Metabolic differences underlying two distinct rat urinary phenotypes, a suggested role for gut microbial metabolism of phenylalanine and a possible connection to autism

Metabolomic changes in children with autism

BACKGROUND

Autism spectrum disorder (ASD) is a neurodevelopmental condition characterized by deficits in social communication and repetitive behaviors. Metabolomic profiling has emerged as a valuable tool for understanding the underlying metabolic dysregulations associated with ASD.

AIM

To comprehensively explore metabolomic changes in children with ASD, integrating findings from various research articles, reviews, systematic reviews, meta-analyses, case reports, editorials, and a book chapter.

METHODS

A systematic search was conducted in electronic databases, including PubMed, PubMed Central, Cochrane Library, Embase, Web of Science, CINAHL, Scopus, LISA, and NLM catalog up until January 2024. Inclusion criteria encompassed research articles (83), review articles (145), meta-analyses (6), systematic reviews (6), case reports (2), editorials (2), and a book chapter (1) related to metabolomic changes in children with ASD. Exclusion criteria were applied to ensure the relevance and quality of included studies.

RESULTS

The systematic review identified specific metabolites and metabolic pathways showing consistent differences in children with ASD compared to typically developing individuals. These metabolic biomarkers may serve as objective measures to support clinical assessments, improve diagnostic accuracy, and inform personalized treatment approaches. Metabolomic profiling also offers insights into the metabolic alterations associated with comorbid conditions commonly observed in individuals with ASD.

CONCLUSION

Integration of metabolomic changes in children with ASD holds promise for enhancing diagnostic accuracy, guiding personalized treatment approaches, monitoring treatment response, and improving outcomes. Further research is needed to validate findings, establish standardized protocols, and overcome technical challenges in metabolomic analysis. By advancing our understanding of metabolic dysregulations in ASD, clinicians can improve the lives of affected individuals and their families.

Cross-Validation of Metabolic Phenotypes in SARS-CoV-2 Infected Subpopulations Using Targeted Liquid Chromatography-Mass Spectrometry (LC-MS)

To ensure biological validity in metabolic phenotyping, findings must be replicated in independent sample sets. Targeted workflows have long been heralded as ideal platforms for such validation due to their robust quantitative capability. We evaluated the capability of liquid chromatography-mass spectrometry (LC-MS) assays targeting organic acids and bile acids to validate metabolic phenotypes of SARS-CoV-2 infection. Two independent sample sets were collected: (1) Australia: plasma, SARS-CoV-2 positive (n = 20), noninfected healthy controls (n = 22) and COVID-19 disease-like symptoms but negative for SARS-CoV-2 infection (n = 22). (2) Spain: serum, SARS-CoV-2 positive (n = 33) and noninfected healthy controls (n = 39). Multivariate modeling using orthogonal projections to latent structures discriminant analyses (OPLS-DA) classified healthy controls from SARS-CoV-2 positive (Australia; R2 = 0.17, ROC-AUC = 1; Spain R2 = 0.20, ROC-AUC = 1). Univariate analyses revealed 23 significantly different (p < 0.05) metabolites between healthy controls and SARS-CoV-2 positive individuals across both cohorts. Significant metabolites revealed consistent perturbations in cellular energy metabolism (pyruvic acid, and 2-oxoglutaric acid), oxidative stress (lactic acid, 2-hydroxybutyric acid), hypoxia (2-hydroxyglutaric acid, 5-aminolevulinic acid), liver activity (primary bile acids), and host-gut microbial cometabolism (hippuric acid, phenylpropionic acid, indole-3-propionic acid). These data support targeted LC-MS metabolic phenotyping workflows for biological validation in independent sample sets.

Untargeted urine metabolomics and machine learning provide potential metabolic signatures in children with autism spectrum disorder

Background

Complementary to traditional biostatistics, the integration of untargeted urine metabolomic profiling with Machine Learning (ML) has the potential to unveil metabolic profiles crucial for understanding diseases. However, the application of this approach in autism remains underexplored. Our objective was to delve into the metabolic profiles of autism utilizing a comprehensive untargeted metabolomics platform coupled with ML.

Methods

Untargeted metabolomics quantification (UHPLC/Q-TOF-MS) was performed for urine analysis. Feature selection was conducted using Lasso regression, and logistic regression, support vector machine, random forest, and extreme gradient boosting were utilized for significance stratification. Pathway enrichment analysis was performed to identify metabolic pathways associated with autism.

Results

A total of 52 autistic children and 40 typically developing children were enrolled. Lasso regression identified ninety-two urinary metabolites that significantly differed between the two groups. Distinct metabolites, such as prostaglandin E2, phosphonic acid, lysine, threonine, and phenylalanine, were revealed to be associated with autism through the application of four different ML methods (p<0.05). The alterations observed in the phosphatidylinositol and inositol phosphate metabolism pathways were linked to the pathophysiology of autism (p<0.05).

Conclusion

Significant urinary metabolites, including prostaglandin E2, phosphonic acid, lysine, threonine, and phenylalanine, exhibit associations with autism. Additionally, the involvement of the phosphatidylinositol and inositol phosphate pathways suggests their potential role in the pathophysiology of autism.

Microbiome function and neurodevelopment in Black infants: vitamin B12 emerges as a key factor

The early life gut microbiome affects the developing brain, and therefore may serve as a target to support neurodevelopment of children living in stressful and under-resourced environments, such as Black youth living on the South Side of Chicago, for whom we observe racial disparities in health. Microbiome compositions/functions key to multiple neurodevelopmental facets have not been studied in Black children, a vulnerable population due to racial disparities in health; thus, a subsample of Black infants living in urban, low-income neighborhoods whose mothers participated in a prenatal nutrition study were recruited for testing associations between composition and function of the gut microbiome (16S rRNA gene sequencing, shotgun metagenomics, and targeted metabolomics of fecal samples) and neurodevelopment (developmental testing, maternal report of temperament, and observed stress regulation). Two microbiome community types, defined by high Lachnospiraceae or Enterobacteriaceae abundance, were discovered in this cohort from 16S rRNA gene sequencing analysis; the Enterobacteriaceae-dominant community type was significantly negatively associated with cognition and language scores, specifically in male children. Vitamin B12 biosynthesis emerged as a key microbiome function from shotgun metagenomics sequencing analysis, showing positive associations with all measured developmental skills (i.e., cognition, language, motor, surgency, effortful control, and observed stress regulation). Blautia spp. also were identified as substantial contributors of important microbiome functions, including vitamin B12 biosynthesis and related vitamin B12-dependent microbiome functions, anti-inflammatory microbial surface antigens, competitive mechanisms against pathobionts, and production of antioxidants. The results are promising with respect to the potential for exploring therapeutic candidates, such as vitamin B12 nutritional or Blautia spp. probiotic supplementation, to support the neurodevelopment of infants at risk for experiencing racial disparities in health.

Microbiome-Gut-Mucosal-Immune-Brain Axis and Autism Spectrum Disorder (ASD): A Novel Proposal of the Role of the Gut Microbiome in ASD Aetiology

Autism Spectrum Disorder (ASD) is a complex neurodevelopmental disorder characterised by deficits in social interaction and communication, as well as restricted and stereotyped interests. Due of the high prevalence of gastrointestinal disorders in individuals with ASD, researchers have investigated the gut microbiota as a potential contributor to its aetiology. The relationship between the microbiome, gut, and brain (microbiome-gut-brain axis) has been acknowledged as a key factor in modulating brain function and social behaviour, but its connection to the aetiology of ASD is not well understood. Recently, there has been increasing attention on the relationship between the immune system, gastrointestinal disorders and neurological issues in ASD, particularly in relation to the loss of specific species or a decrease in microbial diversity. It focuses on how gut microbiota dysbiosis can affect gut permeability, immune function and microbiota metabolites in ASD. However, a very complete study suggests that dysbiosis is a consequence of the disease and that it has practically no effect on autistic manifestations. This is a review of the relationship between the immune system, microbial diversity and the microbiome-gut-brain axis in the development of autistic symptoms severity and a proposal of a novel role of gut microbiome in ASD, where dysbiosis is a consequence of ASD-related behaviour and where dysbiosis in turn accentuates the autistic manifestations of the patients via the microbiome-gut-brain axis in a feedback circuit.

