Multiomic Signatures of Traffic-Related Air Pollution in London Reveal Potential Short-Term Perturbations in Gut Microbiome-Related Pathways.

This randomized crossover study investigated the metabolic and mRNA alterations associated with exposure to high and low traffic-related air pollution (TRAP) in 50 participants who were either healthy or were diagnosed with chronic pulmonary obstructive disease (COPD) or ischemic heart disease (IHD). For the first time, this study combined transcriptomics and serum metabolomics measured in the same participants over multiple time points (2 h before, and 2 and 24 h after exposure) and over two contrasted exposure regimes to identify potential multiomic modifications linked to TRAP exposure. With a multivariate normal model, we identified 78 metabolic features and 53 mRNA features associated with at least one TRAP exposure. Nitrogen dioxide (NO2) emerged as the dominant pollutant, with 67 unique associated metabolomic features. Pathway analysis and annotation of metabolic features consistently indicated perturbations in the tryptophan metabolism associated with NO2 exposure, particularly in the gut-microbiome-associated indole pathway. Conditional multiomics networks revealed complex and intricate mechanisms associated with TRAP exposure, with some effects persisting 24 h after exposure. Our findings indicate that exposure to TRAP can alter important physiological mechanisms even after a short-term exposure of a 2 h walk. We describe for the first time a potential link between NO2 exposure and perturbation of the microbiome-related pathways.

Metabolomic Signatures of Exposure to Nitrate and Trihalomethanes in Drinking Water and Colorectal Cancer Risk in a Spanish Multicentric Study (MCC-Spain).

We investigated the metabolomic profile associated with exposure to trihalomethanes (THMs) and nitrate in drinking water and with colorectal cancer risk in 296 cases and 295 controls from the Multi Case-Control Spain project. Untargeted metabolomic analysis was conducted in blood samples using ultrahigh-performance liquid chromatography-quadrupole time-of-flight mass spectrometry. A variety of univariate and multivariate association analyses were conducted after data quality control, normalization, and imputation. Linear regression and partial least-squares analyses were conducted for chloroform, brominated THMs, total THMs, and nitrate among controls and for case-control status, together with a N-integration model discriminating colorectal cancer cases from controls through interrogation of correlations between the exposure variables and the metabolomic features. Results revealed a total of 568 metabolomic features associated with at least one water contaminant or colorectal cancer. Annotated metabolites and pathway analysis suggest a number of pathways as potentially involved in the link between exposure to these water contaminants and colorectal cancer, including nicotinamide, cytochrome P-450, and tyrosine metabolism. These findings provide insights into the underlying biological mechanisms and potential biomarkers associated with water contaminant exposure and colorectal cancer risk. Further research in this area is needed to better understand the causal relationship and the public health implications.

Metabolic network construction reveals probiotic-specific alterations in the metabolic activity of a synthetic small intestinal community.

IMPORTANCE: The development of probiotic therapies targeted at the small intestinal microbiota represents a significant advancement in the field of probiotic interventions. This region poses unique opportunities due to its low number of gut microbiota, along with the presence of heightened immune and metabolic host responses. However, progress in this area has been hindered by a lack of detailed understanding regarding the molecular mechanisms through which probiotics exert their effects in the small intestine. Our study, utilizing a synthetic community of three small intestinal bacterial strains and the addition of two different probiotic species, and kynurenine as a representative dietary or endogenously produced compound, highlights the importance of selecting probiotic species with diverse genetic capabilities that complement the functional capacity of the resident microbiota, or alternatively, constructing a multispecies formula. This approach holds great promise for the development of effective probiotic therapies and underscores the need to consider the functional capacity of probiotic species when designing interventions.

Biological Relevance of Goat Milk Oligosaccharides to Infant Health.

