Blood metabolome predicts gut microbiome α-diversity in humans

Chinese expert consensus on standard technical specifications for a gut microecomics laboratory (Review)

The intestinal microbiota is a complex ecosystem that not only affects various physiological functions, such as metabolism, inflammation and the immune response, but also has an important effect on the development of tumors and response to treatment. The detection of intestinal flora enables the timely identification of disease-related flora abnormalities, which has significant implications for both disease prevention and treatment. In the field of basic and clinical research targeting gut microbiome, there is a need to recognize and understand the laboratory assays for gut microbiomics. Currently, there is no unified standard for the experimental procedure, quality management and report interpretation of intestinal microbiome assay technology. In order to clarify the process, the Tumor and Microecology Committee of China Anti-Cancer Association and the Tumor and Microecology Committee of Hubei Provincial Immunology Society organized relevant experts to discuss and put forward the standard technical specifications for gut microecomics laboratories, which provides a basis for further in-depth research in the field of intestinal microecomics.

Blood-based biomemristor for hyperglycemia and hyperlipidemia monitoring

Thanks to its structural characteristics and signal patterns similar to those of human brain synapses, memristors are widely believed to be applicable for neuromorphic computing. However, to our knowledge, memristors have not been effectively applied in the biomedical field, especially in disease diagnosis and health monitoring. In this work, a blood-based biomemristor was prepared for in vitro detection of hyperglycemia and hyperlipidemia. It was found that the device exhibits excellent resistance switching (RS) behavior at lower voltage biases. Through mechanism analysis, it has been confirmed that the RS behavior is driven by Ohmic conduction and ion rearrangement. Furthermore, the hyperglycemia and hyperlipidemia detection devices were constructed for the first time based on memristor logic circuits, and circuit simulations were conducted. These results confirm the feasibility of blood-based biomemristors in detecting hyperglycemia and hyperlipidemia, providing new prospects for the important application of memristors in the biomedical field.

Analyzing urinary hippuric acid as a metabolic health biomarker through a supramolecular architecture

The prevalence of metabolic disorders has been found to increase concomitantly with alternations in habitual diet and lifestyle, indicating the importance of metabolic health monitoring for early warning of high-risk status and suggesting effective intervention strategies. Hippuric acid (HA), as one of the most abundant metabolites from the gut microbiota, holds potential as a regulator of metabolic health. Accordingly, it is imperative to establish an efficient, sensitive, and affordable method for large-scale population monitoring, revealing the association between HA level and metabolic disorders. Upon systematic screening of macrocycle•dye reporter pair, a supramolecular architecture (guanidinomethyl-modified calix[5]arene, GMC5A) was employed to sense urinary HA by employing fluorescein (Fl), whose complexation behavior was demonstrated by theoretical calculations, accomplishing quantification of HA in urine from 249 volunteers in the range of 0.10 mM and 10.93 mM. Excitedly, by restricted cubic spline, urinary HA concentration was found to have a significantly negative correlation with the risk of metabolic disorders when it exceeded 0.76 mM, suggesting the importance of dietary habits, especially the consumption of fruits, coffee, and tea, which was unveiled from a simple questionnaire survey. In this study, we accomplished a high throughput and sensitive detection of urinary HA based on supramolecular sensing with the GMC5A•Fl reporter pair, which sheds light on the rapid quantification of urinary HA as an indicator of metabolic health status and early intervention by balancing the daily diet.

Gut microbial features and circulating metabolomic signatures of frailty in older adults

Frailty, a multidimensional indicator of suboptimal aging, reflects cumulative declines across multiple physiological systems. Although age-related changes have been reported in gut microbiota, their role in healthy aging remains unclear. In this study, we calculated frailty index (FI) from 33 health-related items to reflect the overall health status of 1,821 older adults (62-96 years, 55% female) and conducted multi-omics analysis using gut metagenomic sequencing data and plasma metabolomic data. We identified 18 microbial species and 17 metabolites shifted along with frailty severity, with stronger links observed in females. The associations of nine species, including various Clostridium species and Faecalibacterium prausnitzii, with FI were reproducible in two external populations. Plasma glycerol levels, white blood cell count and kidney function partially mediated these associations. A composite microbial score derived from FI significantly predicted 2-year mortality (adjusted hazard ratio across extreme quartiles, 2.86; 95% confidence interval, 1.38-5.93), highlighting the potential of microbiota-based strategies for risk stratification in older adults.