Metabolic Pathway Analysis: Advantages and Pitfalls for the Functional Interpretation of Metabolomics and Lipidomics Data

Over the past decades, pathway analysis has become one of the most commonly used approaches for the functional interpretation of metabolomics data. Although the approach is widely used, it is not well standardized and the impact of different methodologies on the functional outcome is not well understood. Using four publicly available datasets, we investigated two main aspects of topological pathway analysis, namely the consideration of non-human native enzymatic reactions (e.g., from microbiota) and the interconnectivity of individual pathways. The exclusion of non-human native reactions led to detached and poorly represented reaction networks and to loss of information. The consideration of connectivity between pathways led to better emphasis of certain central metabolites in the network; however, it occasionally overemphasized the hub compounds. We proposed and examined a penalization scheme to diminish the effect of such compounds in the pathway evaluation. In order to compare and assess the results between different methodologies, we also performed over-representation analysis of the same datasets. We believe that our findings will raise awareness on both the capabilities and shortcomings of the currently used pathway analysis practices in metabolomics. Additionally, it will provide insights on various methodologies and strategies that should be considered for the analysis and interpretation of metabolomics data.

Differences of gut microbiota and behavioral symptoms between two subgroups of autistic children based on γδT cells-derived IFN-γ Levels: A preliminary study

Background

Autism Spectrum Disorders (ASD) are defined as a group of pervasive neurodevelopmental disorders, and the heterogeneity in the symptomology and etiology of ASD has long been recognized. Altered immune function and gut microbiota have been found in ASD populations. Immune dysfunction has been hypothesized to involve in the pathophysiology of a subtype of ASD.

Methods

A cohort of 105 ASD children were recruited and grouped based on IFN-γ levels derived from ex vivo stimulated γδT cells. Fecal samples were collected and analyzed with a metagenomic approach. Comparison of autistic symptoms and gut microbiota composition was made between subgroups. Enriched KEGG orthologues markers and pathogen-host interactions based on metagenome were also analyzed to reveal the differences in functional features.

Results

The autistic behavioral symptoms were more severe for children in the IFN-γ-high group, especially in the body and object use, social and self-help, and expressive language performance domains. LEfSe analysis of gut microbiota revealed an overrepresentation of Selenomonadales, Negatiyicutes, Veillonellaceae and Verrucomicrobiaceae and underrepresentation of Bacteroides xylanisolvens and Bifidobacterium longum in children with higher IFN-γ level. Decreased metabolism function of carbohydrate, amino acid and lipid in gut microbiota were found in the IFN-γ-high group. Additional functional profiles analyses revealed significant differences in the abundances of genes encoding carbohydrate-active enzymes between the two groups. And enriched phenotypes related to infection and gastroenteritis and underrepresentation of one gut-brain module associated with histamine degradation were also found in the IFN-γ-High group. Results of multivariate analyses revealed relatively good separation between the two groups.

Conclusions

Levels of IFN-γ derived from γδT cell could serve as one of the potential candidate biomarkers to subtype ASD individuals to reduce the heterogeneity associated with ASD and produce subgroups which are more likely to share a more similar phenotype and etiology. A better understanding of the associations among immune function, gut microbiota composition and metabolism abnormalities in ASD would facilitate the development of individualized biomedical treatment for this complex neurodevelopmental disorder.

The Role of Gut Microbiota-Brain Axis in Pathophysiology of ADHD: A Systematic Review

OBJECTIVE

The main goal of this systematic review is to summarize evidences regarding alterations of microbial composition in ADHD cases and uncover underlying mechanisms.

METHODS

A comprehensive search was conducted on PubMed, Web of Science, and Scopus databases up to March 2021. All the observational studies including case-control, cross-sectional, and cohorts investigating the correlations between the gut microbiota and ADHD in both adults and children were included.

RESULTS

We found eight eligible studies. Enterococcus, Bifidobacterium, and Odoribacter were increased which may lead to impaired dopamine related functions in CNS. Moreover, decrease of Faecalibacterium frequency in ADHD could result in higher permeability and crossing of inflammatory cytokines. Regarding the short chain fatty acids-producing bacteria, Ruminococcaceae family decreased and Bacteroides uniformis and Bacteroides ovatus species increased.

CONCLUSION

Gut microbiota correlation with ADHD and its underlying mechanisms could open new windows for developing novel therapies of ADHD by manipulating microbiota.

Metabolism of phenolics in coffee and plant-based foods by canonical pathways: an assessment of the role of fatty acid β-oxidation to generate biologically-active and -inactive intermediates

ω-Phenyl-alkenoic acids are abundant in coffee, fruits, and vegetables. Along with ω-phenyl-alkanoic acids, they are produced from numerous dietary (poly)phenols and aromatic amino acids in vivo. This review addresses how phenyl-ring substitution and flux modulates their gut microbiota and endogenous β-oxidation. 3',5'-Dihydroxy-derivatives (from alkyl-resorcinols, flavanols, proanthocyanidins), and 4'-hydroxy-phenolic acids (from tyrosine, p-coumaric acid, naringenin) are β-oxidation substrates yielding benzoic acids. In contrast, 3',4',5'-tri-substituted-derivatives, 3',4'-dihydroxy-derivatives and 3'-methoxy-4'-hydroxy-derivatives (from coffee, tea, cereals, many fruits and vegetables) are poor β-oxidation substrates with metabolism diverted via gut microbiota dehydroxylation, phenylvalerolactone formation and phase-2 conjugation, possibly a strategy to conserve limited pools of coenzyme A. 4'-Methoxy-derivatives (citrus fruits) or 3',4'-dimethoxy-derivatives (coffee) are susceptible to hepatic "reverse" hydrogenation suggesting incompatibility with enoyl-CoA-hydratase. Gut microbiota-produced 3'-hydroxy-4'-methoxy-derivatives (citrus fruits) and 3'-hydroxy-derivatives (numerous (poly)phenols) are excreted as the phenyl-hydracrylic acid β-oxidation intermediate suggesting incompatibility with hydroxy-acyl-CoA dehydrogenase, albeit with considerable inter-individual variation. Further investigation is required to explain inter-individual variation, factors determining the amino acid to which C6-C3 and C6-C1 metabolites are conjugated, the precise role(s) of l-carnitine, whether glycine might be limiting, and whether phenolic acid-modulation of β-oxidation explains how phenolic acids affect key metabolic conditions, such as fatty liver, carbohydrate metabolism and insulin resistance.

Attention-Deficit/Hyperactivity Disorder and the Gut Microbiota–Gut–Brain Axis: Closing Research Gaps through Female Inclusion in Study Design

The gastrointestinal tract harbors a densely populated community of microbes that exhibits sexual dimorphism. Dysbiosis of this community has been associated with chronic human disease states ranging from metabolic diseases to neuropsychiatric disorders (NPDs). The gut microbiota–gut–brain axis (GMGBA) is a bi-directional pathway that facilitates the interaction of the gut microflora with host physiological functions. Recently, research surrounding the potential roles of the GMGBA in the development of NPDs (e.g., depression, anxiety, and autism spectrum disorders (ASDs)) has increased. However, the role of the GMGBA in attention-deficit/hyperactivity disorder (ADHD), an NPD that affects an estimated 8.4% of children (5.1% of female and 11.5% of male children) and 4% of adults (with a male–female odds ratio of 1.6) in the United States, remains understudied. Herein, we synthesize the current literature regarding the GMGBA, ADHD, and the potentially relevant intersections between the GMGBA and ADHD. Recommendations are presented for pathways of future research into the role(s) of the GMGBA in ADHD etiology and symptomatology. Particular focus is given to the potential for the variable of host sex to act as an outcome modifier of the relationship between the GMGBA and ADHD.