Milk is often regarded as the gold standard for the nourishment of all mammalian offspring. The World Health Organization (WHO) recommends exclusive breastfeeding for the first 6 months of the life of the infant, followed by a slow introduction of complementary foods to the breastfeeding routine for a period of approximately 2 years, whenever this is possible ( Global Strategy for Infant and Young Child Feeding; WHO, 2003). One of the most abundant components in all mammals' milk, which is associated with important health benefits, is the oligosaccharides. The milk oligosaccharides (MOS) of humans and other mammals differ in terms of their concentration and diversity. Among those, goat milk contains more oligosaccharides (gMOS) than other domesticated dairy animals, as well as a greater range of structures. This review summarizes the biological functions of MOS found in both human and goat milk to identify the possible biological relevance of gMOS in human health and development. Based on the existing literature, seven biological functions of gMOS were identified, namely, MOS action as prebiotics, immune modulators, and pathogen traps; their modulation of intestinal cells; protective effect against necrotizing enterocolitis; improved brain development; and positive effects on stressor exposure. Overall, goat milk is a viable alternate supply of functional MOS that could be employed in a newborn formula.

Altered plasma metabolite levels can be detected years before a glioma diagnosis.

Genetic and metabolic changes in tissue and blood are reported to occur several years before glioma diagnosis. Since gliomas are currently detected late, a liquid biopsy for early detection could affect the quality of life and prognosis of patients. Here, we present a nested case-control study of 550 prediagnostic glioma cases and 550 healthy controls from the Northern Sweden Health and Disease study (NSHDS) and the European Prospective Investigation into Cancer and Nutrition (EPIC) study. We identified 93 significantly altered metabolites related to glioma development up to 8 years before diagnosis. Out of these metabolites, a panel of 20 selected metabolites showed strong disease correlation and a consistent progression pattern toward diagnosis in both the NSHDS and EPIC cohorts, and they separated future cases from controls independently of biological sex. The blood metabolite panel also successfully separated both lower-grade glioma and glioblastoma cases from controls, up to 8 years before diagnosis in patients within the NSHDS cohort and up to 2 years before diagnosis in EPIC. Pathway enrichment analysis detected metabolites related to the TCA cycle, Warburg effect, gluconeogenesis, and cysteine, pyruvate, and tyrosine metabolism as the most affected.

Dynamic effects of probiotic formula ecologic®825 on human small intestinal ileostoma microbiota: a network theory approach.

The gut microbiota plays a pivotal role in health and disease. The use of probiotics as microbiota-targeted therapies is a promising strategy to improve host health. However, the molecular mechanisms involved in such therapies are often not well understood, particularly when targeting the small intestinal microbiota. In this study, we investigated the effects of a probiotic formula (Ecologic®825) on the adult human small intestinal ileostoma microbiota. The results showed that supplementation with the probiotic formula led to a reduction in the growth of pathobionts, such as Enterococcaceae and Enterobacteriaceae, and a decrease in ethanol production. These changes were associated with significant alterations in nutrient utilization and resistance to perturbations. These probiotic mediated alterations which coincided with an initial increase in lactate production and decrease in pH were followed by a sharp increase in the levels of butyrate and propionate. Moreover, the probiotic formula increased the production of multiple N-acyl amino acids in the stoma samples. The study demonstrates the utility of network theory in identifying novel microbiota-targeted therapies and improving existing ones. Overall, the findings provide insights into the dynamic molecular mechanisms underlying probiotic therapies, which can aid in the development of more effective treatments for a range of conditions.

Analysis, Stability and Distribution of Pharmaceuticals and Drugs of Abuse over a Period of One Year in Formalin-Fixed Liver and Formalin Solutions.

The present study reports a thorough research on the stability of drugs of abuse and pharmaceuticals over a time period of 12 months. Fixed-liver tissues and formalin solutions where the tissues were preserved were analyzed using an ultra high performance liquid chromatography--tandem mass spectrometry method that has been developed and validated for this purpose. The method monitors 84 drugs in a 13-minute run. The concentrations of the drugs found were compared with their concentrations determined in the fresh liver tissues in a previous study. In the study, 14 cases with forensic interest were included with the main objective of the analysis and the study of the stability and the distribution of drugs of abuse and pharmaceuticals in the human liver and the formalin solution during preservation. The results showed that the number of detected compounds in the first month was significantly lower than the compounds found in fresh tissues. The effect of formalin was catalytic, and few substances could be detected. Specifically, out of the 86 positive detections of the monitored substances in the fresh tissues (in which 25 different substances were found), only 32 (37%) remained detectable 3 months after, 20 (23%) 6 months after and 15 (17%) 12 months after.