Exposome-Wide Ranking to Uncover Environmental Chemicals Associated with Dyslipidemia: A Panel Study in Healthy Older Chinese Adults from the BAPE Study

BACKGROUND

Environmental contaminants (ECs) are increasingly recognized as crucial drivers of dyslipidemia and cardiovascular disease (CVD), but the comprehensive impact spectrum and interlinking mechanisms remain uncertain.

OBJECTIVES

We aimed to systematically evaluate the association between exposure to 80 ECs across seven divergent categories and markers of dyslipidemia and investigate their underpinning biomolecular mechanisms via an unbiased integrative approach of internal chemical exposome and multi-omics.

METHODS

A longitudinal study involving 76 healthy older adults was conducted in Jinan, China, and participants were followed five times from 10 September 2018 to 19 January 2019 in 1-month intervals. A broad spectrum of seven chemical categories covering the prototypes and metabolites of 102 ECs in serum or urine as well as six serum dyslipidemia markers [total cholesterol, high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, apolipoprotein (Apo)A1, ApoB, and ApoE4] were measured. Multi-omics, including the blood transcriptome, serum/urine metabolome, and serum lipidome, were profiled concurrently. Exposome-wide association study and the deletion/substitution/addition algorithms were applied to explore the associations between 80 EC exposures detection frequency > 50 % and dyslipidemia markers. Weighted quantile sum regression was used to assess the mixture effects and relative contributions. Multi-omics profiling, causal inference model, and pathway analysis were conducted to interpret the mediating biomolecules and underlying mechanisms. Examination of cytokines and electrocardiograms was further conducted to validate the observed associations and biomolecular pathways.

RESULTS

Eight main ECs [1-naphthalene, 1-pyrene, 2-fluorene, dibutyl phosphate, tri-phenyl phosphate, mono-(2-ethyl-5-hydroxyhexyl) phthalate, chromium, and vanadium] were significantly associated with most dyslipidemia markers. Multi-omics indicated that the associations were mediated by endogenous biomolecules and pathways, primarily pertinent to CVD, inflammation, and metabolism. Clinical measures of cytokines and electrocardiograms further cross-validated the association of these exogenous ECs with systemic inflammation and cardiac function, demonstrating their potential mechanisms in driving dyslipidemia pathogenesis.

DISCUSSION

It is imperative to prioritize mitigating exposure to these ECs in the primary prevention and control of the dyslipidemia epidemic. https://doi.org/10.1289/EHP13864.

Altered blood microbiome in patients with HCV-related Child-Pugh class B cirrhosis

BACKGROUND

Altered bacterial translocation is associated with changes in hepatic function and the progression from compensated to decompensated cirrhosis. Child-Turcotte-Pugh (CTP) score is an essential indicator of liver severity. Thus, we aimed to study differences in the blood microbiome together with metabolome profile between HCV-infected patients with CTP class B (CTP-B, significant functional compromise) and patients with CTP class A (CTP-A, well-compensated cirrhosis).

METHODS

We conducted a cross-sectional study in patients with advanced HCV-related cirrhosis (n = 88) stratified by CTP-B and CTP-A. Bacterial 16S rRNA sequencing was sequenced by MiSeq Illumina technology and non-targeted metabolomics was performed by GC-MS and LC-MS ESI+ and ESI- to complement the analysis.

RESULTS

Patients with CTP-B had lower levels of richness (Chao1), and alpha diversity (Shannon and Simpson indexes) at phylum level than patients with CTP-A. Likewise, we observed significant differences in beta diversity between groups at phylum, class, and order levels, showing lower diversity in patients with CTP-B. Higher relative abundance of Proteobacteria (p = 0.012), Alphaproteobacteria (p = 0.005), Sphingomonadales (p = 0.012) and Sphingomonadaceae (p = 0.016) were significantly associated with CTP-B. The phylum Proteobacteria was positively correlated with ethanolamine and oleic acid (p = 0.005 and p = 0.004, respectively) and negatively with p-cresol (p = 0.006). In addition, the order Sphingomonadales and the family Sphingomonadaceae was also negatively correlated with p-cresol (p = 0.001 and p = 0.001).

