCs) along with its correlation with polyphenols intake and polyphenol-derived metabolites. Thus, we aimed to decode polyphenol metabolism in CD patients through aspects of diet, gut microbiota, and metabolites. Dietary intake analysis revealed that CD patients exhibited decreased intake of polyphenols. Using metagenomic data from two independent clinical cohorts (FAH-SYSU and PRISM), we quantified abundance of polyphenol degradation associated bacteria and functional genes in CD and HCs and observed a lower capacity of flavonoids degradation in gut microbiota residing in CD patients. Furthermore, through analysis of serum metabolites and enterotypes in participants of FAH-SYSU cohort, we observed that CD patients exhibited reduced levels of serum hippuric acid (HA), one of polyphenol-derived metabolites. HA level was higher in healthier enterotypes (characterized by dominance of Ruminococcaceae and Prevotellaceae, dominant by HCs) and positively correlated with multiple polyphenols intake and abundance of bacteria engaged in flavonoids degradation as well as short-chain fatty acid production, which could serve as a biomarker for effective polyphenol metabolism by the gut microbiota and a healthier gut microbial community structure. Overall, our findings provide a foundation for future work exploring the polyphenol-based or microbiota-targeted therapeutic strategies in CD.

Insights into the early-life chemical exposome of Nigerian infants and potential correlations with the developing gut microbiome

Early-life exposure to natural and synthetic chemicals can impact acute and chronic health conditions. Here, a suspect screening workflow anchored on high-resolution mass spectrometry was applied to elucidate xenobiotics in breast milk and matching stool samples collected from Nigerian mother-infant pairs (n = 11) at three time points. Potential correlations between xenobiotic exposure and the developing gut microbiome, as determined by 16S rRNA gene amplicon sequencing, were subsequently explored. Overall, 12,192 and 16,461 features were acquired in the breast milk and stool samples, respectively. Following quality control and suspect screening, 562 and 864 features remained, respectively, with 149 of these features present in both matrices. Taking advantage of 242 authentic reference standards measured for confirmatory purposes of food bio-actives and toxicants, 34 features in breast milk and 68 features in stool were identified and semi-quantified. Moreover, 51 and 78 features were annotated with spectral library matching, as well as 416 and 652 by in silico fragmentation tools in breast milk and stool, respectively. The analytical workflow proved its versatility to simultaneously determine a diverse panel of chemical classes including mycotoxins, endocrine-disrupting chemicals (EDCs), antibiotics, plasticizers, perfluorinated alkylated substances (PFAS), and pesticides, although it was originally optimized for polyphenols. Spearman rank correlation of the identified features revealed significant correlations between chemicals of the same classification such as polyphenols. One-way ANOVA and differential abundance analysis of the data obtained from stool samples revealed that molecules of plant-based origin elevated as complementary foods were introduced to the infants' diets. Annotated compounds in the stool, such as tricetin, positively correlated with the genus Blautia. Moreover, vulgaxanthin negatively correlated with Escherichia-Shigella. Despite the limited sample size, this exploratory study provides high-quality exposure data of matched biospecimens obtained from mother-infant pairs in sub-Saharan Africa and shows potential correlations between the chemical exposome and the gut microbiome.

Meta-analysis guided development of a standard artificial urine

In this study, we present the first meta-analysis of human urine reported in the literature, drawing data from a total of 35 articles with a combined participant count of 14,021. Through this analysis, we have developed an artificial urine (AU) composition that can be adjusted within typical physiological parameters for in vitro applications. Our findings demonstrate the utility of this AU in determining the solubility of nitrofurantoin, particularly in the context of crystalluria. Notably, we observe that in saline, nitrofurantoin solubility, within the framework of its urinary pharmacokinetics, suggests a risk of crystalluria. However, in AU, this risk is mitigated due to complexation with urea. More broadly, we anticipate that our developed formulation will serve as a foundation for translational studies across biomedical and pharmaceutical sciences.

Temporal metabolomics state in pregnant rat: Analysis of amniotic fluid, placenta, and maternal plasma at embryonic and fetal time points

INTRODUCTION

During pregnancy, the dynamic metabolic demands for fetal growth require a continuous supply of essential metabolites. Understanding maternal metabolome changes during gestation is crucial for predicting disease risks in neonates.

METHODS

The study aimed to characterize the placental and amniotic fluid (AF) metabolomes during gestation in rats at gestational days GD-13 and 19 reflecting the end of the embryonic and fetal periods, respectively, and the maternal plasma, using metabolomics (LC-MS) and chemometrics. The objective was to highlight, through univariate and multivariate analyses, the complementarity of the data obtained from these different biological matrices.

RESULTS

The biological matrix had more impact on the metabolome composition than the gestational stage. The placental and AF metabolomes showed specific metabolome evolving over the two gestational stages. Analyzing the three targeted metabolomes revealed evolving pathways in arginine and proline metabolism/glutathione metabolism and phenylalanine metabolism; purine metabolism; and carbohydrate metabolism. Significantly, lipid metabolism in the placenta exhibited substantial changes with higher levels of certain phosphatidylethanolamine and sphingomyelins at GD19 while some cholesteryl esters and some glycosphingolipids levels being in higher levels at GD13.

DISCUSSION

These data highlight the metabolic gradients (mainly in placenta, also in AF, but only a few in plasma) observed through embryonic patterning and organ development during mid-to late gestation.

Common and distinct metabolomic markers related to immune aging in Western European and East African populations

In old age, impaired immunity causes high susceptibility to infections and cancer, higher morbidity and mortality, and poorer vaccination efficiency. Many factors, such as genetics, diet, and lifestyle, impact aging. This study aimed to investigate how immune responses change with age in healthy Dutch and Tanzanian individuals and identify common metabolites associated with an aged immune profile. We performed untargeted metabolomics from plasma to identify age-associated metabolites, and we correlated their concentrations with ex-vivo cytokine production by immune cells, DNA methylation-based epigenetic aging, and telomere length. Innate immune responses were impacted differently by age in Dutch and Tanzanian cohorts. Age-related decline in steroid hormone precursors common in both populations was associated with higher systemic inflammation and lower cytokine responses. Hippurate and 2-phenylacetamide, commonly more abundant in older individuals, were negatively correlated with cytokine responses and telomere length and positively correlated with epigenetic aging. Lastly, we identified several metabolites that might contribute to the stronger decline in innate immunity with age in Tanzanians. The shared metabolomic signatures of the two cohorts suggest common mechanisms of immune aging, revealing metabolites with potential contributions. These findings also reflect genetic or environmental effects on circulating metabolites that modulate immune responses.

Urinary metabolic characterization of advanced tuberculous meningitis cases in a South African paediatric population

Tuberculous meningitis (TBM) is a severe form of tuberculosis with high neuro-morbidity and mortality, especially among the paediatric population (aged ≤12 years). Little is known of the associated metabolic changes. This study aimed to identify characteristic metabolic markers that differentiate severe cases of paediatric TBM from controls, through non-invasive urine collection. Urine samples selected for this study were from two paediatric groups. Group 1: controls (n = 44): children without meningitis, no neurological symptoms and from the same geographical region as group 2. Group 2: TBM cases (n = 13): collected from paediatric patients that were admitted to Tygerberg Hospital in South Africa on the suspicion of TBM, mostly severely ill; with a later confirmation of TBM. Untargeted 1H NMR-based metabolomics data of urine were generated, followed by statistical analyses via MetaboAnalyst (v5.0), and the identification of important metabolites. Twenty nine urinary metabolites were identified as characteristic of advanced TBM and categorized in terms of six dysregulated metabolic pathways: 1) upregulated tryptophan catabolism linked to an altered vitamin B metabolism; 2) perturbation of amino acid metabolism; 3) increased energy production-metabolic burst; 4) disrupted gut microbiota metabolism; 5) ketoacidosis; 6) increased nitrogen excretion. We also provide original biological insights into this biosignature of urinary metabolites that can be used to characterize paediatric TBM patients in a South African cohort.