Metabolomic profiles of metformin in breast cancer survivors: a pooled analysis of plasmas from two randomized placebo-controlled trials.

BACKGROUND: Obesity is a major health concern for breast cancer survivors, being associated with high recurrence and reduced efficacy during cancer treatment. Metformin treatment is associated with reduced breast cancer incidence, recurrence and mortality. To better understand the underlying mechanisms through which metformin may reduce recurrence, we aimed to conduct metabolic profiling of overweight/obese breast cancer survivors before and after metformin treatment. METHODS: Fasting plasma samples from 373 overweight or obese breast cancer survivors randomly assigned to metformin (n = 194) or placebo (n = 179) administration were collected at baseline, after 6 months (Reach For Health trial), and after 12 months (MetBreCS trial). Archival samples were concurrently analyzed using three complementary methods: untargeted LC-QTOF-MS metabolomics, targeted LC-MS metabolomics (AbsoluteIDQ p180, Biocrates), and gas chromatography phospholipid fatty acid assay. Multivariable linear regression models and family-wise error correction were used to identify metabolites that significantly changed after metformin treatment. RESULTS: Participants (n = 352) with both baseline and study end point samples available were included in the analysis. After adjusting for confounders such as study center, age, body mass index and false discovery rate, we found that metformin treatment was significantly associated with decreased levels of citrulline, arginine, tyrosine, caffeine, paraxanthine, and theophylline, and increased levels of leucine, isoleucine, proline, 3-methyl-2-oxovalerate, 4-methyl-2-oxovalerate, alanine and indoxyl-sulphate. Long-chain unsaturated phosphatidylcholines (PC ae C36:4, PC ae C38:5, PC ae C36:5 and PC ae C38:6) were significantly decreased with the metformin treatment, as were phospholipid-derived long-chain n-6 fatty acids. The metabolomic profiles of metformin treatment suggest change in specific biochemical pathways known to impair cancer cell growth including activation of CYP1A2, alterations in fatty acid desaturase activity, and altered metabolism of specific amino acids, including impaired branched chain amino acid catabolism. CONCLUSIONS: Our results in overweight breast cancer survivors identify new metabolic effects of metformin treatment that may mechanistically contribute to reduced risk of recurrence in this population and reduced obesity-related cancer risk reported in observational studies. TRIAL REGISTRATION: ClinicalTrials.gov identifier: NCT01302379 and EudraCT Protocol #: 2015-001001-14.

Metabolic phenotyping reveals a potential link between elevated faecal amino acids, diet and symptom severity in individuals with severe mental illness.

The brain-gut axis is increasingly recognized as an important contributing factor in the onset and progression of severe mental illnesses such as schizophrenia spectrum disorders and bipolar disorder. This study investigates associations between levels of faecal metabolites identified using 1H-NMR, clinical parameters, and dietary components of forty-two individuals diagnosed in a transdiagnostic approach to have severe mental illness. Faecal levels of the amino acids; alanine, leucine, and valine showed a significant positive correlation with psychiatric symptom severity as well as with dairy intake. Overall, this study proposes a diet-induced link between the brain-gut axis and the severity of psychiatric symptoms, which could be valuable in the design of novel dietary or therapeutic interventions to improve psychiatric symptoms.

Extraction and Quantitative Analysis of Goat Milk Oligosaccharides: Composition, Variation, Associations, and 2'-FL Variability.

Human milk oligosaccharides (hMOS) are associated with health benefits for newborns. We studied the composition of goat MOS (gMOS) from colostrum up to the 9th month of lactation to conceive an overview of the structures present and their fate. Potential correlations with factors such as age, parity, and lifetime milk production were examined. An effective method for gMOS extraction and ultra-high-performance liquid chromatography coupled to fluorescence detection (UPLC-FLD) analysis was established, following 2-aminobenzamide gMOS labeling. Considerable biological variability was highlighted among the 12 quantified gMOS and the 9 non-quantified structures in the individual milk samples. Most characteristic, 2'-fucosyllactose was present in 73.7% of the milk samples analyzed, suggesting the possibility of a secretor/non-secretor goat genotype, similar to humans. Contributing factors to the observed biological variability were goat age, parity, lifetime milk production, and the kids' sex. The results significantly contribute to the current understanding of (variations in) gMOS composition.

