Longitudinal relationship of amino acids and indole metabolites with long-term body mass index and cardiometabolic risk markers in young individuals

In-depth multiomic characterization of the effects of obesity in high-fat diet-fed mice

High-fat diet (HFD)-fed mice have been widely used in the clinical investigation of obesity. However, the long-term effect of HFD on gut microbiota and metabolites, plasma and liver metabolomics, colonic and liver transcriptomics remain largely unknown. In this study, 6-week-old C57BL/6J male mice fed with HFD for 14 weeks showed increased obesity-related indexes including alanine aminotransferase, aspartate aminotransferase, total cholesterol, total triglyceride, free fatty acids, lipopolysaccharides, IL-6, and TNFα. Furthermore, microbial diversity and richness were also significantly decreased. In the colon, genes involved in tryptophan metabolism, PPAR signaling pathway, cholesterol metabolism, and lipid localization and transport, were upregulated. While in the liver, MAPK signaling and unsaturated fatty acid biosynthesis were upregulated. Metabolomic analyses revealed decreased levels of glycerophospholipids and fatty acyl, but increased amino acids, coenzymes and vitamins, and organic acids in the colon, suggesting high absorption of oxidized lipids, while acyl-carnitine, lysophosphatidylcholine, lysophosphatidylethanolamine, and oxidized lipids were reduced in the liver, suggesting a more active lipid metabolism. Finally, correlation analyses revealed a positive correlation between gut microbiota and metabolites and the expression of genes associated with lipid localization, absorption, and transport in the colon, and nutrients and energy metabolism in the liver. Taken together, our results provide a comprehensive characterization of long-term HFD-induced obesity in mice.

Cohort profile update-overview of over 35 years of research in the Dortmund Nutritional and Anthropometric Longitudinally Designed (DONALD) study

PURPOSE

To provide an update on the cohort profile of the DOrtmund Nutritional and Anthropometric Longitudinally Designed (DONALD) study, including objectives, study design, methods and description of the comprehensive data pool, as well as to summarize the most important research findings of recent years.

METHODS

In 1985, the open (dynamic) cohort started to collect information on diet, growth, development, and metabolism of healthy children and adolescents in Dortmund, Germany. Detailed data are collected annually during infancy, childhood, and adolescence of the participants, including a 3-day weighed dietary record, a 24-h urine sample, anthropometric and medical examinations as well as interviews on lifestyle.

RESULTS

Even if the basic examination modules have not changed since the start over 35 years ago, the DONALD study has been continuously further developed by introducing new modules. As such, participants are also invited for follow-up examinations during adulthood since 2005, including an additional fasting blood withdrawal. Overall, 2375 (♂: 1177; ♀: 1198) participants were recruited in the DONALD study between 1985 and 2022. Data from ~ 30,700 anthropometric measurements, ~ 19,200 dietary records, ~ 10,600 24-h urine and ~ 1300 blood samples are available from an observation period of over 35 years.

CONCLUSION

The DONALD study provides a large data pool for longitudinal studies on nutrition, growth, and health in childhood and adolescence, its impact on the development of diseases in early adult life as well as dietary intake trends over more than three decades.

A novel preliminary metabolomic panel for IHD diagnostics and pathogenesis

Cardiovascular disease (CVD) represents one of the main causes of mortality worldwide and nearly a half of it is related to ischemic heart disease (IHD). The article represents a comprehensive study on the diagnostics of IHD through the targeted metabolomic profiling and machine learning techniques. A total of 112 subjects were enrolled in the study, consisting of 76 IHD patients and 36 non-CVD subjects. Metabolomic profiling was conducted, involving the quantitative analysis of 87 endogenous metabolites in plasma. A novel regression method of age-adjustment correction of metabolomics data was developed. We identified 36 significantly changed metabolites which included increased cystathionine and dimethylglycine and the decreased ADMA and arginine. Tryptophan catabolism pathways showed significant alterations with increased levels of serotonin, intermediates of the kynurenine pathway and decreased intermediates of indole pathway. Amino acid profiles indicated elevated branched-chain amino acids and increased amino acid ratios. Short-chain acylcarnitines were reduced, while long-chain acylcarnitines were elevated. Based on these metabolites data, machine learning algorithms: logistic regression, support vector machine, decision trees, random forest, and gradient boosting, were used for IHD diagnostic models. Random forest demonstrated the highest accuracy with an AUC of 0.98. The metabolites Norepinephrine; Xanthurenic acid; Anthranilic acid; Serotonin; C6-DC; C14-OH; C16; C16-OH; GSG; Phenylalanine and Methionine were found to be significant and may serve as a novel preliminary panel for IHD diagnostics. Further studies are needed to confirm these findings.