CONCLUSIONS

Blood microbial diversity was significantly decreased in patients with CTP-B, who presented an enrichment of Proteobacteria, Alphaproteobacteria, Sphingomonadales and Sphingomonadaceae compared to patients with CTP-A.

Saliva, Plasma, and Multifluid Metabolomic Signatures of Periodontal Disease, Type 2 Diabetes Progression, and Markers of Glycemia and Dyslipidemia Among Puerto Rican Adults With Overweight and Obesity

BACKGROUND

Evidence from cohort studies indicates a bidirectional relationship between periodontal disease and type 2 diabetes (T2D), but the underlying mechanisms remain unknown. In this study, we aimed to (1) identify saliva, plasma, and multifluid metabolomic signatures associated with periodontal disease and (2) determine if these signatures predict T2D progression and cardiometabolic biomarkers at year 3.

METHODS AND RESULTS

We included participants from the SOALS (San Juan Overweight Adult Longitudinal Study) (n=911). Metabolites from saliva (k=635) and plasma (k=1051) were quantified using liquid chromatography-mass spectrometry. We applied elastic net regression with 10-fold cross-validation to identify baseline metabolomic signatures of periodontal disease. Multivariable Cox proportional hazards regression and linear regression were used to evaluate the association with T2D progression and biomarker concentrations. Metabolomic profiles included highly weighted metabolites related to lysine and pyrimidine metabolism. Periodontal disease or its 3 metabolomic signatures were not associated with T2D progression in 3 years. Prospectively, 1-SD increments in the multifluid and saliva metabolomic signatures were associated with higher low-density lipoprotein (multifluid: 12.9±5.70, P=0.02; saliva: 13.3±5.11, P=0.009). A 1-SD increment in the plasma metabolomic signature was also associated with Homeostatic Model Assessment for Insulin Resistance (2.67±1.14, P=0.02) and triglyceride (0.52±0.18, P=0.002).

CONCLUSIONS

Although metabolomic signatures of periodontal disease could not predict T2D progression, they were associated with low-density lipoprotein, triglyceride, and Homeostatic Model Assessment for Insulin Resistance levels at year 3.

Synergistic impacts of antibiotics and heavy metals on Hermetia illucens: Unveiling dynamics in larval gut bacterial communities and microbial metabolites

Hermetia illucens larvae showcases remarkable bioremediation capabilities for both antibiotics and heavy metal contaminants. However, the distinctions in larval intestinal microbiota arising from the single and combined effects of antibiotics and heavy metals remain poorly elucidated. In this study, we delved into the details of larval intestinal bacterial communities and microbial metabolites when exposed to single and combined contaminants of oxytetracycline (OTC) and hexavalent chromium (Cr(VI)). After conversion, single contaminant-spiked substrate showed 75.5% of OTC degradation and 95.2% of Cr(VI) reductiuon, while combined contaminant-spiked substrate exhibited 71.3% of OTC degradation and 93.4% of Cr(VI) reductiuon. Single and combined effects led to differences in intestinal bacterial communities, mainly reflected in the genera of Enterococcus, Pseudogracilibacillus, Gracilibacillus, Wohlfahrtiimonas, Sporosarcina, Lysinibacillus, and Myroide. Moreover, these effects also induced differences across various categories of microbial metabolites, which categorized into amino acid and its metabolites, benzene and substituted derivatives, carbohydrates and its metabolites, heterocyclic compounds, hormones and hormone-related compounds, nucleotide and its metabolites, and organic acid and its derivatives. In particular, the differences induced OTC was greater than that of Cr(VI), and combined effects increased the complexity of microbial metabolism compared to that of single contaminant. Correlation analysis indicated that the bacterial genera, Preudogracilibacillus, Enterococcus, Sporosarcina, Lysinibacillus, Wohlfahrtiimonas, Ignatzschineria, and Fusobacterium exhibited significant correlation with significant differential metabolites, these might be used as indicators for the resistance and bioremediation of OTC and Cr(VI) contaminants. These findings are conducive to further understanding that the metabolism of intestinal microbiota determines the resistance of Hermetia illucens to antibiotics and heavy metals.