Metabolic maturation in the infant urine during the first 3 months of life

The infant urine metabolome provides a body metabolic snapshot, and the sample collection can be done without stressing the fragile infant. 424 infant urine samples from 157 infants were sampled longitudinally at 1-, 2-, and 3 months of age. 49 metabolites were detected using proton nuclear magnetic resonance spectroscopy. Data were analyzed with multi- and univariate statistical methods to detect differences related to infant age-stage, gestational age, mother's pre-pregnancy BMI, C-section, infant birth weight, and infant sex. Significant differences were identified between age-stage (pbonferoni < 0.05) in 30% (15/49) of the detected metabolites. Urine creatinine increased significantly from 1 to 3 months. In addition, myo-inositol, taurine, methionine, and glucose seem to have conserved levels within the individual over time. We calculated a urine metabolic maturation age and found that the metabolic age at 3 months is negatively correlated to weight at 1 year. These results demonstrate that the metabolic maturation can be observed in urine metabolome with implications on infant growth and specifically suggesting that the systematic age effect on creatinine promotes caution in using this as normalization of other urine metabolites.

Serum metabolome and gut microbiome alterations are associated with low handgrip strength in older adults

Handgrip strength (HGS), which represents global muscle strength, is a powerful indicator of disability and mortality in older adults; it is also used for the diagnosis of possible- or probable- sarcopenia and physical frailty. This study aimed to explore the metabolic mechanisms and potential biomarkers associated with declining HGS among older adults. We recruited 15 age- and environment-matched inpatients (age, 77-90 years) with low or normal HGS. Liquid chromatography-mass spectrometry (LC-MS) and 16S ribosomal DNA (rDNA) gene sequencing were performed to analyze the metabolome of serum and stool samples and the gut microbiome composition of stool samples. Spearman's correlation analysis was used to identify the potential serum and fecal metabolites associated with HGS. We assessed the levels of serum and fecal metabolites belonging to the class of cinnamic acids and derivatives and reported that the levels of carboxylic acids and their derivatives decreased in the low-HGS group. Serum levels of microbial metabolites, including cinnamoylglycine, 4-methoxycinnamic acid, and (e)-3,4,5-trimethoxycinnamic acid, were positively correlated with HGS. We found that gut microbial α-diversity was significantly higher in the low-HGS group, whereas higher β-diversity was observed in the normal group. The relative abundances of the genera Parabacteroides and Intestinibacter increased significantly in the low-HGS group and were negatively correlated with the serum levels of cinnamoylglycine. The identified metabolites whose levels were markedly altered, and intestinal flora associated with these metabolites suggest the potential metabolic underpinnings for HGS and provide a basis for the further identification of biomarkers of muscle strength decline in older adults.

Comparative profiling of gut microbiota and metabolome in diet-induced obese and insulin-resistant C57BL/6J mice

Diet-based models are commonly used to investigate obesity and related disorders. We conducted a comparative profiling of three obesogenic diets HFD, high fat diet; HFHF, high fat high fructose diet; and HFCD, high fat choline deficient diet to assess their impact on the gut microbiome and metabolome. After 20 weeks, we analyzed the gut microbiota and metabolomes of liver, plasma, cecal, and fecal samples. Fecal and plasma bile acids (BAs) and fecal short-chain fatty acids (SCFAs) were also examined. Significant changes were observed in fecal and cecal metabolites, with increased Firmicutes and decreased Bacteroidetes in the HFD, HFHF, and HFCD-fed mice compared to chow and LFD (low fat diet)-fed mice. Most BAs were reduced in plasma and fecal samples of obese groups, except taurocholic acid, which increased in HFCD mice's plasma. SCFAs like acetate and butyrate significantly decreased in obesogenic diet groups, while propionic acid specifically decreased in the HFCD group. Pathway analysis revealed significant alterations in amino acid, carbohydrate metabolism, and nucleic acid biosynthesis pathways in obese mice. Surprisingly, even LFD-fed mice showed distinct changes in microbiome and metabolite profiles compared to the chow group. This study provides insights into gut microbiome dysbiosis and metabolite alterations induced by obesogenic and LFD diets in various tissues. These findings aid in selecting suitable diet models to study the role of the gut microbiome and metabolites in obesity and associated disorders, with potential implications for understanding similar pathologies in humans.

Microbial metabolites as modulators of host physiology

The gut microbiota is increasingly recognised as a key player in influencing human health and changes in the gut microbiota have been strongly linked with many non-communicable conditions in humans such as type 2 diabetes, obesity and cardiovascular disease. However, characterising the molecular mechanisms that underpin these associations remains an important challenge for researchers. The gut microbiota is a complex microbial community that acts as a metabolic interface to transform ingested food (and other xenobiotics) into metabolites that are detected in the host faeces, urine and blood. Many of these metabolites are only produced by microbes and there is accumulating evidence to suggest that these microbe-specific metabolites do act as effectors to influence human physiology. For example, the gut microbiota can digest dietary complex polysaccharides (such as fibre) into short-chain fatty acids (SCFA) such as acetate, propionate and butyrate that have a pervasive role in host physiology from nutrition to immune function. In this review we will outline our current understanding of the role of some key microbial metabolites, such as SCFA, indole and bile acids, in human health. Whilst many studies linking microbial metabolites with human health are correlative we will try to highlight examples where genetic evidence is available to support a specific role for a microbial metabolite in host health and well-being.

Antidiabetic effect of Ardisia elliptica extract and its mechanisms of action in STZ-NA-induced diabetic rat model via 1H-NMR-based metabolomics

ETHNOPHARMACOLOGICAL RELEVANCE

Ardisia elliptica Thunb. (AE) (Primulaceae) is a medicinal plant found in the Malay Peninsula and has been traditionally used to treat diabetes. However, limited studies to date in providing scientific evidence to support the antidiabetic efficacy of this plant by in-vitro and in-vivo models.

AIM OF THE STUDY

To investigate the anti-hyperglycemic potential of AE through in-vitro enzymatic activities and streptozotocin-nicotinamide (STZ-NA) induced diabetic rat models using proton-nuclear magnetic resonance (1H-NMR)-based metabolomics approach.

MATERIALS AND METHODS

Anti-α-amylase and anti-α-glucosidase activities of the hydroethanolic extracts of AE were evaluated. The absolute quantification of bioactive constituents, using ultra-high performance liquid chromatography (UHPLC) was performed for the most active extract. Three different dosage levels of the AE extract were orally administered for 4 weeks consecutively in STZ-NA induced diabetic rats. Physical assessments, biochemical analysis, and an untargeted 1H-NMR-based metabolomics analysis of the urine and serum were carried out on the animal model.

RESULTS

Type 2 diabetes mellitus (T2DM) rat model was successfully developed based on the clear separation observed between the STZ-NA induced diabetic and normal non-diabetic groups. Discriminating biomarkers included glucose, citrate, succinate, allantoin, hippurate, 2-oxoglutarate, and 3-hydroxybutyrate, as determined through an orthogonal partial least squares-discriminant analysis (OPLS-DA) model. A treatment dosage of 250 mg/kg body weight (BW) of standardized 70% ethanolic AE extract mitigated increase in serum glucose, creatinine, and urea levels, providing treatment levels comparable to that obtained using metformin, with flavonoids primarily contribute to the anti-hyperglycemic activities. Urinary metabolomics disclosed that the following disturbed metabolism pathways: the citrate cycle (TCA cycle), butanoate metabolism, glycolysis and gluconeogenesis, pyruvate metabolism, and synthesis and degradation of ketone bodies, were ameliorated after treatment with the standardized AE extract.

CONCLUSIONS

This study demonstrated the first attempt at revealing the therapeutic effect of oral treatment with 250 mg/kg BW of standardized AE extract on chemically induced T2DM rats. The present study provides scientific evidence supporting the ethnomedicinal use of Ardisia elliptica and further advances the understanding of the fundamental molecular mechanisms affected by this herbal antidote.

Metabolic alterations in urine among the patients with severe fever with thrombocytopenia syndrome

BACKGROUND

The pathogenesis of severe fever with thrombocytopenia syndrome (SFTS) remained unclear. We aimed to profile the metabolic alterations in urine of SFTS patients and provide new evidence for its pathogenesis.