The Beneficial Effects of Dietary Astragali Radix Are Related to the Regulation of Gut Microbiota and Its Metabolites

Astragali Radix (AR) or its extract has been used as an herbal medicine and dietary supplement in China, Europe, and the United States. The gut microbiota could provide new insights for exploring dietary supplements' underlying mechanism on organisms. However, no reports have focused on the regulatory effect of AR on the gut microbiota as a dietary supplement. In this study, healthy ICR mice of either sex were divided into AR and control (CON) groups and given AR water extract (4.55 mg/kg·day-1) or saline by gavage for 14 days, respectively. Then 16S rRNA gene sequencing and ultra-high-performance liquid chromatography quadrupole time-of-flight tandem mass spectrometry-based fecal metabolomics were integrated to investigate the benefits of dietary AR. Weighted gene coexpression network analysis was also introduced to investigate the metabolites with highly synergistic changes. AR supplementation influenced the structure of intestinal microflora, especially enriching short-chain fatty acid-producing bacteria g_Coprobacillus, g_Prevotella, and g_Parabacteroides. AR also significantly altered the fecal metabolome, mainly related to amino acid metabolism, nucleotide metabolism, and bile acid (BA) metabolism. Moreover, the increased secondary BAs and BA-sulfates might closely relate to intestinal microflora. These findings provide valuable insights for future research of dietary AR as a functional food.

The Influence of Probiotic Supplementation on the Obesity Indexes, Neuroinflammatory and Oxidative Stress Markers, Gut Microbial Diversity, and Working Memory in Obese Thai Children

Obesity is a worldwide health problem with a complex interaction between gut microbiota and cognition. Several studies have demonstrated that probiotic treatments improve characteristics linked to obesity. The present study aimed to evaluate the effects of probiotic supplementation on the obesity indexes, inflammatory and oxidative stress markers, gut microbiota, and working memory in obese children. Ten obese children were assigned to receive the probiotics (8 × 109 CFU of Lactobacillus paracasei HII01 and Bifidobacterium animalis subsp. lactis) for 12 weeks. Demographic data were recorded. Urine and fecal samples were collected to evaluate biomarkers related to obesity and cognition. Behavioral working memory was assessed using the visual n-back test. Electroencephalography was employed to measure electrical activity during the visual n-back test. All parameters were evaluated at the baseline and after 12 weeks. The results revealed that probiotic supplementation significantly altered some gut microbial metabolites, gut microbiota, total antioxidant capacity, and neuroinflammatory markers. However, no significant changes were observed in the visual n-back test or electroencephalographic recordings after 12 weeks. In conclusion, the use of probiotics might be an alternative treatment that could improve the gut microbial ecosystem and microbial metabolites, as well as host antioxidant and neuroinflammation levels. The preliminary results indicated that further detailed prolonged studies are needed in order to determine the beneficial effects of the studied probiotics.

An Investigation into the Relationship of Circulating Gut Microbiome Molecules and Inflammatory Markers with the Risk of Incident Dementia in Later Life

The gut microbiome may be involved in the occurrence of dementia primarily through the molecular mechanisms of producing bioactive molecules and promoting inflammation. Epidemiological evidence linking gut microbiome molecules and inflammatory markers to dementia risk has been mixed, and the intricate interplay between these groups of biomarkers suggests that their joint investigation in the context of dementia is warranted. We aimed to simultaneously investigate the association of circulating levels of selected gut microbiome molecules and inflammatory markers with dementia risk. This case-cohort epidemiological study included 805 individuals (83 years, 66% women) free of dementia at baseline. Plasma levels of 19 selected gut microbiome molecules comprising lipopolysaccharide, short-chain fatty acids, and indole-containing tryptophan metabolites as well as four inflammatory markers measured at baseline were linked to incident all-cause (ACD) and Alzheimer's disease dementia (AD) in binary outcomes and time-to-dementia analyses. Independent of several covariates, seven gut microbiome molecules, 5-hydroxyindole-3-acetic acid, indole-3-butyric acid, indole-3-acryloylglycine, indole-3-lactic acid, indole-3-acetic acid methyl ester, isobutyric acid, and 2-methylbutyric acid, but no inflammatory markers discriminated incident dementia cases from non-cases. Furthermore, 5-hydroxyindole-3-acetic acid (hazard ratio: 0.58; 0.36-0.94, P = 0.025) was associated with time-to-ACD. These molecules underpin gut microbiome-host interactions in the development of dementia and they may be crucial in its prevention and intervention strategies. Future larger epidemiological studies are needed to confirm our findings, specifically in exploring the repeatedly measured circulating levels of these molecules and investigating their causal relationship with dementia risk.