Comparing the metabolic signatures of obesity defined by waist circumference, waist-hip ratio, or BMI

OBJECTIVE

Measuring obesity is crucial for assessing health risks and developing effective prevention and treatment strategies. The most common methods used to measure obesity include BMI, waist circumference, and waist-hip ratio. This study aimed to determine the metabolic signatures associated with each measure of obesity in the Qatari population.

METHODS

Metabolomics profiling was conducted to identify, quantify, and characterize metabolites in serum samples from the study participants. Inverse rank normalization, principal component analysis, and orthogonal partial least square-discriminant analysis were used to analyze the metabolomics data.

RESULTS

This study revealed significant differences in metabolites associated with obesity based on different measurements. In men, phosphatidylcholine and phosphatidylethanolamine metabolites were significantly enriched in individuals classified as having obesity based on the waist-hip ratio. In women, significant changes were observed in leucine, isoleucine, and valine metabolism metabolites. Unique metabolites were found in the different categorization groups that could serve as biomarkers for assessing many obesity-related disorders.

CONCLUSIONS

This study identified unique metabolic signatures associated with obesity based on different measurements in the Qatari population. These findings contribute to a better understanding of the molecular pathways involved in obesity and may have implications for developing personalized prevention and treatment strategies.

A novel Bacillus aerolatus CX253 attenuates inflammation induced by Streptococcus pneumoniae in childhood and pregnant rats by regulating gut microbiome

Streptococcus pneumoniae (Spn) is the predominant pathogen responsible for community-acquired pneumonia (CAP) in children under five years old, and it can induce over 17% of pregnant women. However, no more effective measures exist to prevent infection induced by Spn in these two special populations. The beneficial microbes can antagonize Spn and provide new targets for preventing pneumococcal infections. This study used 16S rRNA gene sequencing and targeted metabolomics to evaluate the role of the Bacillus aerolatus CX253 (CX253) in alleviating Spn infection. Additionally, the colonization of CX253 was observed in nose, trachea, and lung by using confocal laser scanning microscopy and fluorescent labeling techniques. Compared with the model group, the expression level of interleukin-1β was dropped 1.81-fold and 2.22-fold, and interleukin-6 was decreased 2.39-fold and 1.84-fold. The express of tumor necrosis factor-α was down 2.30-fold and 3.84-fold in prevention group of childhood and pregnant rats, respectively. The 16S rRNA sequencing results showed that CX253 administration alone significantly increased the abundance of Lactobacillus, Limosilactobacillus, and Prevotella in the gut of childhood and pregnant rats. Furthermore, the CX253 increased propionate in the gut of childhood rats and increased propionate and butyrate in the gut of pregnant rats to inhibit pulmonary inflammation. In summary, CX253 attenuated Spn-induced inflammation by regulating the gut microbiota and SCFAs. The research provides valuable information for the prevention of pneumonia.

Aberrant bowel movement frequencies coincide with increased microbe-derived blood metabolites associated with reduced organ function

Bowel movement frequency (BMF) directly impacts the gut microbiota and is linked to diseases like chronic kidney disease or dementia. In particular, prior work has shown that constipation is associated with an ecosystem-wide switch from fiber fermentation and short-chain fatty acid production to more detrimental protein fermentation and toxin production. Here, we analyze multi-omic data from generally healthy adults to see how BMF affects their molecular phenotypes, in a pre-disease context. Results show differential abundances of gut microbial genera, blood metabolites, and variation in lifestyle factors across BMF categories. These differences relate to inflammation, heart health, liver function, and kidney function. Causal mediation analysis indicates that the association between lower BMF and reduced kidney function is partially mediated by the microbially derived toxin 3-indoxyl sulfate (3-IS). This result, in a generally healthy context, suggests that the accumulation of microbiota-derived toxins associated with abnormal BMF precede organ damage and may be drivers of chronic, aging-related diseases.