METHODS

A case-control study was conducted in the 154th hospital in China. Totally 88 cases and 22 controls aged ≥ 18 years were enrolled. The cases were selected from laboratory-confirmed SFTS patients. The controls were selected among SFTSV-negative population. Those with diabetes, cancer, hepatitis and other sexually transmitted diseases were excluded in both groups. Fatal cases and survival cases were 1:1 matched. Inter-group differential metabolites and pathways were obtained, and the inter-group discrimination ability was evaluated.

RESULTS

Tryptophan metabolism and phenylalanine metabolism were the top one important metabolism pathway in differentiating the control and case groups, and the survival and fatal groups, respectively. The significant increase of differential metabolites in tryptophan metabolism, including 5-hydroxyindoleacetate (5-HIAA), L-kynurenine (KYN), 5-hydroxy-L-tryptophan (5-HTP), 3-hydroxyanthranilic acid (3-HAA), and the increase of phenylpyruvic acid and decrease of hippuric acid in phenylalanine metabolism indicated the potential metabolic alterations in SFTSV infection. The increase of 5-HIAA, KYN, 5-HTP, phenylpyruvic acid and hippuric acid were involved in the fatal progress of SFTS patients.

CONCLUSIONS

Tryptophan metabolism and phenylalanine metabolism might be involved in the pathogenesis of SFTSV infection. These findings provided new evidence for the pathogenesis and treatment of SFTS.

A systematic review of metabolomic findings in adult and pediatric renal disease

Chronic kidney disease (CKD) affects over 0.5 billion people worldwide across their lifetimes. Despite a growingly ageing world population, an increase in all-age prevalence of kidney disease persists. Adult-onset forms of kidney disease often result from lifestyle-modifiable metabolic illnesses such as type 2 diabetes. Pediatric and adolescent forms of renal disease are primarily caused by morphological abnormalities of the kidney, as well as immunological, infectious and inherited metabolic disorders. Alterations in energy metabolism are observed in CKD of varying causes, albeit the molecular mechanisms underlying pathology are unclear. A systematic indexing of metabolites identified in plasma and urine of patients with kidney disease alongside disease enrichment analysis uncovered inborn errors of metabolism as a framework that links features of adult and pediatric kidney disease. The relationship of genetics and metabolism in kidney disease could be classified into three distinct landscapes: (i) Normal genotypes that develop renal damage because of lifestyle and / or comorbidities; (ii) Heterozygous genetic variants and polymorphisms that result in unique metabotypes that may predispose to the development of kidney disease via synergistic heterozygosity, and (iii) Homozygous genetic variants that cause renal impairment by perturbing metabolism, as found in children with monogenic inborn errors of metabolism. Interest in the identification of early biomarkers of onset and progression of CKD has grown steadily in the last years, though it has not translated into clinical routine yet. This systematic review indexes findings of differential concentration of metabolites and energy pathway dysregulation in kidney disease and appraises their potential use as biomarkers.

Harnessing Small-Molecule Analyte Detection in Complex Media: Combining Molecularly Imprinted Polymers, Electrolytic Transistors, and Machine Learning

Small-molecule analyte detection is key for improving quality of life, particularly in health monitoring through the early detection of diseases. However, detecting specific markers in complex multicomponent media using devices compatible with point-of-care (PoC) technologies is still a major challenge. Here, we introduce a novel approach that combines molecularly imprinted polymers (MIPs), electrolyte-gated transistors (EGTs) based on 2D materials, and machine learning (ML) to detect hippuric acid (HA) in artificial urine, being a critical marker for toluene intoxication, parasitic infections, and kidney and bowel inflammation. Reduced graphene oxide (rGO) was used as the sensory material and molecularly imprinted polymer (MIP) as supramolecular receptors. Employing supervised ML techniques based on symbolic regression and compressive sensing enabled us to comprehensively analyze the EGT transfer curves, eliminating the need for arbitrary signal selection and allowing a multivariate analysis during HA detection. The resulting device displayed simultaneously low operating voltages (<0.5 V), rapid response times (≤10 s), operation across a wide range of HA concentrations (from 0.05 to 200 nmol L-1), and a low limit of detection (LoD) of 39 pmol L-1. Thanks to the ML multivariate analysis, we achieved a 2.5-fold increase in the device sensitivity (1.007 μA/nmol L-1) with respect to the human data analysis (0.388 μA/nmol L-1). Our method represents a major advance in PoC technologies, by enabling the accurate determination of small-molecule markers in complex media via the combination of ML analysis, supramolecular analyte recognition, and electrolytic transistors.

Diabetes-associated breast cancer is molecularly distinct and shows a DNA damage repair deficiency

Diabetes commonly affects patients with cancer. We investigated the influence of diabetes on breast cancer biology using a 3-pronged approach that included analysis of orthotopic human tumor xenografts, patient tumors, and breast cancer cells exposed to diabetes/hyperglycemia-like conditions. We aimed to identify shared phenotypes and molecular signatures by investigating the metabolome, transcriptome, and tumor mutational burden. Diabetes and hyperglycemia did not enhance cell proliferation but induced mesenchymal and stem cell-like phenotypes linked to increased mobility and odds of metastasis. They also promoted oxyradical formation and both a transcriptome and mutational signatures of DNA repair deficiency. Moreover, food- and microbiome-derived metabolites tended to accumulate in breast tumors in the presence of diabetes, potentially affecting tumor biology. Breast cancer cells cultured under hyperglycemia-like conditions acquired increased DNA damage and sensitivity to DNA repair inhibitors. Based on these observations, we conclude that diabetes-associated breast tumors may show an increased drug response to DNA damage repair inhibitors.

The role of microbiota and its modulation in colonic diverticular disease

BACKGROUND

Diverticular disease (DD) is a common condition in Western countries. The role of microbiota in the pathogenesis of DD and its related symptoms has been frequently postulated since most complications of this disease are bacteria-driven and most therapies rely on microbiota modulation. Preliminary data showed fecal microbial imbalance in patients with DD, particularly when symptomatic, with an increase of pro-inflammatory and potentially pathogenetic bacteria. In addition, bacterial metabolic markers can mirror specific pathways of the disease and may be even used for monitoring treatment effects. All treatments currently suggested for DD can affect microbiota structure and metabolome compositions.

PURPOSE

Sparse evidence is available linking gut microbiota perturbations, diverticular disease pathophysiology, and symptom development. We aimed to summarize the available knowledge on gut microbiota evaluation in diverticular disease, with a focus on symptomatic uncomplicated DD, and the relative treatment strategies.

Metabolomic profiling of preterm birth in pregnant women living with HIV

BACKGROUND

Preterm birth is a leading cause of death in children under the age of five. The risk of preterm birth is increased by maternal HIV infection as well as by certain antiretroviral regimens, leading to a disproportionate burden on low- and medium-income settings where HIV is most prevalent. Despite decades of research, the mechanisms underlying spontaneous preterm birth, particularly in resource limited areas with high HIV infection rates, are still poorly understood and accurate prediction and therapeutic intervention remain elusive.

OBJECTIVES

Metabolomics was utilized to identify profiles of preterm birth among pregnant women living with HIV on two different antiretroviral therapy (ART) regimens.

METHODS

This pilot study comprised 100 mother-infant dyads prior to antiretroviral initiation, on zidovudine monotherapy or on protease inhibitor-based antiretroviral therapy. Pregnancies that resulted in preterm births were matched 1:1 with controls by gestational age at time of sample collection. Maternal plasma and blood spots at 23-35 weeks gestation and infant dried blood spots at birth, were assayed using an untargeted metabolomics method. Linear regression and random forests classification models were used to identify shared and treatment-specific markers of preterm birth.

RESULTS

Classification models for preterm birth achieved accuracies of 95.5%, 95.7%, and 80.7% in the untreated, zidovudine monotherapy, and protease inhibitor-based treatment groups, respectively. Urate, methionine sulfone, cortisone, and 17α-hydroxypregnanolone glucuronide were identified as shared markers of preterm birth. Other compounds including hippurate and N-acetyl-1-methylhistidine were found to be significantly altered in a treatment-specific context.

CONCLUSION

This study identified previously known as well as novel metabolomic features of preterm birth in pregnant women living with HIV. Validation of these models in a larger, independent cohort is necessary to ascertain whether they can be utilized to predict preterm birth during a stage of gestation that allows for therapeutic intervention or more effective resource allocation.