Replication and mediation of the association between the metabolome and clinical markers of metabolic health in an adolescent cohort study

Metabolomics-derived metabolites (henceforth metabolites) may mediate the relationship between modifiable risk factors and clinical biomarkers of metabolic health (henceforth clinical biomarkers). We set out to study the associations of metabolites with clinical biomarkers and a potential mediation effect in a population of young adults. First, we conducted a systematic literature review searching for metabolites associated with 11 clinical biomarkers (inflammation markers, glucose, blood pressure or blood lipids). Second, we replicated the identified associations in a study population of n = 218 (88 males and 130 females, average age of 18 years) participants of the DONALD Study. Sex-stratified linear regression models adjusted for age and BMI and corrected for multiple testing were calculated. Third, we investigated our previously reported metabolites associated with anthropometric and dietary factors mediators in sex-stratified causal mediation analysis. For all steps, both urine and blood metabolites were considered. We found 41 metabolites in the literature associated with clinical biomarkers meeting our inclusion criteria. We were able to replicate an inverse association of betaine with CRP in women, between body mass index and C-reactive protein (CRP) and between body fat and leptin. There was no evidence of mediation by lifestyle-related metabolites after correction for multiple testing. We were only able to partially replicate previous findings in our age group and did not find evidence of mediation. The complex interactions between lifestyle factors, the metabolome, and clinical biomarkers warrant further investigation.

Effects of sea salt intake on metabolites, steroid hormones, and gut microbiota in rats

High salt intake is positively linked to many health problems, but the effect of mineral-rich sea salt (SS) has rarely been studied. To better understand the physiological effects of SS intake, the changes in general characteristics, metabolites, steroid hormones, and gut microbiota of SS-fed rats were investigated. Male rats were fed either a normal diet (ND, control) or ND containing 1% SS or 4% SS for 5 weeks. SS intake decreased fat, spleen, liver, and body weight, and increased blood urea nitrogen (BUN), water intake, and gut salt content. Accumulated gut salt content led to a decrease in beneficial bacteria, such as Lachnospiraceae and Lactobacillus, but an increase in potentially harmful bacteria, resulting in a change in lipid metabolites associated with gut health. Interestingly, most renal lysophosphatidylcholines (LPCs) associated with many renal functions were dramatically decreased and female hormones, such as estrogens, were significantly more altered than the male hormones by high SS intake. Although further investigation is needed, these data suggest that high SS intake could be positively linked to kidney dysfunction and gut health problems, and salt-related physiological changes may be sex-specific. Additionally, these data will be useful to better under-stand the physiological effects of SS intake.

Unlocking the Potential of the Human Microbiome for Identifying Disease Diagnostic Biomarkers

The human microbiome encodes more than three million genes, outnumbering human genes by more than 100 times, while microbial cells in the human microbiota outnumber human cells by 10 times. Thus, the human microbiota and related microbiome constitute a vast source for identifying disease biomarkers and therapeutic drug targets. Herein, we review the evidence backing the exploitation of the human microbiome for identifying diagnostic biomarkers for human disease. We describe the importance of the human microbiome in health and disease and detail the use of the human microbiome and microbiota metabolites as potential diagnostic biomarkers for multiple diseases, including cancer, as well as inflammatory, neurological, and metabolic diseases. Thus, the human microbiota has enormous potential to pave the road for a new era in biomarker research for diagnostic and therapeutic purposes. The scientific community needs to collaborate to overcome current challenges in microbiome research concerning the lack of standardization of research methods and the lack of understanding of causal relationships between microbiota and human disease.

Analyzing the Systems Biology Effects of COVID-19 mRNA Vaccines to Assess Their Safety and Putative Side Effects

COVID-19 vaccines have been instrumental tools in reducing the impact of SARS-CoV-2 infections around the world by preventing 80% to 90% of hospitalizations and deaths from reinfection, in addition to preventing 40% to 65% of symptomatic illnesses. However, the simultaneous large-scale vaccination of the global population will indubitably unveil heterogeneity in immune responses as well as in the propensity to developing post-vaccine adverse events, especially in vulnerable individuals. Herein, we applied a systems biology workflow, integrating vaccine transcriptional signatures with chemogenomics, to study the pharmacological effects of mRNA vaccines. First, we derived transcriptional signatures and predicted their biological effects using pathway enrichment and network approaches. Second, we queried the Connectivity Map (CMap) to prioritize adverse events hypotheses. Finally, we accepted higher-confidence hypotheses that have been predicted by independent approaches. Our results reveal that the mRNA-based BNT162b2 vaccine affects immune response pathways related to interferon and cytokine signaling, which should lead to vaccine success, but may also result in some adverse events. Our results emphasize the effects of BNT162b2 on calcium homeostasis, which could be contributing to some frequently encountered adverse events related to mRNA vaccines. Notably, cardiac side effects were signaled in the CMap query results. In summary, our approach has identified mechanisms underlying both the expected protective effects of vaccination as well as possible post-vaccine adverse effects. Our study illustrates the power of systems biology approaches in improving our understanding of the comprehensive biological response to vaccination against COVID-19.