NMR-Based Metabolomics of Rat Hippocampus, Serum, and Urine in Two Models of Autism

Autism spectrum disorders (ASDs) are increasingly diagnosed as developmental disabilities of unclear etiology related to genetic, epigenetic, or environmental factors. The diagnosis of ASD in children is based on the recognition of typical behavioral symptoms, while no reliable biomarkers are available. Rats in whom ASD-like symptoms are due to maternal administration of the teratogenic drugs valproate or thalidomide on critical day 11 of pregnancy are widely used models in autism research. The present studies, aimed at detecting changes in the levels of hydrophilic and hydrophobic metabolites, were carried out on 1-month-old rats belonging to the abovementioned two ASD models and on a control group. Analysis of both hydrophilic and hydrophobic metabolite levels gives a broader view of possible mechanisms involved in the pathogenesis of autism. Hippocampal proton magnetic resonance (MRS) spectroscopy and ex vivo nuclear magnetic resonance (NMR) analysis of serum and urine samples were used. The results were analyzed using advanced statistical tests. Both the results of our present MRS studies of the hippocampus and of the NMR studies of body fluids in both ASD models, particularly from the THAL model, appeared to be consistent with previously published NMR results of hippocampal homogenates and data from the literature on autistic children. We detected symptoms of disturbances in neurotransmitter metabolism, energy deficit, and oxidative stress, as well as intestinal malfunction, which shed light on the pathogenesis of ASD and could be used for diagnostic purposes. These results confirm the usefulness of the noninvasive techniques used in ASD studies.

Childhood ADHD, Going Beyond the Brain: A Meta-Analysis on Peripheral Physiological Markers of the Heart and the Gut

Attention-Deficit/Hyperactivity Disorder (ADHD) is the most common neurodevelopmental disorder diagnosed in children. Questions regarding its increased diagnostic rates and pharmacological treatments in developing children have led to a more holistic review of the multi-system pathophysiology observed in ADHD. The dopaminergic neurotransmitter system, known for its influence on reward-motivated behaviors and motor control, and the frontostriatal systems, that mediate motor, cognition, and behavior, are associated with ADHD's development. However, studies have shown that these neural systems do not wholly account for ADHD's multilayered and heterogeneous symptom presentation. For instance, the literature suggests that emotional dysregulation, the inability to regulate one's emotional responses to provoking stimuli, is associated with increased risk for social impairment in ADHD. A broader examination of physiological systems in children with ADHD has found potential markers in the heart-brain and gut-brain axes that correspond with certain behaviors associated with emotional dysregulation in recent studies. Hence, the purpose of this meta-analysis is to aggregate ten applicable published case studies and analyze task-related heart rate reactivity (HRR; n = 5 studies) and gut microbiota (n = 5 studies) data in children with and without ADHD. Data from a total of 531 youth with ADHD and 603 youth without ADHD revealed significant small and medium effect sizes for higher Chao1 levels and Actinobacteria levels in the ADHD group, respectively, but no evidence of altered task-related HRR. Thus, further research into multi-system psychophysiological measures of emotional dysregulation and ADHD is warranted. The clinical, empirical, and educational implications of these findings are discussed.

SYSTEMATIC REVIEW REGISTRATION

https://www.crd.york.ac.uk/prospero/, identifier PROSPERO (CRD42021236819).

Hippuric acid: Could became a barometer for frailty and geriatric syndromes?

Aging is a natural biological event that has some downsides such as increased frailty, decline in cognitive and physical functions leading to chronical diseases, and lower quality of life. There is therefore a pressing need of reliable biomarkers to identify populations at risk of developing age-associated syndromes in order to improve their quality of life, promote healthy ageing and a more appropriate clinical management, when needed. Here we discuss the importance of hippuric acid, an endogenous co-metabolite, as a possible hallmark of human aging and age-related diseases, summarizing the scientific literature over the last years. Hippuric acid, the glycine conjugate of benzoic acid, derives from the catabolism by means of intestinal microflora of dietary polyphenols found in plant-based foods (e.g. fruits, vegetables, tea and coffee). In healthy conditions hippuric acid levels in blood and/or urine rise significantly during aging while its excretion drops in conditions related with aging, including cognitive impairments, rheumatic diseases, sarcopenia and hypomobility. This literature highlights the utility of hippuric acid in urine and plasma as a plausible hallmark of frailty, related to low fruit and vegetable intake and changes in gut microflora.

The role of microbiota-gut-brain axis in neuropsychiatric and neurological disorders

Emerging evidence indicates that the gut microbiota play a crucial role in the bidirectional communication between the gut and the brain suggesting that the gut microbes may shape neural development, modulate neurotransmission and affect behavior, and thereby contribute to the pathogenesis and/or progression of many neurodevelopmental, neuropsychiatric, and neurological conditions. This review summarizes recent data on the role of microbiota-gut-brain axis in the pathophysiology of neuropsychiatric and neurological disorders including depression, anxiety, schizophrenia, autism spectrum disorders, Parkinson's disease, migraine, and epilepsy. Also, the involvement of microbiota in gut disorders co-existing with neuropsychiatric conditions is highlighted. We discuss data from both in vivo preclinical experiments and clinical reports including: (1) studies in germ-free animals, (2) studies exploring the gut microbiota composition in animal models of diseases or in humans, (3) studies evaluating the effects of probiotic, prebiotic or antibiotic treatment as well as (4) the effects of fecal microbiota transplantation.

Comprehensive physiopathology and serum metabolomics for the evaluation of the influence mechanism of qi deficiency on xenograft mouse models of liver cancer

Traditional Chinese medicine believes that qi deficiency is important pathogenesis and syndrome of liver cancer and thus is crucial in related research. However, the effect of qi deficiency on the occurrence and development of liver cancer is still unclear. This study aimed to establish a liver cancer model of qi deficiency through the swimming exhaustion and xenograft of human hepatoma HepG2 cells. The effects of qi deficiency on the occurrence and development of liver cancer were investigated by analyzing tumor development, blood routine, histopathology, and serum metabolomics. Results showed that qi deficiency greatly affected the physiology and tumor growth of xenograft mice. Eight potential biomarkers were identified by metabolomics based on ultra-high performance liquid chromatography and tandem quadrupole time-of-flight mass spectrometry. Their main pathways were arachidonic acid metabolism, phenylalanine metabolism, purine metabolism, glycerolipid metabolism, steroid biosynthesis, sphingomyelin metabolism, and fatty acid metabolism pathway. Finally, the effects of qi deficiency on the occurrence and development of liver cancer were comprehensively analyzed, and the mechanism of this process was preliminarily clarified.

Mass spectrometry-based urinary metabolomics for exploring the treatment effects of Radix ginseng-Schisandra chinensis herb pair on Alzheimer's disease in rats

Herb pairs are the unique combinations of two relatively fixed herbs, intrinsically convey the basic idea of traditional Chinese medicine prescriptions. The compatibility of Radix ginseng and Schisandra chinensis has been used in traditional Chinese medicine for treating Alzheimer's disease for many years. However, there are few studies on Radix ginseng-Schisandra chinensis herb pair, and the underlying action mechanism is still unclear. In this study, the mechanism of Radix ginseng-Schisandra chinensis herb pair on Alzheimer's disease was investigated by using the mass spectrometry-based urinary metabolomics method. Sixteen urinary endogenous metabolites were identified as potential biomarkers. Meanwhile, 10 biomarkers were quantified with tandem mass spectrometry. The study result showed that the brain pathologic symptoms of model rats were improved and the potential biomarkers were adjusted backward significantly after the herb pair administration. The metabolic pathways linked to the herb pair-regulated endogenous biomarkers included phenylalanine and tyrosine metabolism, tryptophan metabolism, purine metabolism, and so on. The above metabolic pathways reflected that Radix ginseng-Schisandra chinensis herb pair mainly regulates abnormal energy metabolism, reduces inflammation, and regulates gut microbiota and neurotransmitters in the treatment of Alzheimer's disease.

A Pilot Study for Metabolic Profiling of Obesity-Associated Microbial Gut Dysbiosis in Male Wistar Rats

Obesity is one of the most incident and concerning disease worldwide. Definite strategies to prevent obesity and related complications remain elusive. Among the risk factors of the onset of obesity, gut microbiota might play an important role in the pathogenesis of the disease, and it has received extensive attention because it affects the host metabolism. In this study, we aimed to define a metabolic profile of the segregated obesity-associated gut dysbiosis risk factor. The study of the metabolome, in an obesity-associated gut dysbiosis model, provides a relevant way for the discrimination on the different biomarkers in the obesity onset. Thus, we developed a model of this obesity risk factors through the transference of gut microbiota from obese to non-obese male Wistar rats and performed a subsequent metabolic analysis in the receptor rats. Our results showed alterations in the lipid metabolism in plasma and in the phenylalanine metabolism in urine. In consequence, we have identified metabolic changes characterized by: (1) an increase in DG:34:2 in plasma, a decrease in hippurate, (2) an increase in 3-HPPA, and (3) an increase in o-coumaric acid. Hereby, we propose these metabolites as a metabolic profile associated to a segregated dysbiosis state related to obesity disease.