From the perspective of rumen microbiome and host metabolome, revealing the effects of feeding strategies on Jersey Cows on the Tibetan Plateau

Background

Previous studies have discussed the effects of grazing and house feeding on yaks during the cold season when forage is in short supply, but there is limited information on the effects of these feeding strategies on Jersey cows introduced to the Tibetan Plateau. The objective of this study was to use genomics and metabolomics analyses to examine changes in rumen microbiology and organism metabolism of Jersey cows with different feeding strategies.

Methods

We selected 12 Jersey cows with similar body conditions and kept them for 60 days under grazing (n = 6) and house-feeding (n = 6) conditions. At the end of the experiment, samples of rumen fluid and serum were collected from Jersey cows that had been fed using different feeding strategies. The samples were analyzed for rumen fermentation parameters, rumen bacterial communities, serum antioxidant and immunological indices, and serum metabolomics. The results of the study were examined to find appropriate feeding strategies for Jersey cows during the cold season on the Tibetan plateau.

Results

The results of rumen fermentation parameters showed that concentrations of acetic acid, propionic acid, and ammonia nitrogen in the house-feeding group (Group B) were significantly higher than in the grazing group (Group G) (P < 0.05). In terms of the rumen bacterial community 16S rRNA gene, the Chao1 index was significantly higher in Group G than in Group B (P = 0.038), while observed species, Shannon and Simpson indices were not significantly different from the above-mentioned groups (P > 0.05). Beta diversity analysis revealed no significant differences in the composition of the rumen microbiota between the two groups. Analysis of serum antioxidant and immune indices showed no significant differences in total antioxidant capacity between Group G and Group B (P > 0.05), while IL-6, Ig-M , and TNF-α were significantly higher in Group G than in Group B (P < 0.05). LC-MS metabolomics analysis of serum showed that a total of 149 major serum differential metabolites were found in Group G and Group B. The differential metabolites were enriched in the metabolic pathways of biosynthesis of amino acids, protein digestion and absorption, ABC transporters, aminoacyl-tRNA biosynthesis, mineral absorption, and biosynthesis of unsaturated fatty acids. These data suggest that the house-feeding strategy is more beneficial to improve the physiological state of Jersey cows on the Tibetan Plateau during the cold season when forages are in short supply.

IBS randomized study: FODMAPs alter bile acids, phenolic- and tryptophan metabolites, while gluten modifies lipids

Diet is considered a culprit for symptoms in irritable bowel syndrome (IBS), although the mechanistic understanding of underlying causes is lacking. Metabolomics, i.e., the analysis of metabolites in biological samples may offer a diet-responsive fingerprint for IBS. Our aim was to explore alterations in the plasma metabolome after interventions with fermentable oligosaccharides, disaccharides, monosaccharides, and polyols (FODMAPs) or gluten versus control in IBS, and to relate such alterations to symptoms. People with IBS (n = 110) were included in a double-blind, randomized, crossover study with 1-wk provocations of FODMAPs, gluten, or placebo. Symptoms were evaluated with the IBS severity scoring system (IBS-SSS). Untargeted metabolomics was performed on plasma samples using LC-qTOF-MS. Discovery of metabolite alterations by treatment was performed using random forest followed by linear mixed modeling. Associations were studied using Spearman correlation. The metabolome was affected by FODMAP [classification rate (CR) 0.88, P < 0.0001], but less by gluten intake CR 0.72, P = 0.01). FODMAP lowered bile acids, whereas phenolic-derived metabolites and 3-indolepropionic acid (IPA) were higher compared with placebo. IPA and some unidentified metabolites correlated weakly to abdominal pain and quality of life. Gluten affected lipid metabolism weakly, but with no interpretable relationship to IBS. FODMAP affected gut microbial-derived metabolites relating to positive health outcomes. IPA and unknown metabolites correlated weakly to IBS severity. Minor symptom worsening by FODMAP intake must be weighed against general positive health aspects of FODMAP. The gluten intervention affected lipid metabolism weakly with no interpretable association to IBS severity. Registration: www.clinicaltrials.gov as NCT03653689.NEW & NOTEWORTHY In irritable bowel syndrome (IBS), fermentable oligo-, di-, monosaccharides, and polyols (FODMAPs) affected microbial-derived metabolites relating to positive health outcomes such as reduced risk of colon cancer, inflammation, and type 2 diabetes, as shown in previous studies. The minor IBS symptom induction by FODMAP intake must be weighed against the positive health aspects of FODMAP consumption. Gluten affected lipids weakly with no association to IBS severity.

Circulating metabolites modulated by diet are associated with depression

Metabolome reflects the interplay of genome and exposome at molecular level and thus can provide deep insights into the pathogenesis of a complex disease like major depression. To identify metabolites associated with depression we performed a metabolome-wide association analysis in 13,596 participants from five European population-based cohorts characterized for depression, and circulating metabolites using ultra high-performance liquid chromatography/tandem accurate mass spectrometry (UHPLC/MS/MS) based Metabolon platform. We tested 806 metabolites covering a wide range of biochemical processes including those involved in lipid, amino-acid, energy, carbohydrate, xenobiotic and vitamin metabolism for their association with depression. In a conservative model adjusting for life style factors and cardiovascular and antidepressant medication use we identified 8 metabolites, including 6 novel, significantly associated with depression. In individuals with depression, increased levels of retinol (vitamin A), 1-palmitoyl-2-palmitoleoyl-GPC (16:0/16:1) (lecithin) and mannitol/sorbitol and lower levels of hippurate, 4-hydroxycoumarin, 2-aminooctanoate (alpha-aminocaprylic acid), 10-undecenoate (11:1n1) (undecylenic acid), 1-linoleoyl-GPA (18:2) (lysophosphatidic acid; LPA 18:2) are observed. These metabolites are either directly food derived or are products of host and gut microbial metabolism of food-derived products. Our Mendelian randomization analysis suggests that low hippurate levels may be in the causal pathway leading towards depression. Our findings highlight putative actionable targets for depression prevention that are easily modifiable through diet interventions.

Faecal and urine metabolites, but not gut microbiota, may predict response to low FODMAP diet in irritable bowel syndrome

BACKGROUND

The low FODMAP diet (LFD) leads to clinical response in 50%-80% of patients with irritable bowel syndrome (IBS). It is unclear why only some patients respond.

AIMS

To determine if differences in baseline faecal microbiota or faecal and urine metabolite profiles may separate clinical responders to the diet from non-responders allowing predictive algorithms to be proposed.

METHODS

We recruited adults fulfilling Rome III criteria for IBS to a blinded randomised controlled trial. Patients were randomised to sham diet with a placebo supplement (control) or LFD supplemented with either placebo (LFD) or 1.8 g/d B-galactooligosaccharide (LFD/B-GOS), for 4 weeks. Clinical response was defined as adequate symptom relief at 4 weeks after the intervention (global symptom question). Differences between responders and non-responders in faecal microbiota (FISH, 16S rRNA sequencing) and faecal (gas-liquid chromatography, gas-chromatography mass-spectrometry) and urine (1 H NMR) metabolites were analysed.

RESULTS

At 4 weeks, clinical response differed across the 3groups with adequate symptom relief of 30% (7/23) in controls, 50% (11/22) in the LFD group and 67% (16/24) in the LFD/B-GOS group (p = 0.048). In the control and the LFD/B-GOS groups, microbiota and metabolites did not separate responders from non-responders. In the LFD group, higher baseline faecal propionate (sensitivity 91%, specificity 89%) and cyclohexanecarboxylic acid esters (sensitivity 80%, specificity 78%), and urine metabolite profile (Q2 0.296 vs. randomised -0.175) predicted clinical response.

CONCLUSIONS

Baseline faecal and urine metabolites may predict response to the LFD.