Goat Milk Oligosaccharides: Their Diversity, Quantity, and Functional Properties in Comparison to Human Milk Oligosaccharides.

Human milk is considered the golden standard in infant nutrition. Free oligosaccharides in human milk provide important health benefits. These oligosaccharides function as prebiotics, immune modulators, and pathogen inhibitors and were found to improve barrier function in the gut. Infant formulas nowadays often contain prebiotics but lack the specific functions of human milk oligosaccharides (hMOS). Milk from domesticated animals also contains milk oligosaccharides but at much lower levels and with less diversity. Goat milk contains significantly more oligosaccharides (gMOS) than bovine (bMOS) or sheep (sMOS) milk and also has a larger diversity of structures. This review summarizes structural studies, revealing a diversity of up to 77 annotated gMOS structures with almost 40 structures fully characterized. Quantitative studies of goat milk oligosaccharides range from 60 to 350 mg/L in mature milk and from 200 to 650 mg/L in colostrum. These levels are clearly lower than in human milk (5-20 g/L) but higher than in other domesticated dairy animals, e.g., bovine (30-60 mg/L) and sheep (20-40 mg/L). Finally, the review focuses on demonstrated and potential functionalities of gMOS. Some studies have shown anti-inflammatory effects of mixtures enriched in gMOS. Goat MOS also display prebiotic potential, particularly in stimulating growth of bifidobacteria preferentially. Although functional studies of gMOS are still limited, several structures are also found in human milk and have known functions as immune modulators and pathogen inhibitors. In conclusion, goat milk constitutes a promising alternative source for milk oligosaccharides, which can be used in infant formula.

A pilot case-control study of urine metabolomics in preterm neonates with necrotizing enterocolitis.

Necrotizing enterocolitis (NEC) is a leading cause of gastrointestinal morbidity and mortality in preterm neonates. The aim of this pilot study was to explore using metabolomics alternations in the urine metabolites related to NEC that could possibly serve as diagnostic biomarkers of the disease. Urine samples were prospectively collected at the day of initial evaluation for NEC from 15 diseased preterm neonates (five Bell's stage I and ten stage II/III) and an equal number of matched controls. Urine metabolic profiles were assessed using non-targeted nuclear magnetic resonance spectroscopy and targeted liquid chromatography-tandem mass spectrometry monitoring 108 metabolites. Multivariate statistical models with data from either analytical approach showed clear separation between the metabolic profiles of neonates with NEC and controls. Twenty-five discriminant metabolites were identified belonging to amino and organic acids, sugars and vitamins. A number of metabolite combinations were found to have an excellent diagnostic performance in detecting neonates developing NEC. Our results show that the metabolic profile of neonates with NEC differs significantly from that of controls, making possible their separation using urine metabolomic analysis. Nevertheless, whether the small set of significant metabolites detected in this investigation could be used as early diagnostic biomarkers of NEC should be validated in larger studies.

Targeted LC-MS/MS for the evaluation of proteomics biomarkers in the blood of neonates with necrotizing enterocolitis and late-onset sepsis.