Comparison of the Metabolic Profiles in the Plasma and Urine Samples Between Autistic and Typically Developing Boys: A Preliminary Study

Background: Autism spectrum disorder (ASD) is defined as a pervasive developmental disorder which is caused by genetic and environmental risk factors. Besides the core behavioral symptoms, accumulated results indicate children with ASD also share some metabolic abnormalities. Objectives: To analyze the comprehensive metabolic profiles in both of the first-morning urine and plasma samples collected from the same cohort of autistic boys. Methods: In this study, 30 autistic boys and 30 tightly matched healthy control (HC) boys (age range: 2.4~6.7 years) were recruited. First-morning urine and plasma samples were collected and the liquid chromatography-mass spectrometry (LC-MS) was applied to obtain the untargeted metabolic profiles. The acquired data were processed by multivariate analysis and the screened metabolites were grouped by metabolic pathway. Results: Different discriminating metabolites were found in plasma and urine samples. Notably, taurine and catechol levels were decreased in urine but increased in plasma in the same cohort of ASD children. Enriched pathway analysis revealed that perturbations in taurine and hypotaurine metabolism, phenylalanine metabolism, and arginine and proline metabolism could be found in both of the plasma and urine samples. Conclusion: These preliminary results suggest that a series of common metabolic perturbations exist in children with ASD, and confirmed the importance to have a comprehensive analysis of the metabolites in different biological samples to reveal the full picture of the complex metabolic patterns associated with ASD. Further targeted analyses are needed to validate these results in a larger cohort.

Differential Metabolites in Chinese Autistic Children: A Multi-Center Study Based on Urinary 1H-NMR Metabolomics Analysis

Background: Autism spectrum disorder (ASD) is a group of early-onset neurodevelopmental disorders. However, there is no valuable biomarker for the early diagnosis of ASD. Our large-scale and multi-center study aims to identify metabolic variations between ASD and healthy children and to investigate differential metabolites and associated pathogenic mechanisms. Methods: One hundred and seventeen autistic children and 119 healthy children were recruited from research centers of 7 cities. Urine samples were assayed by ¹H-NMR metabolomics analysis to detect metabolic variations. Multivariate statistical analysis, including principal component analysis (PCA), and orthogonal projection to latent structure discriminant analysis (OPLS-DA), as well as univariate analysis were used to assess differential metabolites between the ASD and control groups. The differential metabolites were further analyzed by receiver operating characteristics (ROC) curve analysis and metabolic pathways analysis. Results: Compared with the control group, the ASD group showed higher levels of glycine, guanidinoacetic acid, creatine, hydroxyphenylacetylglycine, phenylacetylglycine, and formate and lower levels of 3-aminoisobutanoic acid, alanine, taurine, creatinine, hypoxanthine, and N-methylnicotinamide. ROC curve showed relatively significant diagnostic values for hypoxanthine [area under the curve (AUC) = 0.657, 95% CI 0.588 to 0.726], creatinine (AUC = 0.639, 95% CI 0.569 to 0.709), creatine (AUC = 0.623, 95% CI 0.552 to 0.694), N-methylnicotinamide (AUC = 0.595, 95% CI 0.523 to 0.668), and guanidinoacetic acid (AUC = 0.574, 95% CI 0.501 to 0.647) in the ASD group. Combining the metabolites creatine, creatinine and hypoxanthine, the AUC of the ROC curve reached 0.720 (95% CI 0.659 to 0.777). Significantly altered metabolite pathways associated with differential metabolites were glycine, serine and threonine metabolism, arginine and proline metabolism, and taurine and hypotaurine metabolism. Conclusions: Urinary amino acid metabolites were significantly altered in children with ASD. Amino acid metabolic pathways might play important roles in the pathogenic mechanisms of ASD.

Untargeted Metabolomic Profiling Using UHPLC-QTOF/MS Reveals Metabolic Alterations Associated with Autism

Autism spectrum disorder (ASD) is a clinical spectrum of neurodevelopment disorder characterized by deficits in social communication and social interaction along with repetitive/stereotyped behaviors. The current diagnosis for autism relies entirely on clinical evaluation and has many limitations. In this study, we aim to elucidate the potential mechanism behind autism and establish a series of potential biomarkers for diagnosis. Here, we established an ultra-high-performance liquid chromatography-quadrupole time-of-flight mass spectrometry- (UHPLC-QTOF/MS-) based metabonomic approach to discriminate the metabolic modifications between the cohort of autism patients and the healthy subjects. UHPLC-QTOF/MS analysis revealed that 24 of the identified potential biomarkers were primarily involved in amino acid or lipid metabolism and the tryptophan kynurenine pathway. The combination of nicotinamide, anthranilic acid, D-neopterin, and 7,8-dihydroneopterin allows for discrimination between ASD patients and controls, which were validated in an independent autism case-control cohort. The results indicated that UHPLC-QTOF/MS-based metabolomics is capable of rapidly profiling autism metabolites and is a promising technique for the discovery of potential biomarkers related to autism.

Dietary Components, Microbial Metabolites and Human Health: Reading between the Lines

Trillions of bacteria reside in the human gut and they metabolize dietary substances to obtain nutrients and energy while producing metabolites. Therefore, different dietary components could affect human health in various ways through microbial metabolism. Many such metabolites have been shown to affect human physiological activities, including short-chain fatty acids metabolized from carbohydrates; indole, kynurenic acid and para-cresol, metabolized from amino acids; conjugated linoleic acid and linoleic acid, metabolized from lipids. Here, we review the features of these metabolites and summarize the possible molecular mechanisms of their metabolisms by gut microbiota. We discuss the potential roles of these metabolites in health and diseases, and the interactions between host metabolism and the gut microbiota. We also show some of the major dietary patterns around the world and hope this review can provide insights into our eating habits and improve consumers' health conditions.

Gut Microbiota Dysbiosis Associated With Altered Production of Short Chain Fatty Acids in Children With Neurodevelopmental Disorders

While gut microbiota dysbiosis has been linked with autism, its role in the etiology of other neurodevelopmental disorders (NDD) is largely underexplored. To our knowledge this is the first study to evaluate gut microbiota diversity and composition in 36 children from the Republic of Serbia diagnosed with NDD and 28 healthy children. The results revealed an increased incidence of potentially harmful bacteria, closely related to Clostridium species, in the NDD patient group compared to the Control group: Desulfotomaculum guttoideum (P < 0.01), Intestinibacter bartlettii (P < 0.05), and Romboutsia ilealis (P < 0.001). On the other hand, significantly lower diversity of common commensal bacteria in the NDD group of patients was noticed. Enterococcus faecalis (P < 0.05), Enterococcus gallinarum (P < 0.01), Streptococcus pasteurianus (P < 0.05), Lactobacillus rhamnosus (P < 0.01) and Bifidobacteria sp. were detected in lower numbers of patients or were even absent in some NDD patients. In addition, butyrate-producing bacteria Faecalibacterium prausnitzii (P < 0.01), Butyricicoccus pullicaecorum (P < 0.05), and Eubacterium rectale (P = 0.07) were less frequent in the NDD patient group. In line with that, the levels of fecal short chain fatty acids (SCFAs) were determined. Although significant differences in SCFA levels were not detected between NDD patients and the Control group, a positive correlation was noted between number of rDNA amplicons obtained with universal primers and level of propionic acid, as well as a trend for levels of total SCFAs and butyric acid in the Control group. This correlation is lost in the NDD patient group, indicating that NDD patients' microbiota differs from the microbiota of healthy children in the presence or number of strong SCFA-producing bacteria. According to a range-weighted richness index it was observed that microbial diversity was significantly lower in the NDD patient group. Our study reveals that the intestinal microbiota from NDD patients differs from the microbiota of healthy children. It is hypothesized that early life microbiome might have an impact on GI disturbances and accompanied behavioral problems frequently observed in patients with a broad spectrum of NDD.