Tissue-specific reprogramming of glutamine metabolism maintains tolerance to sepsis

Reprogramming metabolism is of great therapeutic interest for reducing morbidity and mortality during sepsis-induced critical illness. Disappointing results from randomized controlled trials targeting glutamine and antioxidant metabolism in patients with sepsis have begged a deeper understanding of the tissue-specific metabolic response to sepsis. The current study sought to fill this gap. We analyzed skeletal muscle transcriptomics of critically ill patients, versus elective surgical controls, which revealed reduced expression of genes involved in mitochondrial metabolism and electron transport, with increases in glutathione cycling, glutamine, branched chain, and aromatic amino acid transport. We then performed untargeted metabolomics and 13C isotope tracing to analyze systemic and tissue specific metabolic phenotyping in a murine polymicrobial sepsis model. We found an increased number of correlations between the metabolomes of liver, kidney, and spleen, with loss of correlations between the heart and quadriceps and all other organs, pointing to a shared metabolic signature within vital abdominal organs, and unique metabolic signatures for muscles during sepsis. A lowered GSH:GSSG and elevated AMP:ATP ratio in the liver underlie the significant upregulation of isotopically labeled glutamine's contribution to TCA cycle anaplerosis and glutamine-derived glutathione biosynthesis; meanwhile, the skeletal muscle and spleen were the only organs where glutamine's contribution to the TCA cycle was significantly suppressed. These results highlight tissue-specific mitochondrial reprogramming to support liver energetic demands and antioxidant synthesis, rather than global mitochondrial dysfunction, as a metabolic consequence of sepsis.

Strain dropouts reveal interactions that govern the metabolic output of the gut microbiome

The gut microbiome is complex, raising questions about the role of individual strains in the community. Here, we address this question by constructing variants of a complex defined community in which we eliminate strains that occupy the bile acid 7α-dehydroxylation niche. Omitting Clostridium scindens (Cs) and Clostridium hylemonae (Ch) eliminates secondary bile acid production and reshapes the community in a highly specific manner: eight strains change in relative abundance by >100-fold. In single-strain dropout communities, Cs and Ch reach the same relative abundance and dehydroxylate bile acids to a similar extent. However, Clostridium sporogenes increases >1,000-fold in the ΔCs but not ΔCh dropout, reshaping the pool of microbiome-derived phenylalanine metabolites. Thus, strains that are functionally redundant within a niche can have widely varying impacts outside the niche, and a strain swap can ripple through the community in an unpredictable manner, resulting in a large impact on an unrelated community-level phenotype.

Investigating the Urinary Metabolome in the First Year of Life and Its Association with Later Diagnosis of Autism Spectrum Disorder or Non-Typical Neurodevelopment in the MARBLES Study

Developmental disabilities are often associated with alterations in metabolism. However, it remains unknown how early these metabolic issues may arise. This study included a subset of children from the Markers of Autism Risks in Babies-Learning Early Signs (MARBLES) prospective cohort study. In this analysis, 109 urine samples collected at 3, 6, and/or 12 months of age from 70 children with a family history of ASD who went on to develop autism spectrum disorder (ASD n = 17), non-typical development (Non-TD n = 11), or typical development (TD n = 42) were investigated by nuclear magnetic resonance (NMR) spectroscopy to measure urinary metabolites. Multivariate principal component analysis and a generalized estimating equation were performed with the objective of exploring the associations between urinary metabolite levels in the first year of life and later adverse neurodevelopment. We found that children who were later diagnosed with ASD tended to have decreased urinary dimethylamine, guanidoacetate, hippurate, and serine, while children who were later diagnosed with Non-TD tended to have elevated urinary ethanolamine and hypoxanthine but lower methionine and homovanillate. Children later diagnosed with ASD or Non-TD both tended to have decreased urinary 3-aminoisobutyrate. Our results suggest subtle alterations in one-carbon metabolism, gut-microbial co-metabolism, and neurotransmitter precursors observed in the first year of life may be associated with later adverse neurodevelopment.

Whole Body Distribution of Labile Coenzymes and Antioxidants in a Mouse Model as Visualized Using 1H NMR Spectroscopy

Coenzyme A, acetyl coenzyme A, coenzymes of cellular energy, coenzymes of redox reactions, and antioxidants mediate biochemical reactions fundamental to the functioning of all living cells. There is an immense interest in measuring them routinely in biological specimens to gain insights into their roles in cellular functions and to help characterize the biological status. However, it is challenging to measure them ex vivo as they are sensitive to specimen harvesting, extraction, and measurement conditions. This challenge is largely underappreciated and carries the risk of grossly inaccurate measurements that lead to incorrect inferences. To date, several efforts have been focused on alleviating this challenge using NMR spectroscopy. However, a comprehensive solution for the measurement of the compounds in a wide variety of biological specimens is still lacking. As a part of addressing this challenge, we demonstrate here that the total pool of each group of unstable metabolites offers a starting place for the representation of labile metabolites in biological specimens. Based on this approach, in this proof-of-concept study, we determine the distribution of the labile compounds in different organs including heart, kidney, liver, brain, and skeletal muscle of a mouse model. The results were independently validated using different specimens and a different metabolite extraction protocol. Further, we show that both stable and unstable metabolites were distributed differentially in different organs, which signifies their differential functional roles, the knowledge of which is currently lacking for many metabolites. Intriguingly, the concentration of taurine, an amino sulfonic acid, in skeletal muscle is >30 mM, which is the highest for any metabolite in a mammalian tissue known to date. To the best of our knowledge, this is the first study to profile the whole body distribution of the labile and other high-concentration metabolites using NMR spectroscopy. The results may pave ways for gaining new insights into cellular functions in health and diseases.

Gut microbiota disturbances and protein-energy wasting in chronic kidney disease: a narrative review

Protein-energy wasting (PEW) is common in patients with chronic kidney disease (CKD) and is associated with increased morbidity and mortality, and lower quality of life. It is a complex syndrome, in which inflammation and retention of uremic toxins are two main factors. Causes of inflammation and uremic toxin retention in CKD are multiple; however, gut dysbiosis plays an important role, serving as a link between those entities and PEW. Besides, there are several pathways by which microbiota may influence PEW, e.g., through effects on appetite mediated by microbiota-derived proteins and hormonal changes, or by impacting skeletal muscle via a gut-muscle axis. Hence, microbiota disturbances may influence PEW independently of its relationship with local and systemic inflammation. A better understanding of the complex interrelationships between microbiota and the host may help to explain how changes in the gut affect distant organs and systems of the body and could potentially lead to the development of new strategies targeting the microbiota to improve nutrition and clinical outcomes in CKD patients. In this review, we describe possible interactions of gut microbiota with nutrient metabolism, energy balance, hunger/satiety signals and muscle depletion, all of which are strongly related to PEW in CKD patients.

Canagliflozin protects the cardiovascular system through effects on the gut environment in non-diabetic nephrectomized rats

BACKGROUND

The gut produces toxins that contribute to the cardiovascular complications of chronic kidney disease. Canagliflozin, a sodium glucose cotransporter (SGLT) 2 inhibitor that is used as an anti-diabetic drug, has a weak inhibitory effect against SGLT1 and may affect the gut glucose concentration and environment.

METHODS

Here, we determined the effect of canagliflozin on the gut microbiota and the serum gut-derived uremic toxin concentrations in 5/6th nephrectomized (Nx) rats.

RESULTS

Canagliflozin increased the colonic glucose concentration and restored the number of Lactobacillus bacteria, which was low in Nx rats. In addition, the expression of tight junction proteins in the ascending colon was low in Nx rats, and this was partially restored by canagliflozin. Furthermore, the serum concentrations of gut-derived uremic toxins were significantly increased by Nx and reduced by canagliflozin. Finally, the wall of the thoracic aorta was thicker and there was more cardiac interstitial fibrosis in Nx rats, and these defects were ameliorated by canagliflozin.

CONCLUSIONS

The increases in colonic glucose concentration, Lactobacillus numbers and tight junction protein expression, and the decreases in serum uremic toxin concentrations and cardiac interstitial fibrosis may have been caused by the inhibition of SGLT1 by canagliflozin because similar effects were not identified in tofogliflozin-treated rats.