Association between Personal Abiotic Airborne Exposures and Body Composition Changes among Healthy Adults (60-69 Years Old): A Combined Exposome-Wide and Lipidome Mediation Approach from the China BAPE Study

BACKGROUND

Evidence suggested that abiotic airborne exposures may be associated with changes in body composition. However, more evidence is needed to identify key pollutants linked to adverse health effects and their underlying biomolecular mechanisms, particularly in sensitive older adults.

OBJECTIVES

Our research aimed to systematically assess the relationship between abiotic airborne exposures and changes in body composition among healthy older adults, as well as the potential mediating mechanisms through the serum lipidome.

METHODS

From September 2018 to January 2019, we conducted a monthly survey among 76 healthy adults (60-69 years old) in the China Biomarkers of Air Pollutant Exposure (BAPE) study, measuring their personal exposures to 632 abiotic airborne pollutions using MicroPEM and the Fresh Air wristband, 18 body composition indicators from the InBody 770 device, and lipidomics from venous blood samples. We used an exposome-wide association study (ExWAS) and deletion/substitution/addition (DSA) model to unravel complex associations between exposure to contaminant mixtures and body composition, a Bayesian kernel machine regression (BKMR) model to assess the overall effect of key exposures on body composition, and mediation analysis to identify lipid intermediators.

RESULTS

The ExWAS and DSA model identified that 2,4,5-T methyl ester (2,4,5-TME), 9,10-Anthracenedione (ATQ), 4b,8-dimethyl-2-isopropylphenanthrene, and 4b,5,6,7,8,8a,9,10-octahydro-(DMIP) were associated with increased body fat mass (BFM), fat mass indicators (FMI), percent body fat (PBF), and visceral fat area (VFA) in healthy older adults [Bonferroni-Hochberg false discovery rate ( FD R BH ) < 0.05 ]. The BKMR model demonstrated a positive correlation between contaminants (anthracene, ATQ, copaene, di-epi-α -cedrene, and DMIP) with VFA. Mediation analysis revealed that phosphatidylcholine [PC, PC(16:1e/18:1), PC(16:2e/18:0)] and sphingolipid [SM, SM(d18:2/24:1)] mediated a significant portion, ranging from 12.27% to 26.03% (p-value < 0.05 ), of the observed increase in VFA.

DISCUSSION

Based on the evidence from multiple model results, ATQ and DMIP were statistically significantly associated with the increased VFA levels of healthy older adults, potentially regulated through lipid intermediators. These findings may have important implications for identifying potentially harmful environmental chemicals and developing targeted strategies for the control and prevention of chronic diseases in the future, particularly as the global population is rapidly aging. https://doi.org/10.1289/EHP13865.

Multi-omics data integration using ratio-based quantitative profiling with Quartet reference materials

Characterization and integration of the genome, epigenome, transcriptome, proteome and metabolome of different datasets is difficult owing to a lack of ground truth. Here we develop and characterize suites of publicly available multi-omics reference materials of matched DNA, RNA, protein and metabolites derived from immortalized cell lines from a family quartet of parents and monozygotic twin daughters. These references provide built-in truth defined by relationships among the family members and the information flow from DNA to RNA to protein. We demonstrate how using a ratio-based profiling approach that scales the absolute feature values of a study sample relative to those of a concurrently measured common reference sample produces reproducible and comparable data suitable for integration across batches, labs, platforms and omics types. Our study identifies reference-free 'absolute' feature quantification as the root cause of irreproducibility in multi-omics measurement and data integration and establishes the advantages of ratio-based multi-omics profiling with common reference materials.

Diet influences knee osteoarthritis osteophyte formation via gut microbiota and serum metabolites

Osteophyte formation, a key indicator of osteoarthritis (OA) severity, remains poorly understood in its relation to gut microbiota and metabolites in knee osteoarthritis (KOA). We conducted 16S rDNA sequencing and untargeted metabolomics on fecal and serum samples from 20 healthy volunteers, 80 KOA patients in Guangdong, and 100 in Inner Mongolia, respectively. Through bioinformatics analysis, we identified 3 genera and 5 serum metabolites associated with KOA osteophyte formation. Blautia abundance negatively correlated with meat, cheese, and bean consumption. The 5 serum metabolites negatively correlated with dairy, beef, cheese, sugar, and salt intake, yet positively with age and oil consumption. Higher Blautia levels in the gut may contribute to KOA osteophyte formation, with serum metabolites LTB4 and PGD2 potentially serving as biomarkers. KOA patients in Inner Mongolia exhibited lower Blautia levels and reduced expression of 5 serum metabolites, possibly due to cheese consumption habits, resulting in less osteophyte formation.