Late-onset sepsis (LOS) and necrotizing enterocolitis (NEC) are severe life-threatening conditions for neonates. Accurate, early diagnosis and timely initiation of treatment are crucial. Non-specific overlapping clinical signs along with the non-sensitive/specific diagnostic tools set obstacles to speedy, trustful diagnosis including differential diagnosis. The objective of this study was to evaluate the potential of targeted LC-MS/MS proteomics in identifying diagnostic biomarkers of NEC or LOS. We conducted a prospective case-control study evaluating serum proteomics profiles of 25 NEC, 18 LOS, and an equal number of matched control neonates, over three sampling points. Eighty-three concatemers and synthetic peptides belonging to 47 protein markers of the two diseases were selected after thorough literature search. A novel selected reaction monitoring (SRM), LC-MS/MS method was developed for their analysis and evaluation as potential biomarkers. Multivariate and univariate statistical analyses highlighted significant proteins in differentiating LOS and NEC neonates and diseased from controls. Moreover, panels of proteins were tested for their ability to distinguish LOS from NEC and controls. We suggest two panels of three proteins each, exhibiting very high diagnostic value for LOS and excellent diagnostic performance at the critical LOS-NEC differentiation, reaching an AUC ROC value close to 1 (0.999). These panels constitute a valuable starting point for further validation with broader cohorts of neonates, aiming to improve the clinical practice. Graphical abstract ᅟ.

1H NMR-based metabolomics reveals the effect of maternal habitual dietary patterns on human amniotic fluid profile.

Maternal diet may influence offspring's health, even within well-nourished populations. Amniotic fluid (AF) provides a rational compartment for studies on fetal metabolism. Evidence in animal models indicates that maternal diet affects AF metabolic profile; however, data from human studies are scarce. Therefore, we have explored whether AF content may be influenced by maternal diet, using a validated food-frequency questionnaire and implementing NMR-based metabolomics. Sixty-five AF specimens, from women undergoing second-trimester amniocentesis for prenatal diagnosis, were analysed. Complementary, maternal serum and urine samples were profiled. Hierarchical cluster analysis identified 2 dietary patterns, cluster 1 (C1, n = 33) and cluster 2 (C2, n = 32). C1 was characterized by significantly higher percentages of energy derived from refined cereals, yellow cheese, red meat, poultry, and "ready-to-eat" foods, while C2 by higher (P < 0.05) whole cereals, vegetables, fruits, legumes, and nuts. 1H NMR spectra allowed the identification of metabolites associated with these dietary patterns; glucose, alanine, tyrosine, valine, citrate, cis-acotinate, and formate were the key discriminatory metabolites elevated in C1 AF specimens. This is the first evidence to suggest that the composition of AF is influenced by maternal habitual dietary patterns. Our results highlight the need to broaden the knowledge on the importance of maternal nutrition during pregnancy.

Urine metabolomics in neonates with late-onset sepsis in a case-control study.

Although late-onset sepsis (LOS) is a major cause of neonatal morbidity and mortality, biomarkers evaluated in LOS lack high diagnostic accuracy. In this prospective, case-control, pilot study, we aimed to determine the metabolic profile of neonates with LOS. Urine samples were collected at the day of initial LOS evaluation, the 3rd and 10th day, thereafter, from 16 septic neonates (9 confirmed and 7 possible LOS cases) and 16 non-septic ones (controls) at respective time points. Urine metabolic profiles were assessed using non-targeted nuclear magnetic resonance spectroscopy and targeted liquid chromatography-tandem mass spectrometry analysis. Multivariate statistical models with data from either analytical approach showed clear separation between the metabolic profiles of septic neonates (both possible and confirmed) and the controls. Metabolic changes appeared to be related to disease progression. Overall, neonates with confirmed or possible LOS exhibited comparable metabolic profiles indicating similar metabolic alternations upon the onset of clinical manifestations. This methodology therefore enabled the discrimination of neonates with LOS from non-septic individuals, providing potential for further research toward the discovery of LOS-related biomarkers.

Investigation of the derivatization conditions for GC-MS metabolomics of biological samples.

AIM: Metabolomics applications represent an emerging field where significant efforts are directed. Derivatization consists prerequisite for GC-MS metabolomics analysis. METHODS: Common silylation agents were tested for the derivatization of blood plasma. Optimization of methoxyamination and silylation reactions was performed on a mixture of reference standards, consisting of 46 different metabolites. Stability of derivatized metabolites was tested at 4°C. RESULTS: Optimum results were achieved using N-methyl-N-(trimethylsilyl)trifluoroacetamide. Methoxyamination at room temperature for 24 h followed by 2-h silylation at high temperature lead to efficient derivatization. CONCLUSION: Formation and stability of derivatives among metabolites differ greatly, so derivatization should be studied before application in metabolomics studies.