Metabolic and Transcriptomic Changes in the Mouse Brain in Response to Short-Term High-Fat Metabolic Stress

The chronic consumption of diets rich in saturated fats leads to obesity and associated metabolic disorders including diabetes and atherosclerosis. Intake of a high-fat diet (HFD) is also recognized to dysregulate neural functions such as cognition, mood, and behavior. However, the effects of short-term high-fat diets on the brain are elusive. Here, we investigated molecular changes in the mouse brain following an acute HFD for 10 days by employing RNA sequencing and metabolomics profiling. Aberrant expressions of 92 genes were detected in the brain tissues of acute HFD-exposed mice. The differentially expressed genes were enriched for various pathways and processes such as superoxide metabolism. In our global metabolomic profiling, a total of 59 metabolites were significantly altered by the acute HFD. Metabolic pathways upregulated from HFD-exposed brain tissues relative to control samples included oxidative stress, oxidized polyunsaturated fatty acids, amino acid metabolism (e.g., branched-chain amino acid catabolism, and lysine metabolism), and the gut microbiome. Acute HFD also elevated levels of N-acetylated amino acids, urea cycle metabolites, and uracil metabolites, further suggesting complex changes in nitrogen metabolism. The observed molecular events in the present study provide a valuable resource that can help us better understand how acute HFD stress impacts brain homeostasis.

Controlling the confounding effect of metabolic gene expression to identify actual metabolite targets in microsatellite instability cancers

BACKGROUND

The metabolome is the best representation of cancer phenotypes. Gene expression can be considered a confounding covariate affecting metabolite levels. Data integration across metabolomics and genomics to establish the biological relevance of cancer metabolism is challenging. This study aimed to eliminate the confounding effect of metabolic gene expression to reflect actual metabolite levels in microsatellite instability (MSI) cancers.

METHODS

In this study, we propose a new strategy using covariate-adjusted tensor classification in high dimensions (CATCH) models to integrate metabolite and metabolic gene expression data to classify MSI and microsatellite stability (MSS) cancers. We used datasets from the Cancer Cell Line Encyclopedia (CCLE) phase II project and treated metabolomic data as tensor predictors and data on gene expression of metabolic enzymes as confounding covariates.

RESULTS

The CATCH model performed well, with high accuracy (0.82), sensitivity (0.66), specificity (0.88), precision (0.65), and F1 score (0.65). Seven metabolite features adjusted for metabolic gene expression, namely, 3-phosphoglycerate, 6-phosphogluconate, cholesterol ester, lysophosphatidylethanolamine (LPE), phosphatidylcholine, reduced glutathione, and sarcosine, were found in MSI cancers. Only one metabolite, Hippurate, was present in MSS cancers. The gene expression of phosphofructokinase 1 (PFKP), which is involved in the glycolytic pathway, was related to 3-phosphoglycerate. ALDH4A1 and GPT2 were associated with sarcosine. LPE was associated with the expression of CHPT1, which is involved in lipid metabolism. The glycolysis, nucleotide, glutamate, and lipid metabolic pathways were enriched in MSI cancers.

CONCLUSIONS

We propose an effective CATCH model for predicting MSI cancer status. By controlling the confounding effect of metabolic gene expression, we identified cancer metabolic biomarkers and therapeutic targets. In addition, we provided the possible biology and genetics of MSI cancer metabolism.

Sex Differences in Fatty Acid Metabolism and Blood Pressure Response to Dietary Salt in Humans

Salt sensitivity is a trait in which high dietary sodium (Na+) intake causes an increase in blood pressure (BP). We previously demonstrated that in the gut, elevated dietary Na+ causes dysbiosis. The mechanistic interplay between excess dietary Na+-induced alteration in the gut microbiome and sex differences is less understood. The goal of this study was to identify novel metabolites in sex differences and blood pressure in response to a high dietary Na+ intake. We performed stool and plasma metabolomics analysis and measured the BP of human volunteers with salt intake above or below the American Heart Association recommendations. We also performed RNA sequencing on human monocytes treated with high salt in vitro. The relationship between BP and dietary Na+ intake was different in women and men. Network analysis revealed that fatty acids as top subnetworks differentially changed with salt intake. We found that women with high dietary Na+ intake have high levels of arachidonic acid related metabolism, suggesting a role in sex differences of the blood pressure response to Na+. The exposure of monocytes to high salt in vitro upregulates the transcription of fatty acid receptors and arachidonic acid-related genes. These findings provide potentially novel insights into metabolic changes underlying gut dysbiosis and inflammation in salt sensitivity of BP.

Urinary Metabolic Profiling of Liver Fluke-Induced Cholangiocarcinoma-A Follow-Up Study

Background/Aims

Global liquid chromatography mass spectrometry (LC-MS) profiling in a Thai population has previously identified a urinary metabolic signature in Opisthorchis viverrini-induced cholangiocarcinoma (CCA), primarily characterised by disturbance in acylcarnitine, bile acid, steroid, and purine metabolism. However, the detection of thousands of analytes by LC-MS in a biological sample in a single experiment potentially introduces false discovery errors. To verify these observed metabolic perturbations, a second validation dataset from the same population was profiled in a similar fashion.

Methods

Reverse-phase ultra-performance liquid-chromatography mass spectrometry was utilised to acquire the global spectral profile of 98 spot urine samples (from 46 healthy volunteers and 52 CCA patients) recruited from Khon Kaen, northeast Thailand (the highest incidence of CCA globally).

Results

Metabolites were differentially expressed in the urinary profiles from CCA patients. High urinary elimination of bile acids was affected by the presence of obstructive jaundice. The urine metabolome associated with non-jaundiced CCA patients showed a distinctive pattern, similar but not identical to published studies. A panel of 10 metabolites achieved a diagnostic accuracy of 93.4% and area under the curve value of 98.8% (CI = 96.3%-100%) for the presence of CCA.

Conclusions

Global characterisation of the CCA urinary metabolome identified several metabolites of biological interest in this validation study. Analyses of the diagnostic utility of the discriminant metabolites showed excellent diagnostic potential. Further larger scale studies are required to confirm these findings internationally, particularly in comparison to sporadic CCA, not associated with liver fluke infestation.

Changes in the Urine Metabolomic Profile in Patients Recovering from Severe COVID-19

Metabolomics is a relatively new research area that focuses mostly on the profiling of selected molecules and metabolites within the organism. A SARS-CoV-2 infection itself can lead to major disturbances in the metabolite profile of the infected individuals. The aim of this study was to analyze metabolomic changes in the urine of patients during the acute phase of COVID-19 and approximately one month after infection in the recovery period. We discuss the observed changes in relation to the alterations resulting from changes in the blood plasma metabolome, as described in our previous study. The metabolome analysis was performed using NMR spectroscopy from the urine of patients and controls. The urine samples were collected at three timepoints, namely upon hospital admission, during hospitalization, and after discharge from the hospital. The acute COVID-19 phase induced massive alterations in the metabolic composition of urine was linked with various changes taking place in the organism. Discriminatory analyses showed the feasibility of successful discrimination of COVID-19 patients from healthy controls based on urinary metabolite levels, with the highest significance assigned to citrate, Hippurate, and pyruvate. Our results show that the metabolomic changes persist one month after the acute phase and that the organism is not fully recovered.

Disentangling the Complexity of Nutrition, Frailty and Gut Microbial Pathways during Aging: A Focus on Hippuric Acid

Hippuric acid (HA) is a metabolite resulting from the hepatic glycine conjugation of benzoic acid (BA) or from the gut bacterial metabolism of phenylalanine. BA is generally produced by gut microbial metabolic pathways after the ingestion of foods of vegetal origin rich in polyphenolic compounds, namely, chlorogenic acids or epicatechins. It can also be present in foods, either naturally or artificially added as a preservative. The plasma and urine HA levels have been used in nutritional research for estimating the habitual fruit and vegetable intake, especially in children and in patients with metabolic diseases. HA has also been proposed as a biomarker of aging, since its levels in the plasma and urine can be influenced by the presence of several age-related conditions, including frailty, sarcopenia and cognitive impairment. Subjects with physical frailty generally exhibit reduced plasma and urine levels of HA, despite the fact that HA excretion tends to increase with aging. Conversely, subjects with chronic kidney disease exhibit reduced HA clearance, with HA retention that may exert toxic effects on the circulation, brain and kidneys. With regard to older patients with frailty and multimorbidity, interpreting the HA levels in the plasma and urine may result particularly challenging because HA is at the crossroads between diet, gut microbiota, liver and kidney function. Although these considerations may not make HA the ideal biomarker of aging trajectories, the study of its metabolism and clearance in older subjects may provide valuable information for disentangling the complex interaction between diet, gut microbiota, frailty and multimorbidity.