Genome-scale metabolic modelling of the human gut microbiome reveals changes of the glyoxylate and dicarboxylate metabolism in metabolic disorders

The human gut microbiome has been associated with metabolic disorders including obesity, type 2 diabetes, and atherosclerosis. Understanding the contribution of microbiome metabolic changes is important for elucidating the role of gut bacteria in regulating metabolism. We used available metagenomics data from these metabolic disorders, together with genome-scale metabolic modeling of key bacteria in the individual and community-level to investigate the mechanistic role of the gut microbiome in metabolic diseases. Modeling predicted increased levels of glutamate consumption along with the production of ammonia, arginine, and proline in gut bacteria common across the disorders. Abundance profiles and network-dependent analysis identified the enrichment of tartrate dehydrogenase in the disorders. Moreover, independent plasma metabolite levels showed associations between metabolites including proline and tyrosine and an increased tartrate metabolism in healthy obese individuals. We, therefore, propose that an increased tartrate metabolism could be a significant mediator of the microbiome metabolic changes in metabolic disorders.

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Metagenomic analysis highlights key common bacterial species across metabolic diseases

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Metabolic models showed higher levels of acetate produced by disease enriched bacteria

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Reaction analysis revealed increases in the glyoxylate and dicarboxylate pathway

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Metabolomics and modeling analysis showed the potential role of tartrate metabolism

Bidirectional Cell-Cell Communication via Indole and Cyclo(Pro-Tyr) Modulates Interspecies Biofilm Formation

The extracellular signaling molecule indole plays a pivotal role in biofilm formation by the enteric gammaproteobacterium Escherichia coli; this process is particularly correlated with the extracellular indole concentration. Using the indole-biodegrading betaproteobacterium Burkholderia unamae, we examined the mechanism by which these two bacteria modulate biofilm formation in an indole-dependent manner. We quantified the spatial organization of cocultured microbial communities at the micrometer scale through computational image analysis, ultimately identifying how bidirectional cell-to-cell communication modulated the physical relationships between them. Further analysis allowed us to determine the mechanism by which the B. unamae-derived signaling diketopiperazine cyclo(Pro-Tyr) considerably upregulated indole biosynthesis and enhanced E. coli biofilm formation. We also determined that the presence of unmetabolized indole enhanced the production of cyclo(Pro-Tyr). Thus, bidirectional cell-to-cell communication that occurred via interspecies signaling molecules modulated the formation of a mixed-species biofilm between indole-producing and indole-consuming species. IMPORTANCE Indole is a relatively stable N-heterocyclic aromatic compound that is widely found in nature. To date, the correlations between indole-related bidirectional cell-to-cell communications and interspecies communal organization remain poorly understood. In this study, we used an experimental model, which consisted of indole-producing and indole-degrading bacteria, to evaluate how bidirectional cell-to-cell communication modulated interspecies biofilm formation via intrinsic and environmental cues. We identified a unique spatial patterning of indole-producing and indole-degrading bacteria within mixed-species biofilms. This spatial patterning was an active process mediated by bidirectional physicochemical interactions. Our findings represent an important step in gaining a more thorough understanding of the process of polymicrobial biofilm formation and advance the possibility of using indole-degrading bacteria to address biofilm-related health and industry issues.

An Investigation into the Temporal Reproducibility of Tryptophan Metabolite Networks Among Healthy Adolescents