Down regulation of p-coumarate 3-hydroxylase in petunia uniquely alters the profile of emitted floral volatiles

Petunia × hybrida cv ‘Mitchell Diploid’ floral volatile benzenoid/phenylpropanoid (FVBP) biosynthesis ultimately produces floral volatiles derived sequentially from phenylalanine, cinnamic acid, and p-coumaric acid. In an attempt to better understand biochemical steps after p-coumaric acid production, we cloned and characterized three petunia transcripts with high similarity to p-coumarate 3-hydroxylase (C3H), hydroxycinnamoyl-CoA:shikimate/quinate hydroxycinnamoyl transferase (HCT), and caffeoyl shikimate esterase (CSE). Transcript accumulation of PhC3H and PhHCT was highest in flower limb tissue during open flower stages. PhCSE transcript accumulation was also highest in flower limb tissue, but it was detected earlier at initial flower opening with a bell-shaped distribution pattern. Down regulation of endogenous PhC3H transcript resulted in altered transcript accumulation of many other FVBP network transcripts, a reduction in floral volatiles, and the emission of a novel floral volatile. Down regulation of PhHCT transcript did not have as large of an effect on floral volatiles as was observed for PhC3H down regulation, but eugenol and isoeugenol emissions were significantly reduced on the downstream floral volatiles. Together these results indicate that PhC3H is involved in FVBP biosynthesis and the reduction of PhC3H transcript influences FVBP metabolism at the network level. Additional research is required to illustrate PhHCT and PhCSE functions of petunia.

Macronutrient metabolism by the human gut microbiome: major fermentation by-products and their impact on host health

The human gut microbiome is a critical component of digestion, breaking down complex carbohydrates, proteins, and to a lesser extent fats that reach the lower gastrointestinal tract. This process results in a multitude of microbial metabolites that can act both locally and systemically (after being absorbed into the bloodstream). The impact of these biochemicals on human health is complex, as both potentially beneficial and potentially toxic metabolites can be yielded from such microbial pathways, and in some cases, these effects are dependent upon the metabolite concentration or organ locality. The aim of this review is to summarize our current knowledge of how macronutrient metabolism by the gut microbiome influences human health. Metabolites to be discussed include short-chain fatty acids and alcohols (mainly yielded from monosaccharides); ammonia, branched-chain fatty acids, amines, sulfur compounds, phenols, and indoles (derived from amino acids); glycerol and choline derivatives (obtained from the breakdown of lipids); and tertiary cycling of carbon dioxide and hydrogen. Key microbial taxa and related disease states will be referred to in each case, and knowledge gaps that could contribute to our understanding of overall human wellness will be identified.

The Possible Role of the Microbiota-Gut-Brain-Axis in Autism Spectrum Disorder

New research points to a possible link between autism spectrum disorder (ASD) and the gut microbiota as many autistic children have co-occurring gastrointestinal problems. This review focuses on specific alterations of gut microbiota mostly observed in autistic patients. Particularly, the mechanisms through which such alterations may trigger the production of the bacterial metabolites, or leaky gut in autistic people are described. Various altered metabolite levels were observed in the blood and urine of autistic children, many of which were of bacterial origin such as short chain fatty acids (SCFAs), indoles and lipopolysaccharides (LPS). A less integrative gut-blood-barrier is abundant in autistic individuals. This explains the leakage of bacterial metabolites into the patients, triggering new body responses or an altered metabolism. Some other co-occurring symptoms such as mitochondrial dysfunction, oxidative stress in cells, altered tight junctions in the blood-brain barrier and structural changes in the cortex, hippocampus, amygdala and cerebellum were also detected. Moreover, this paper suggests that ASD is associated with an unbalanced gut microbiota (dysbiosis). Although the cause-effect relationship between ASD and gut microbiota is not yet well established, the consumption of specific probiotics may represent a side-effect free tool to re-establish gut homeostasis and promote gut health. The diagnostic and therapeutic value of bacterial-derived compounds as new possible biomarkers, associated with perturbation in the phenylalanine metabolism, as well as potential therapeutic strategies will be discussed.

Differences in cecal microbiome of selected high and low feather-pecking laying hens

In mammals, it has become increasingly clear that the gut microbiota influences not only gastrointestinal physiology but also modulates behavior. In domestic birds, ceca have the greatest gastrointestinal microbial population. Feather-pecking (FP) behavior in laying hens is one of the most important unsolved behavioral issues in modern agriculture. The aim of the present study was to assess the cecal microbial community of divergently selected high (HFP; n = 20) and low (LFP; n = 20) feather-pecking birds at 60 wk of age. The cecal samples were subjected to community profiling of 16S rRNA and in silico metagenomics using a modified bar-coded Illumina sequencing method on a MiSeq Illumina sequencer. Our results revealed that compared to HFP birds, LFP birds are characterized by an increased overall microbial diversity (beta diversity) shown by a difference in the Bray–Curtis index (R² = 0.171, P < 0.05). Furthermore, operational taxonomic unit comparisons showed an increased presence of Clostridiae and decreased presence of Lactobaccillacae in HFP birds when compared to LFP birds (False Discovery Rate < 0.05, Mann–Whitney comparisons). Our data indicate that there may be differences in the cecal profile between these 2 lines of laying hens. More research, building on this first study using sequencing technology for profiling the chicken cecal microbiome, will be needed in order to reveal if and how there exists a functional link between the performance of FP and the cecal microbial community.

Dietary Considerations in Autism Spectrum Disorders: The Potential Role of Protein Digestion and Microbial Putrefaction in the Gut-Brain Axis

Children with autism spectrum disorders (ASD), characterized by a range of behavioral abnormalities and social deficits, display high incidence of gastrointestinal (GI) co-morbidities including chronic constipation and diarrhea. Research is now increasingly able to characterize the “fragile gut” in these children and understand the role that impairment of specific GI functions plays in the GI symptoms associated with ASD. This mechanistic understanding is extending to the interactions between diet and ASD, including food structure and protein digestive capacity in exacerbating autistic symptoms. Children with ASD and gut co-morbidities exhibit low digestive enzyme activity, impaired gut barrier integrity and the presence of antibodies specific for dietary proteins in the peripheral circulation. These findings support the hypothesis that entry of dietary peptides from the gut lumen into the vasculature are associated with an aberrant immune response. Furthermore, a subset of children with ASD exhibit high concentrations of metabolites originating from microbial activity on proteinaceous substrates. Taken together, the combination of specific protein intakes poor digestion, gut barrier integrity, microbiota composition and function all on a background of ASD represents a phenotypic pattern. A potential consequence of this pattern of conditions is that the fragile gut of some children with ASD is at risk for GI symptoms that may be amenable to improvement with specific dietary changes. There is growing evidence that shows an association between gut dysfunction and dysbiosis and ASD symptoms. It is therefore urgent to perform more experimental and clinical research on the “fragile gut” in children with ASD in order to move toward advancements in clinical practice. Identifying those factors that are of clinical value will provide an evidence-based path to individual management and targeted solutions; from real time sensing to the design of diets with personalized protein source/processing, all to improve GI function in children with ASD.

Flux analysis of inborn errors of metabolism

Patients with an inborn error of metabolism (IEM) are deficient of an enzyme involved in metabolism, and as a consequence metabolism reprograms itself to reach a new steady state. This new steady state underlies the clinical phenotype associated with the deficiency. Hence, we need to know the flux of metabolites through the different metabolic pathways in this new steady state of the reprogrammed metabolism. Stable isotope technology is best suited to study this. In this review the progress made in characterizing the altered metabolism will be presented. Studies done in patients to estimate the residual flux through the metabolic pathway affected by enzyme deficiencies will be discussed. After this, studies done in model systems will be reviewed. The focus will be on glycogen storage disease type I, medium-chain acyl-CoA dehydrogenase deficiency, propionic and methylmalonic aciduria, urea cycle defects, phenylketonuria, and combined D,L-2-hydroxyglutaric aciduria. Finally, new developments are discussed, which allow the tracing of metabolic reprogramming in IEM on a genome-wide scale. In conclusion, the outlook for flux analysis of metabolic derangement in IEMs looks promising.

Poor cognitive ageing: Vulnerabilities, mechanisms and the impact of nutritional interventions

BACKGROUND

Ageing is a highly complex process marked by a temporal cascade of events, which promote alterations in the normal functioning of an individual organism. The triggers of normal brain ageing are not well understood, even less so the factors which initiate and steer the neuronal degeneration, which underpin disorders such as dementia. A wealth of data on how nutrients and diets may support cognitive function and preserve brain health are available, yet the molecular mechanisms underlying their biological action in both normal ageing, age-related cognitive decline, and in the development of neurodegenerative disorders have not been clearly elucidated.