Robust performance of a live bacterial therapeutic chassis lacking the colibactin gene cluster

E. coli Nissle (EcN) is a non-pathogenic probiotic bacterium of the Enterobacteriaceae family that has been used for over a century to promote general gut health. Despite the history of safe usage of EcN, concerns have been raised regarding the presence of the pks gene cluster, encoding the genotoxin colibactin, due to its association with colorectal cancer. Here, we sought to determine the effect of pks island removal on the in vitro and in vivo robustness and activity of EcN and EcN-derived strains. A deletion of the pks island (Δpks) was constructed in wild type and engineered strains of EcN using lambda red recombineering. Mass spectrometric measurement of N-myristoyl-D-asparagine, released during colibactin maturation, confirmed that the pks deletion abrogated colibactin production. Growth curves were comparable between Δpks strains and their isogenic parents, and wild type EcN displayed no competitive advantage to the Δpks strain in mixed culture. Deletion of pks also had no effect on the activity of strains engineered to degrade phenylalanine (SYNB1618 and SYNB1934) or oxalate (SYNB8802). Furthermore, 1:1 mixed dosing of wild type and Δpks EcN in preclinical mouse and nonhuman primate models demonstrated no competitive disadvantage for the Δpks strain with regards to transit time or colonization. Importantly, there was no significant difference on in vivo strain performance between the clinical-stage strain SYNB1934 and its isogenic Δpks variant with regards to recovery of the quantitative strain-specific biomarkers d5- trans-cinnamic acid, and d5-hippuric acid. Taken together, these data support that the pks island is dispensable for Synthetic Biotic fitness and activity in vivo and that its removal from engineered strains of EcN will not have a deleterious effect on strain efficacy.

Measuring the intake of dietary bioactives: Pitfalls and how to avoid them

Bioactives are food constituents that, while not essential to human life, can affect health. Thus, there is increased interest in developing dietary recommendations for bioactives. Such recommendations require detailed information about the long-term association between habitual intake and health at population scale, and these can only be provided by large-scale observational studies. Nutritional epidemiology relies on the accurate estimation of intake, but currently used methods, commonly based on a 2-step process involving self-reports and food composition tables, are fraught with significant challenges and are unable to estimate the systemic presence of bioactives. Intake assessments based on nutritional biomarkers can provide an advanced alternative, but there are a number of pitfalls that need to be addressed in order to obtain reliable data on intake. Using flavan-3-ols as a case study, we highlight here key challenges and how they may be avoided. Taken together, we believe that the approaches outlined in this review can be applied to a wide range of food constituents, and doing so will improve assessments of the dietary intake of bioactives.

Food-Derived Uremic Toxins in Chronic Kidney Disease

Patients with chronic kidney disease (CKD) have a higher cardiovascular risk compared to the average population, and this is partially due to the plasma accumulation of solutes known as uremic toxins. The binding of some solutes to plasma proteins complicates their removal via conventional therapies, e.g., hemodialysis. Protein-bound uremic toxins originate either from endogenous production, diet, microbial metabolism, or the environment. Although the impact of diet on uremic toxicity in CKD is difficult to quantify, nutrient intake plays an important role. Indeed, most uremic toxins are gut-derived compounds. They include Maillard reaction products, hippurates, indoles, phenols, and polyamines, among others. In this review, we summarize the findings concerning foods and dietary components as sources of uremic toxins or their precursors. We then discuss their endogenous metabolism via human enzyme reactions or gut microbial fermentation. Lastly, we present potential dietary strategies found to be efficacious or promising in lowering uremic toxins plasma levels. Aligned with current nutritional guidelines for CKD, a low-protein diet with increased fiber consumption and limited processed foods seems to be an effective treatment against uremic toxins accumulation.

Host-microbe co-metabolism via MCAD generates circulating metabolites including hippuric acid

The human gut microbiota produces dozens of small molecules that circulate in blood, accumulate to comparable levels as pharmaceutical drugs, and influence host physiology. Despite the importance of these metabolites to human health and disease, the origin of most microbially-produced molecules and their fate in the host remains largely unknown. Here, we uncover a host-microbe co-metabolic pathway for generation of hippuric acid, one of the most abundant organic acids in mammalian urine. Combining stable isotope tracing with bacterial and host genetics, we demonstrate reduction of phenylalanine to phenylpropionic acid by gut bacteria; the host re-oxidizes phenylpropionic acid involving medium-chain acyl-CoA dehydrogenase (MCAD). Generation of germ-free male and female MCAD-/- mice enabled gnotobiotic colonization combined with untargeted metabolomics to identify additional microbial metabolites processed by MCAD in host circulation. Our findings uncover a host-microbe pathway for the abundant, non-toxic phenylalanine metabolite hippurate and identify β-oxidation via MCAD as a novel mechanism by which mammals metabolize microbiota-derived metabolites.

Acute effects of moderate vs. vigorous endurance exercise on urinary metabolites in healthy, young, physically active men-A multi-platform metabolomics approach

Introduction: Endurance exercise alters whole-body as well as skeletal muscle metabolism and physiology, leading to improvements in performance and health. However, biological mechanisms underlying the body's adaptations to different endurance exercise protocols are not entirely understood. Methods: We applied a multi-platform metabolomics approach to identify urinary metabolites and associated metabolic pathways that distinguish the acute metabolic response to two endurance exercise interventions at distinct intensities. In our randomized crossover study, 16 healthy, young, and physically active men performed 30 min of continuous moderate exercise (CME) and continuous vigorous exercise (CVE). Urine was collected during three post-exercise sampling phases (U01/U02/U03: until 45/105/195 min post-exercise), providing detailed temporal information on the response of the urinary metabolome to CME and CVE. Also, fasting spot urine samples were collected pre-exercise (U00) and on the following day (U04). While untargeted two-dimensional gas chromatography-mass spectrometry (GC×GC-MS) led to the detection of 608 spectral features, 44 metabolites were identified and quantified by targeted nuclear magnetic resonance (NMR) spectroscopy or liquid chromatography-mass spectrometry (LC-MS). Results: 104 urinary metabolites showed at least one significant difference for selected comparisons of sampling time points within or between exercise trials as well as a relevant median fold change >1.5 or <0. 6 ¯ (NMR, LC-MS) or >2.0 or <0.5 (GC×GC-MS), being classified as either exercise-responsive or intensity-dependent. Our findings indicate that CVE induced more profound alterations in the urinary metabolome than CME, especially at U01, returning to baseline within 24 h after U00. Most differences between exercise trials are likely to reflect higher energy requirements during CVE, as demonstrated by greater shifts in metabolites related to glycolysis (e.g., lactate, pyruvate), tricarboxylic acid cycle (e.g., cis-aconitate, malate), purine nucleotide breakdown (e.g., hypoxanthine), and amino acid mobilization (e.g., alanine) or degradation (e.g., 4-hydroxyphenylacetate). Discussion: To conclude, this study provided first evidence of specific urinary metabolites as potential metabolic markers of endurance exercise intensity. Future studies are needed to validate our results and to examine whether acute metabolite changes in urine might also be partly reflective of mechanisms underlying the health- or performance-enhancing effects of endurance exercise, particularly if performed at high intensities.

Derivatization of N-Acyl Glycines by 3-Nitrophenylhydrazine for Targeted Metabolomics Analysis and Their Application to the Study of Diabetes Progression in Mice

N-Acyl glycines (NAGlys) are an important class of metabolites in the detoxification system of the human body. They have been used in the diagnosis of several metabolic diseases. Liquid chromatography-mass spectrometry (LC-MS) is the most frequently used NAGlys detection platform. Here, we describe a simple and sensitive method of NAGlys detection by LC-MS in plasma and urine samples. This approach is based on the use of a derivatization reagent, 3-nitrophenylhydrazine. The reaction is quick in aqueous solution, and no quenching step is needed. To expand the coverage of NAGlys when standards are not available, NAGlys were first identified based on high-resolution LC-MS. Quantification was subsequently carried out on triple quadrupole LC-MS. This approach allowed a much broader measurement of NAGlys (41 NAGlys in total), especially when authentic standards are unavailable. Comprehensive analysis of NAGlys with this new method was applied in plasma and urine samples of db/db diabetic and non-diabetic db/m+ control mice. The majority of detected NAGlys were altered with high differentiation ability in plasma and urine samples from diabetic and non-diabetic mice. These identified NAGlys hold the potential to be diagnostic biomarkers for type II diabetes and diabetic complications.