Tryptophan and its bioactive metabolites are associated with health conditions such as systemic inflammation, cardiometabolic diseases, and neurodegenerative disorders. There are dynamic interactions among metabolites of tryptophan. The interactions between metabolites, particularly those that are strong and temporally reproducible could be of pathophysiological relevance. Using a targeted metabolomics approach, the concentration levels of tryptophan and 18 of its metabolites across multiple pathways was quantified in 24-hours urine samples at 2 time-points, age 17 years (baseline) and 18 years (follow-up) from 132 (52% female) apparently healthy adolescent participants of the DOrtmund Nutritional and Anthropometric Longitudinally Designed (DONALD) Study. In sex-specific analyses, we applied 2 network approaches, the Gaussian graphical model and Bayesian network to (1) explore the network structure for both time-points, (2) retrieve strongly related metabolites, and (3) determine whether the strongly related metabolites were temporally reproducible. Independent of selected covariates, the 2 network approaches revealed 5 associations that were strong and temporally reproducible. These were novel relationships, between kynurenic acid and indole-3-acetic acid in females and between kynurenic acid and xanthurenic acid in males, as well as known relationships between kynurenine and 3-hydroxykynurenine, and between 3-hydroxykynurenine and 3-hydroxyanthranilic acid in females and between tryptophan and kynurenine in males. Overall, this epidemiological study using network-based approaches shed new light into tryptophan metabolism, particularly the interaction of host and microbial metabolites. The 5 observed relationships suggested the existence of a temporally stable pattern of tryptophan and 6 metabolites in healthy adolescent, which could be further investigated in search of fingerprints of specific physiological states. The metabolites in these relationships may represent a multi-biomarker panel that could be informative for health outcomes.

Effects of Clostridium butyricum on growth performance, metabonomics and intestinal microbial differences of weaned piglets

Background

Weaning stress of piglets causes a huge economic loss to the pig industry. Balance and stability of the intestinal microenvironment is an effective way to reduce the occurance of stress during the weaning process. Clostridium butyricum, as a new microecological preparation, is resistant to high temperature, acid, bile salts and some antibiotics. The aim of present study is to investigate the effects of C. butyricum on the intestinal microbiota and their metabolites in weaned piglets.

Results

There was no statistical significance in the growth performance and the incidence of diarrhoea among the weaned piglets treated with C. butyricum during 0–21 days experimental period. Analysis of 16S rRNA gene sequencing results showed that the operational taxonomic units (OTUs), abundance-based coverage estimator (ACE) and Chao index of the CB group were found to be significantly increased compared with the NC group (P < 0.05). Bacteroidetes, Firmicutes and Tenericutes were the predominant bacterial phyla in the weaned piglets. A marked increase in the relative abundance of Megasphaera, Ruminococcaceae_NK4A214_group and Prevotellaceae_UCG-003, along with a decreased relative abundance of Ruminococcaceae_UCG-005 was observed in the CB group, when compared with the NC group (P < 0.05). With the addition of C. butyricum, a total of twenty-two significantly altered metabolites were obtained in the feces of piglets. The integrated pathway analysis by MetaboAnalyst indicated that arginine and proline metabolism; valine, leucine and isoleucine biosynthesis; and phenylalanine metabolism were the main three altered pathways, based on the topology. Furthermore, Spearman’s analysis revealed some altered gut microbiota genus such as Oscillospira, Ruminococcaceae_NK4A214_group, Megasphaera, Ruminococcaceae_UCG-005, Prevotella_2, Ruminococcaceae_UCG-002, Rikenellaceae_RC9_gut_group and Prevotellaceae_UCG-003 were associated with the alterations in the fecal metabolites (P < 0.05), indicating that C. butyricum presented a potential protective impact through gut microbiota. The intestinal metabolites changed by C. butyricum mainly involved the variation of citrulline, dicarboxylic acids, branched-chain amino acid and tryptophan metabolic pathways.

Conclusions

Overall, this study strengthens the idea that the dietary C. butyricum treatment can significantly alter the intestinal microbiota and metabolite profiles of the weaned piglets, and C. butyricum can offer potential benefits for the gut health.

Associations of BMI and Body Fat with Urine Metabolome in Adolescents Are Sex-Specific: A Cross-Sectional Study

Epidemiologic studies examining the relationship between body composition and the urine metabolome may improve our understanding of the role of metabolic dysregulation in body composition-related health conditions. Previous studies, mostly in adult populations, have focused on a single measure of body composition, body mass index (BMI), and sex-specific associations are rarely explored. We investigate sex-specific associations of two measures of body composition—BMI and body fat (BF)—with the urine metabolome in adolescents. In 369 participants (age 16–18, 49% female) of the Dortmund Nutritional and Anthropometric Longitudinally Designed (DONALD) study, we examined sex-specific associations of these two measures of body composition, BMI and BF, and 1407 (467 unknown) 24 h urine metabolites analyzed by untargeted metabolomics cross-sectionally. Missing metabolites were imputed. We related metabolites (dependent variable) to BMI and BF (independent variable) separately using linear regression. The models were additionally adjusted for covariates. We found 10 metabolites associated with both BMI and BF. We additionally found 11 metabolites associated with only BF, and nine with only BMI. None of these associations was in females. We observed a strong sexual dimorphism in the relationship between body composition and the urine metabolome.