OBJECTIVES

This review aims to summarise the current state of knowledge of vulnerabilities that predispose towards dysfunctional brain ageing, highlight potential protective mechanisms, and discuss dietary interventions that may be used as therapies. A special focus of this paper is on the impact of nutrition on neuroprotection and the underlying molecular mechanisms, and this focus reflects the discussions held during the 2nd workshop 'Nutrition for the Ageing Brain: Functional Aspects and Mechanisms' in Copenhagen in June 2016. The present review is the most recent in a series produced by the Nutrition and Mental Performance Task Force under the auspice of the International Life Sciences Institute Europe (ILSI Europe).

CONCLUSION

Coupling studies of cognitive ageing with studies investigating the effect of nutrition and dietary interventions as strategies targeting specific mechanisms, such as neurogenesis, protein clearance, inflammation, and non-coding and microRNAs is of high value. Future research on the impact of nutrition on cognitive ageing will need to adopt a longitudinal approach and multimodal nutritional interventions will likely need to be imposed in early-life to observe significant impact in older age.

Post hoc analysis of plasma amino acid profiles: towards a specific pattern in autism spectrum disorder and intellectual disability

Objectives Autism spectrum disorders and intellectual disability present a challenge for therapeutic and dietary management. We performed a re-analysis of plasma amino acid chromatography of children with autism spectrum disorders ( n = 22) or intellectual disability ( n = 29) to search for a metabolic signature that can distinguish individuals with these disorders from controls ( n = 30). Methods We performed univariate and multivariate analyses using different machine learning strategies, from the raw data of the amino acid chromatography. Finally, we analysed the metabolic pathways associated with discriminant biomarkers. Results Multivariate analysis revealed models to discriminate patients with autism spectrum disorders or intellectual disability and controls from plasma amino acid profiles ( P < 0.0003). Univariate analysis showed that autism spectrum disorder and intellectual disability patients shared similar differences relative to controls, including lower glutamate ( P < 0.0001 and P = 0.0002, respectively) and serine ( P = 0.002 for both) concentrations. The multivariate model ( P < 6.12.10^-7) to discriminate between autism spectrum disorders and intellectual disability revealed the involvement of urea, 3-methyl-histidine and histidine metabolism. Biosigner analysis and univariate analysis confirmed the role of 3-methylhistidine ( P = 0.004), histidine ( P = 0.003), urea ( P = 0.0006) and lysine ( P = 0.002). Conclusions We revealed discriminant metabolic patterns between autism spectrum disorders, intellectual disability and controls. Amino acids known to play a role in neurotransmission were discriminant in the models comparing autism spectrum disorders or intellectual disability to controls, and histidine and b-alanine metabolism was specifically highlighted in the model.

Microbiome and metabolome data integration provides insight into health and disease

For much of our history, the most basic information about the microbial world has evaded characterization. Next-generation sequencing has led to a rapid increase in understanding of the structure and function of host-associated microbial communities in diverse diseases ranging from obesity to autism. Through experimental systems such as gnotobiotic mice only colonized with known microbes, a causal relationship between microbial communities and disease phenotypes has been supported. Now, microbiome research must move beyond correlations and general demonstration of causality to develop mechanistic understandings of microbial influence, including through their metabolic activities. Similar to the microbiome field, advances in technologies for cataloguing small molecules have broadened our understanding of the metabolites that populate our bodies. Integration of microbial and metabolomics data paired with experimental validation has promise for identifying microbial influence on host physiology through production, modification, or degradation of bioactive metabolites. Realization of microbial metabolic activities that affect health is hampered by gaps in our understanding of (1) biological properties of microbes and metabolites, (2) which microbial enzymes/pathways produce which metabolites, and (3) the effects of metabolites on hosts. Capitalizing on known mechanistic relationships and filling gaps in our understanding has the potential to enable translational microbiome research across disease contexts.

Gut microbiome in ADHD and its relation to neural reward anticipation

BACKGROUND

Microorganisms in the human intestine (i.e. the gut microbiome) have an increasingly recognized impact on human health, including brain functioning. Attention-deficit/hyperactivity disorder (ADHD) is a neurodevelopmental disorder associated with abnormalities in dopamine neurotransmission and deficits in reward processing and its underlying neuro-circuitry including the ventral striatum. The microbiome might contribute to ADHD etiology via the gut-brain axis. In this pilot study, we investigated potential differences in the microbiome between ADHD cases and undiagnosed controls, as well as its relation to neural reward processing.

METHODS

We used 16S rRNA marker gene sequencing (16S) to identify bacterial taxa and their predicted gene functions in 19 ADHD and 77 control participants. Using functional magnetic resonance imaging (fMRI), we interrogated the effect of observed microbiome differences in neural reward responses in a subset of 28 participants, independent of diagnosis.

RESULTS

For the first time, we describe gut microbial makeup of adolescents and adults diagnosed with ADHD. We found that the relative abundance of several bacterial taxa differed between cases and controls, albeit marginally significant. A nominal increase in the Bifidobacterium genus was observed in ADHD cases. In a hypothesis-driven approach, we found that the observed increase was linked to significantly enhanced 16S-based predicted bacterial gene functionality encoding cyclohexadienyl dehydratase in cases relative to controls. This enzyme is involved in the synthesis of phenylalanine, a precursor of dopamine. Increased relative abundance of this functionality was significantly associated with decreased ventral striatal fMRI responses during reward anticipation, independent of ADHD diagnosis and age.

CONCLUSIONS

Our results show increases in gut microbiome predicted function of dopamine precursor synthesis between ADHD cases and controls. This increase in microbiome function relates to decreased neural responses to reward anticipation. Decreased neural reward anticipation constitutes one of the hallmarks of ADHD.

Development of a QuEChERS-Based Stable-Isotope Dilution LC-MS/MS Method To Quantitate Ferulic Acid and Its Main Microbial and Hepatic Metabolites in Milk

Forage plants of the Poaceae family are grown as pasturage or used for the production of hay, straw, corn stover, etc. Although ferulic acid contents of grasses are generally high, the amount of ingested ferulic acid differs depending on the type of forage, resulting in varying contents of ferulic acid and its microbial and hepatic metabolites in milk. Concentrations and patterns of these metabolites may be used as markers to track different forages in livestock feeding. Therefore, we developed a stable isotope dilution assay to quantitate ferulic acid, 12 ferulic acid-based metabolites, p-coumaric acid, and cinnamic acid in milk. Because most analytes were not commercially available as stable isotope labeled standard compounds, they were synthesized as ¹³C- or deuterium-labeled standard compounds. A modification of the QuEChERS method, a Quick, Easy, Cheap, Effective, Rugged, and Safe approach usually applied to analyze pesticides in plant-based products, was used to extract the phenolic acids from milk. Determination was carried out by LC-ESI-MS/MS in scheduled multiple reaction monitoring modus. By using three different milk samples, the applicability of the validated approach was demonstrated.

NMR-Based Metabonomic Analysis of Physiological Responses to Starvation and Refeeding in the Rat

Starvation is a postabsorptive condition derived from a limitation on food resources by external factors. Energy homeostasis is maintained under this condition by using sources other than glucose via adaptive mechanisms. After refeeding, when food is available, other adaptive processes are linked to energy balance. However, less has been reported about the physiological mechanisms present as a result of these conditions, considering the rat as a supraorganism. Metabolic profiling using (1)H nuclear magnetic resonance spectroscopy was used to characterize the physiological metabolic differences in urine specimens collected under starved, refed, and recovered conditions. In addition, because starvation induced lack of faecal production and not all animals produced faeces during refeeding, 24 h pooled faecal water samples were also analyzed. Urinary metabolites upregulated by starvation included 2-butanamidoacetate, 3-hydroxyisovalerate, ketoleucine, methylmalonate, p-cresyl glucuronide, p-cresyl sulfate, phenylacetylglycine, pseudouridine, creatinine, taurine, and N-acetyl glycoprotein, which were related to renal and skeletal muscle function, β-oxidation, turnover of proteins and RNA, and host-microbial interactions. Food-derived metabolites, including gut microbial cometabolites, and tricarboxylic acid cycle intermediates were upregulated under refed and recovered conditions, which characterized anabolic urinary metabotypes. The upregulation of creatine and pantothenate indicated an absorptive state after refeeding. Fecal short chain fatty acids, 3-(3-hydroxyphenyl)propionate, lactate, and acetoin provided additional information about the combinatorial metabolism between the host and gut microbiota. This investigation contributes to allow a deeper understanding of physiological responses associated with starvation and refeeding.