Machine learning model for predicting age in healthy individuals using age-related gut microbes and urine metabolites

Age-related gut microbes and urine metabolites were investigated in 568 healthy individuals using metataxonomics and metabolomics. The richness and evenness of the fecal microbiota significantly increased with age, and the abundance of 16 genera differed between the young and old groups. Additionally, 17 urine metabolites contributed to the differences between the young and old groups. Among the microbes that differed by age, Bacteroides and Prevotella 9 were confirmed to be correlated with some urine metabolites. The machine learning algorithm eXtreme gradient boosting (XGBoost) was shown to produce the best performing age predictors, with a mean absolute error of 5.48 years. The accuracy of the model improved to 4.93 years with the inclusion of urine metabolite data. This study shows that the gut microbiota and urine metabolic profiles can be used to predict the age of healthy individuals with relatively good accuracy.

Comparison of metabolites in rumen fluid, urine, and feces of dairy cow from subacute ruminal acidosis model measured by proton nuclear magnetic resonance spectroscopy

OBJECTIVE

In this study, metabolites that changed in the rumen fluid, urine and feces of dairy cows fed different feed ratios were investigated.

METHODS

Eight Holstein cows were used in this study. Rumen fluid, urine, and feces were collected from the normal concentrate diet (NCD) (Italian ryegrass 80%: concentrate 20% in the total feed) and high concentrate diet (HCD) groups (20%: 80%) of dairy cows. Metabolite analysis was performed using proton nuclear magnetic resonance (NMR) identification, and statistical analysis was performed using Chenomx NMR software 8.4 and Metaboanalyst 4.0.

RESULTS

The two groups of rumen fluid and urine samples were separated, and samples from the same group were aggregated together. On the other hand, the feces samples were not separated and showed similar tendencies between the two groups. In total, 160, 177, and 188 metabolites were identified in the rumen fluid, urine, and feces, respectively. The differential metabolites with low and high concentrations were 15 and 49, 14 and 16, and 2 and 2 in the rumen fluid, urine, and feces samples, in the NCD group.

CONCLUSION

As HCD is related to rumen microbial changes, research on different metabolites such as glucuronate, acetylsalicylate, histidine, and O-Acetylcarnitine, which are related to bacterial degradation and metabolism, will need to be carried out in future studies along with microbial analysis. In urine, the identified metabolites, such as gallate, syringate, and vanillate can provide insight into microbial, metabolic, and feed parameters that cause changes depending on the feed rate. Additionally, it is thought that they can be used as potential biomarkers for further research on subacute ruminal acidosis.

Effect of Acylated and Nonacylated Anthocyanins on Urine Metabolic Profile during the Development of Type 2 Diabetes in Zucker Diabetic Fatty Rats

The effect of nonacylated and acylated anthocyanins on urinary metabolites in diabetic rats was investigated. Nonacylated anthocyanins extract from bilberries (NAAB) or acylated anthocyanins extract from purple potatoes (AAPP) was given to Zucker diabetic fatty (ZDF) rats for 8 weeks at daily doses of 25 and 50 mg/kg body weight. ¹H NMR metabolomics was applied to study alterations in urinary metabolites from three time points (weeks 1, 4, and 8). Both types of anthocyanins modulated the metabolites associated with the tricarboxylic acid cycle, gut microbiota metabolism, and renal function at weeks 1 and 4, such as 2-oxoglutarate, fumarate, alanine, trigonelline, and hippurate. In addition, only a high dose of AAPP decreased monosaccharides, formate, lactate, and glucose levels at week 4, suggesting improvement in energy production in mitochondria, glucose homeostasis, and oxidative stress. This study suggested different impacts of AAPP and NAAB on the metabolic profile of urine in diabetes.

Dietary restriction and medical therapy drives PPARα-regulated improvements in early diabetic kidney disease in male rats

The attenuation of diabetic kidney disease (DKD) by metabolic surgery is enhanced by pharmacotherapy promoting renal fatty acid oxidation (FAO). Using the Zucker Diabetic Fatty and Zucker Diabetic Sprague Dawley rat models of DKD, we conducted studies to determine if these effects could be replicated with a non-invasive bariatric mimetic intervention. Metabolic control and renal injury were compared in rats undergoing a dietary restriction plus medical therapy protocol (DMT; fenofibrate, liraglutide, metformin, ramipril, and rosuvastatin) and ad libitum-fed controls. The global renal cortical transcriptome and urinary 1H-NMR metabolomic profiles were also compared. Kidney cell type-specific and medication-specific transcriptomic responses were explored through in silico deconvolution. Transcriptomic and metabolomic correlates of improvements in kidney structure were defined using a molecular morphometric approach. The DMT protocol led to ∼20% weight loss, normalized metabolic parameters and was associated with reductions in indices of glomerular and proximal tubular injury. The transcriptomic response to DMT was dominated by changes in fenofibrate- and peroxisome proliferator-activated receptor-α (PPARα)-governed peroxisomal and mitochondrial FAO transcripts localizing to the proximal tubule. DMT induced urinary excretion of PPARα-regulated metabolites involved in nicotinamide metabolism and reversed DKD-associated changes in the urinary excretion of tricarboxylic acid (TCA) cycle intermediates. FAO transcripts and urinary nicotinamide and TCA cycle metabolites were moderately to strongly correlated with improvements in glomerular and proximal tubular injury. Weight loss plus pharmacological PPARα agonism is a promising means of attenuating DKD.

Nuclear Magnetic Resonance Metabolomic Profiling and Urine Chemistries in Incident Kidney Stone Formers Compared with Controls

BACKGROUND

The urine metabolites and chemistries that contribute to kidney stone formation are not fully understood. This study examined differences between the urine metabolic and chemistries profiles of first-time stone formers and controls.

METHODS

High-resolution 1H-nuclear magnetic resonance (NMR) spectroscopy-based metabolomic analysis was performed in 24-hour urine samples from a prospective cohort of 418 first-time symptomatic kidney stone formers and 440 controls. In total, 48 NMR-quantified metabolites in addition to 12 standard urine chemistries were assayed. Analysis of covariance was used to determine the association of stone former status with urine metabolites or chemistries after adjusting for age and sex and correcting for the false discovery rate. Gradient-boosted machine methods with nested cross-validation were applied to predict stone former status.

RESULTS

Among the standard urine chemistries, stone formers had lower urine oxalate and potassium and higher urine calcium, phosphate, and creatinine. Among NMR urine metabolites, stone formers had lower hippuric acid, trigonelline, 2-furoylglycine, imidazole, and citrate and higher creatine and alanine. A cross-validated model using urine chemistries, age, and sex yielded a mean AUC of 0.76 (95% CI, 0.73 to 0.79). A cross-validated model using urine chemistries, NMR-quantified metabolites, age, and sex did not meaningfully improve the discrimination (mean AUC, 0.78; 95% CI, 0.75 to 0.81). In this combined model, among the top ten discriminating features, four were urine chemistries and six NMR-quantified metabolites.

CONCLUSIONS

Although NMR-quantified metabolites did not improve discrimination, several urine metabolic profiles were identified that may improve understanding of kidney stone pathogenesis.

Genome-microbiome interplay provides insight into the determinants of the human blood metabolome

Variation in the blood metabolome is intimately related to human health. However, few details are known about the interplay between genetics and the microbiome in explaining this variation on a metabolite-by-metabolite level. Here, we perform analyses of variance for each of 930 blood metabolites robustly detected across a cohort of 1,569 individuals with paired genomic and microbiome data while controlling for a number of relevant covariates. We find that 595 (64%) of these blood metabolites are significantly associated with either host genetics or the gut microbiome, with 69% of these associations driven solely by the microbiome, 15% driven solely by genetics and 16% under hybrid genome-microbiome control. Additionally, interaction effects, where a metabolite-microbe association is specific to a particular genetic background, are quite common, albeit with modest effect sizes. This knowledge will help to guide targeted interventions designed to alter the composition of the human blood metabolome.