Sample preparation optimization in fecal metabolic profiling.

Metabolomic analysis of feces can provide useful insight on the metabolic status, the health/disease state of the human/animal and the symbiosis with the gut microbiome. As a result, recently there is increased interest on the application of holistic analysis of feces for biomarker discovery. For metabolomics applications, the sample preparation process used prior to the analysis of fecal samples is of high importance, as it greatly affects the obtained metabolic profile, especially since feces, as matrix are diversifying in their physicochemical characteristics and molecular content. However there is still little information in the literature and lack of a universal approach on sample treatment for fecal metabolic profiling. The scope of the present work was to study the conditions for sample preparation of rat feces with the ultimate goal of the acquisition of comprehensive metabolic profiles either untargeted by NMR spectroscopy and GC-MS or targeted by HILIC-MS/MS. A fecal sample pooled from male and female Wistar rats was extracted under various conditions by modifying the pH value, the nature of the organic solvent and the sample weight to solvent volume ratio. It was found that the 1/2 (wf/vs) ratio provided the highest number of metabolites under neutral and basic conditions in both untargeted profiling techniques. Concerning LC-MS profiles, neutral acetonitrile and propanol provided higher signals and wide metabolite coverage, though extraction efficiency is metabolite dependent.

Global Metabolic Stress of Isoeffort Continuous and High Intensity Interval Aerobic Exercise: A Comparative 1H NMR Metabonomic Study.

The overall metabolic/energetic stress that occurs during an acute bout of exercise is proposed to be the main driving force for long-term training adaptations. Continuous and high-intensity interval exercise protocols (HIIE) are currently prescribed to acquire the muscular and metabolic benefits of aerobic training. We applied 1H NMR-based metabonomics to compare the overall metabolic perturbation and activation of individual bioenergetic pathways of three popular aerobic exercises matched for effort/strain. Nine men performed continuous, long-interval (3 min), and short-interval (30 s) bouts of exercise under isoeffort conditions. Blood was collected before and after exercise. The multivariate PCA and OPLS-DA models showed a distinct separation of pre- and postexercise samples in three protocols. The two models did not discriminate the postexercise overall metabolic profiles of the three exercise types. Analysis focused on muscle bioenergetic pathways revealed an extensive upregulation of carbohydrate-lipid metabolism and the TCA cycle in all three protocols; there were only a few differences among protocols in the postexercise abundance of molecules when long-interval bouts were performed. In conclusion, continuous and HIIE exercise protocols, when performed with similar effort/strain, induce comparable global metabolic response/stress despite their marked differences in work-bout intensities. This study highlights the importance of NMR metabonomics in comprehensive monitoring of metabolic consequences of exercise training in the blood of athletes and exercising individuals.

GC-MS analysis of blood for the metabonomic investigation of the effects of physical exercise and allopurinol administration on rats.

Exhaustive exercise is a generator of free radicals and reactive species in mammals. Allopurinol is a known inhibitor of xanthine oxidase, a source of free radicals during exercise. In this study, the influence of allopurinol on the metabolic profile of blood plasma of rats that had undergone exhaustive swimming was investigated by GC-MS. Rats were divided into four groups: (i) placebo administration, no exercise; (ii) placebo administration followed by exercise until exhaustion; (iii) allopurinol administration, no exercise; and (iv) allopurinol administration followed by exercise until exhaustion. Samples obtained following the aforementioned treatments were analyzed on GC-MS after two-step derivatization (methoxymation and silylation). GC-MS analysis in full scan acquisition achieved the quantitation of 86 metabolites in 45min. GC-MS data were analyzed using univariate and multivariate statistical analysis methods. Safe classification/prediction of the samples was accomplished according to exercise and allopurinol administration. Separation of the study groups according to exercise was mainly due to lactic acid, pyruvic acid, 2-hydroxybutyric acid, uracil, oxalic acid, pyroglutamic acid and stearic acid (p<0.05). Separation according to allopurinol administration was mainly due to compounds of the purine catabolic pathway and amino acids. Allopurinol administration was not found to modulate the metabolic responses to exercise.