Gut Microbiota Profiling: Metabolomics Based Approach to Unravel Compounds Affecting Human Health

The gut microbiota is composed of a huge number of different bacteria, that produce a large amount of compounds playing a key role in microbe selection and in the construction of a metabolic signaling network. The microbial activities are affected by environmental stimuli leading to the generation of a wide number of compounds, that influence the host metabolome and human health. Indeed, metabolite profiles related to the gut microbiota can offer deep insights on the impact of lifestyle and dietary factors on chronic and acute diseases. Metagenomics, metaproteomics and metabolomics are some of the meta-omics approaches to study the modulation of the gut microbiota. Metabolomic research applied to biofluids allows to: define the metabolic profile; identify and quantify classes and compounds of interest; characterize small molecules produced by intestinal microbes; and define the biochemical pathways of metabolites. Mass spectrometry and nuclear magnetic resonance spectroscopy are the principal technologies applied to metabolomics in terms of coverage, sensitivity and quantification. Moreover, the use of biostatistics and mathematical approaches coupled with metabolomics play a key role in the extraction of biologically meaningful information from wide datasets. Metabolomic studies in gut microbiota-related research have increased, focusing on the generation of novel biomarkers, which could lead to the development of mechanistic hypotheses potentially applicable to the development of nutritional and personalized therapies.

Gut Microbiota Profiling: Metabolomics Based Approach to Unravel Compounds Affecting Human Health

The gut microbiota is composed of a huge number of different bacteria, that produce a large amount of compounds playing a key role in microbe selection and in the construction of a metabolic signaling network. The microbial activities are affected by environmental stimuli leading to the generation of a wide number of compounds, that influence the host metabolome and human health. Indeed, metabolite profiles related to the gut microbiota can offer deep insights on the impact of lifestyle and dietary factors on chronic and acute diseases. Metagenomics, metaproteomics and metabolomics are some of the meta-omics approaches to study the modulation of the gut microbiota. Metabolomic research applied to biofluids allows to: define the metabolic profile; identify and quantify classes and compounds of interest; characterize small molecules produced by intestinal microbes; and define the biochemical pathways of metabolites. Mass spectrometry and nuclear magnetic resonance spectroscopy are the principal technologies applied to metabolomics in terms of coverage, sensitivity and quantification. Moreover, the use of biostatistics and mathematical approaches coupled with metabolomics play a key role in the extraction of biologically meaningful information from wide datasets. Metabolomic studies in gut microbiota-related research have increased, focusing on the generation of novel biomarkers, which could lead to the development of mechanistic hypotheses potentially applicable to the development of nutritional and personalized therapies.

Gut Microbiota Profiling: Metabolomics Based Approach to Unravel Compounds Affecting Human Health

The gut microbiota is composed of a huge number of different bacteria, that produce a large amount of compounds playing a key role in microbe selection and in the construction of a metabolic signaling network. The microbial activities are affected by environmental stimuli leading to the generation of a wide number of compounds, that influence the host metabolome and human health. Indeed, metabolite profiles related to the gut microbiota can offer deep insights on the impact of lifestyle and dietary factors on chronic and acute diseases. Metagenomics, metaproteomics and metabolomics are some of the meta-omics approaches to study the modulation of the gut microbiota. Metabolomic research applied to biofluids allows to: define the metabolic profile; identify and quantify classes and compounds of interest; characterize small molecules produced by intestinal microbes; and define the biochemical pathways of metabolites. Mass spectrometry and nuclear magnetic resonance spectroscopy are the principal technologies applied to metabolomics in terms of coverage, sensitivity and quantification. Moreover, the use of biostatistics and mathematical approaches coupled with metabolomics play a key role in the extraction of biologically meaningful information from wide datasets. Metabolomic studies in gut microbiota-related research have increased, focusing on the generation of novel biomarkers, which could lead to the development of mechanistic hypotheses potentially applicable to the development of nutritional and personalized therapies.

Metabolomics of autism spectrum disorders: early insights regarding mammalian-microbial cometabolites

INTRODUCTION

Autism spectrum disorders (ASD) are a group of neurodevelopmental disorders consisting of delayed or impaired language development and difficulties in social interactions. The very high degree of phenotypic heterogeneity in ASD originates from the interaction between environmental risk factors and susceptible genetic loci, leading to epigenetic DNA methylation. Advances in system biology are becoming strategic for implementing knowledge on the ASD aetiology and for the early diagnosis of the disease after birth.

AREAS COVERED

We overhauled the value of either targeted or untargeted metabolomics studies in autism for identifying the most relevant metabolic pathways and key metabolites implicated in the disease, with special emphasis to mammalian-microbial metabolites. The most discriminant metabolites in ASD belong to amino acid metabolism, antioxidant status, nicotinic acid metabolism, and mitochondrial metabolism. Expert commentary: Most published studies point out the role of metabolites derived from the gut microbiota: they can modulate the behavioral phenotype of the autistic children, greatly influencing host metabolic pathways and the immune system, shaping the individual susceptibility to the disease. Pitfalls and caveats in metabolomics results across studies have been additionally recognized and discussed leading to the conclusion that metabolomics studies in ASD are far to be definitive and univocal.

Phenylketonuria and Gut Microbiota: A Controlled Study Based on Next-Generation Sequencing

Phenylketonuria (PKU) is an inborn error of metabolism associated with high blood levels of phenylalanine (Phe). A Phe-restricted diet supplemented with L-amino acids is the main treatment strategy for this disease; if started early, most neurological abnormalities can be prevented. The healthy human gut contains trillions of commensal bacteria, often referred to as the gut microbiota. The composition of the gut microbiota is known to be modulated by environmental factors, including diet. In this study, we compared the gut microbiota of 8 PKU patients on Phe-restricted dietary treatment with that of 10 healthy individuals. The microbiota were characterized by 16S rRNA sequencing using the Ion Torrent™ platform. The most dominant phyla detected in both groups were Bacteroidetes and Firmicutes. PKU patients showed reduced abundance of the Clostridiaceae, Erysipelotrichaceae, and Lachnospiraceae families, Clostridiales class, Coprococcus, Dorea, Lachnospira, Odoribacter, Ruminococcus and Veillonella genera, and enrichment of Prevotella, Akkermansia, and Peptostreptococcaceae. Microbial function prediction suggested significant differences in starch/glucose and amino acid metabolism between PKU patients and controls. Together, our results suggest the presence of distinct taxonomic groups within the gut microbiome of PKU patients, which may be modulated by their plasma Phe concentration. Whether our findings represent an effect of the disease itself, or a consequence of the modified diet is unclear.

Microbial-Derived Metabolites Reflect an Altered Intestinal Microbiota during Catch-Up Growth in Undernourished Neonatal Mice

BACKGROUND

Protein-energy undernutrition during early development confers a lifelong increased risk of obesity-related metabolic disease. Mechanisms by which metabolic abnormalities persist despite catch-up growth are poorly understood.

OBJECTIVE

We sought to determine whether abnormal metabolomic and intestinal microbiota profiles from undernourished neonatal mice remain altered during catch-up growth.

METHODS

Male and female CD1 mouse pups were undernourished by timed separation from lactating dams for 4 h at 5 d of age, 8 h at 6 d of age, and 12 h/d from 7 to 15 d of age, then resumed ad libitum nursing, whereas controls fed uninterrupted. Both groups were weaned simultaneously to a standard unpurified diet. At 3 time points (0, 1, and 3 wk after ending feed deprivation), metabolites in urine, plasma, and stool were identified with the use of mass spectrometry, and fecal microbes were identified with the use of 16S metagenomic sequencing.

RESULTS

Undernourished mice completely recovered deficits of 36% weight and 9% length by 3 wk of refeeding, at which time they had 1.4-fold higher plasma phenyllactate and 2.0-fold higher urinary p-cresol sulfate concentrations than did controls. Plasma serotonin concentrations in undernourished mice were 25% lower at 0 wk but 1.5-fold higher than in controls at 3 wk. Whereas most urine and plasma metabolites normalized with refeeding, 117 fecal metabolites remained altered at 3 wk, including multiple N-linked glycans. Microbiota profiles from undernourished mice also remained distinct, with lower mean proportions of Bacteroidetes (67% compared with 83%) and higher proportions of Firmicutes (26% compared with 16%). Abundances of the mucolytic organisms Akkermansia muciniphila and Mucispirillum schaedleri were altered at 0 and 1 wk. Whereas microbiota from undernourished mice at 0 wk contained 11% less community diversity (P = 0.015), refed mice at 3 wk harbored 1.2-fold greater diversity (P = 0.0006) than did controls.

CONCLUSION

Microbial-derived metabolites and intestinal microbiota remain altered during catch-up growth in undernourished neonatal mice.

Maternal Weaning Modulates Emotional Behavior and Regulates the Gut-Brain Axis

Evidence shows that nutritional and environmental stress stimuli during postnatal period influence brain development and interactions between gut and brain. In this study we show that in rats, prevention of weaning from maternal milk results in depressive-like behavior, which is accompanied by changes in the gut bacteria and host metabolism. Depressive-like behavior was studied using the forced-swim test on postnatal day (PND) 25 in rats either weaned on PND 21, or left with their mother until PND 25 (non-weaned). Non-weaned rats showed an increased immobility time consistent with a depressive phenotype. Fluorescence in situ hybridization showed non-weaned rats to harbor significantly lowered Clostridium histolyticum bacterial groups but exhibit marked stress-induced increases. Metabonomic analysis of urine from these animals revealed significant differences in the metabolic profiles, with biochemical phenotypes indicative of depression in the non-weaned animals. In addition, non-weaned rats showed resistance to stress-induced modulation of oxytocin receptors in amygdala nuclei, which is indicative of passive stress-coping mechanism. We conclude that delaying weaning results in alterations to the gut microbiota and global metabolic profiles which may contribute to a depressive phenotype and raise the issue that mood disorders at early developmental ages may reflect interplay between mammalian host and resident bacteria.

Does our gut microbiome predict cardiovascular risk? A review of the evidence from metabolomics

Millions of microbes are found in the human gut, and are collectively referred as the gut microbiota. Recent studies have estimated that the microbiota genome contains 100-fold more genes than the host genome. These microbiota contribute to digestion by processing energy substrates unutilized by the host, with about half of the total genome of the gut microbiota being related to central carbon and amino acid metabolism as well as the biosynthesis of secondary metabolites. Therefore, the gut microbiome and its interaction with the host influences many aspects of health and disease, including the composition of biofluids such as urine and blood plasma. Metabolomics is uniquely suited to capture these functional host-microbe interactions. This review aims at providing an overview of recent metabolomics evidence of gut microbiota-host metabolic interactions with a specific focus on cardiovascular disease and related aspects of the metabolic syndrome. Furthermore, the emphasis is given on the complexities of translating these metabolite signatures as potential clinical biomarkers, as the composition and activity of gut microbiome change with many factors, particularly with diet, with special reference to trimethylamine-oxide.

Mass-Spectrometry-Based Serum Metabolomics of a C57BL/6J Mouse Model of High-Fat-Diet-Induced Non-alcoholic Fatty Liver Disease Development

Obesity, dyslipidemia, insulin resistance, oxidative stress, and inflammation are key clinical risk factors for the progression of non-alcoholic fatty liver disease (NAFLD). Currently, there is no comprehensive metabolic profile of a well-established animal model that effectively mimics the etiology and pathogenesis of NAFLD in humans. Here, we report the pathophysiological and metabolomic changes associated with NAFLD development in a C57BL/6J mouse model in which NAFLD was induced by feeding a high-fat diet (HFD) for 4, 8, 12, and 16 weeks. Serum metabolomic analysis was conducted using ultrahigh-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (UHPLC-QTOF-MS) and gas chromatography-mass spectrometry (GC-MS) to establish a metabolomic profile. Analysis of the metabolomic profile in combination with principal component analysis revealed marked differences in metabolites between the control and HFD group depending upon NAFLD severity. A total of 30 potential biomarkers were strongly associated with the development of NAFLD. Among these, 11 metabolites were mainly related to carbohydrate metabolism, hepatic biotransformation, collagen synthesis, and gut microbial metabolism, which are characteristics of obesity, as well as significantly increased serum glucose, total cholesterol, and hepatic triglyceride levels during the onset of NAFLD (4 weeks). At 8 weeks, 5 additional metabolites that are chiefly involved in perturbation of lipid metabolism and insulin secretion were found to be associated with hyperinsulinemia, hyperlipidemia, and hepatic steatosis in the mid-term of NAFLD progression. At the end of 12 and 16 weeks, 14 additional metabolites were predominantly correlated to abnormal bile acid synthesis, oxidative stress, and inflammation, representing hepatic inflammatory infiltration during NAFLD development. These results provide potential biomarkers for early risk assessment of NAFLD and further insights into NAFLD development.

Combined 1H-NMR and 1H-13C HSQC-NMR to improve urinary screening in autism spectrum disorders

Autism spectrum disorders (ASD) are neurodevelopmental diseases with complex genetic and environmental etiological factors. Although genetic causes play a significant part in the etiology of ASD, metabolic disturbances may also play a causal role or modulate the clinical features of ASD. The number of ASD studies involving metabolomics is increasing, and sometime with conflicting findings. We assessed the metabolomics profiling of urine samples to determine a comprehensive biochemical signature of ASD. Furthermore, to date no study has combined metabolic profiles obtained from different analytical techniques to distinguish patient with ASD from healthy individuals. We obtained (1)H-NMR spectra and 2D (1)H-(13)C HSQC NMR spectra from urine samples of patients with ASD or healthy controls. We analyzed these spectra by multivariate statistical data analysis. The OPLS-DA model obtained from (1)H NMR spectra showed a good discrimination between ASD samples and non-ASD samples (R(2)Y(cum) = 0.70 and Q(2) = 0.51). Combining the (1)H NMR spectra and the 2D (1)H-(13)C HSQC NMR spectra increased the overall quality and predictive value of the OPLS-DA model (R(2)Y(cum) = 0.84 and Q(2) = 0.71), leading to a better sensitivity and specificity. Urinary excretion of succinate, glutamate and 3-methyl-histidine differed significantly between ASD and non-ASD samples. Urinary screening of children with neurodevelopmental disorders by combining NMR spectroscopies (1D and 2D) in multivariate analysis is a better sensitive and a straightforward method that could help the diagnosis ASD.

Gastrointestinal dysfunction in autism spectrum disorder: the role of the mitochondria and the enteric microbiome

Autism spectrum disorder (ASD) affects a significant number of individuals worldwide with the prevalence continuing to grow. It is becoming clear that a large subgroup of individuals with ASD demonstrate abnormalities in mitochondrial function as well as gastrointestinal (GI) symptoms. Interestingly, GI disturbances are common in individuals with mitochondrial disorders and have been reported to be highly prevalent in individuals with co-occurring ASD and mitochondrial disease. The majority of individuals with ASD and mitochondrial disorders do not manifest a primary genetic mutation, raising the possibility that their mitochondrial disorder is acquired or, at least, results from a combination of genetic susceptibility interacting with a wide range of environmental triggers. Mitochondria are very sensitive to both endogenous and exogenous environmental stressors such as toxicants, iatrogenic medications, immune activation, and metabolic disturbances. Many of these same environmental stressors have been associated with ASD, suggesting that the mitochondria could be the biological link between environmental stressors and neurometabolic abnormalities associated with ASD. This paper reviews the possible links between GI abnormalities, mitochondria, and ASD. First, we review the link between GI symptoms and abnormalities in mitochondrial function. Second, we review the evidence supporting the notion that environmental stressors linked to ASD can also adversely affect both mitochondria and GI function. Third, we review the evidence that enteric bacteria that are overrepresented in children with ASD, particularly Clostridia spp., produce short-chain fatty acid metabolites that are potentially toxic to the mitochondria. We provide an example of this gut–brain connection by highlighting the propionic acid rodent model of ASD and the clinical evidence that supports this animal model. Lastly, we discuss the potential therapeutic approaches that could be helpful for GI symptoms in ASD and mitochondrial disorders. To this end, this review aims to help better understand the underlying pathophysiology associated with ASD that may be related to concurrent mitochondrial and GI dysfunction.