Integrated Analysis of Microbiome and Metabolome Reveals Disease-Specific Profiles in Inflammatory Bowel Diseases and Intestinal Behçet's Disease

The gut microbial and metabolic characteristics of intestinal Behçet's disease (BD), a condition sharing many clinical similarities with ulcerative colitis (UC) and Crohn's disease (CD), are largely unexplored. This study investigated the gut microbial and metabolic characteristics of intestinal BD as well as potential biomarkers, comparing them with those in UC, CD, and healthy controls. Colon tissue and stool samples from 100 patients (35 UC, 30 CD, and 35 intestinal BD) and 41 healthy volunteers were analyzed using 16S ribosomal RNA sequencing to assess microbial diversity, taxonomic composition, and functional profiling. Plasma metabolomic analyses were performed using gas chromatography and ultra-performance liquid chromatography-mass spectrometry. Results indicated reduced microbial diversity in CD but not in intestinal BD, with intestinal BD showing fewer changes compared to controls yet distinct taxonomic features from UC, CD, and controls. Common alterations across all diseases included a reduction in beneficial bacteria producing short-chain fatty acids. Intestinal BD-specific changes featured a decreased abundance of Bacteroides fragilis. Metabolomic profiles in intestinal BD were similar to those in CD but distinct from those in UC, displaying significant changes in energy metabolism and genetic information processing. This integrative analysis revealed both shared and unique profiles in intestinal BD compared with UC, CD, and controls, advancing our understanding of the distinctive features of these diseases.

Multi-omics Analysis of a Fecal Microbiota Transplantation Trial Identifies Novel Aspects of Acute GVHD Pathogenesis

Acute GVHD (aGVHD) is a major complication of allogeneic hematopoietic cell transplantation (alloHCT) associated with gut microbiota disruptions. However, whether therapeutic microbiota modulation prevents aGVHD is unknown. We conducted a randomized, placebo-controlled trial of third-party fecal microbiota transplantation (FMT) administered at the peak of microbiota injury in 100 patients with acute myeloid leukemia receiving induction chemotherapy and alloHCT recipients. Despite improvements in microbiome diversity, expansion of commensals, and shrinkage of potential pathogens, aGVHD occurred more frequently after FMT than placebo. Although this unexpected finding could be explained by clinical differences between the two arms, we asked whether a microbiota explanation might be also present. To this end, we performed multi-omics analysis of preintervention and postintervention gut microbiome and serum metabolome. We found that postintervention expansion of Faecalibacterium, a commensal genus with gut-protective and anti-inflammatory properties under homeostatic conditions, predicted a higher risk for aGVHD. Faecalibacterium expansion occurred predominantly after FMT and was due to engraftment of unique donor taxa, suggesting that donor Faecalibacterium-derived antigens might have stimulated allogeneic immune cells. Faecalibacterium and ursodeoxycholic acid (an anti-inflammatory secondary bile acid) were negatively correlated, offering an alternative mechanistic explanation. In conclusion, we demonstrate context dependence of microbiota effects where a normally beneficial bacteria may become detrimental in disease. While FMT is a broad, community-level intervention, it may need precision engineering in ecologically complex settings where multiple perturbations (e.g., antibiotics, intestinal damage, alloimmunity) are concurrently in effect.

SIGNIFICANCE

Post-FMT expansion of Faecalibacterium, associated with donor microbiota engraftment, predicted a higher risk for aGVHD in alloHCT recipients. Although Faecalibacterium is a commensal genus with gut-protective and anti-inflammatory properties under homeostatic conditions, our findings suggest that it may become pathogenic in the setting of FMT after alloHCT. Our results support a future trial with precision engineering of the FMT product used as GVHD prophylaxis after alloHCT.

Tomato Pectin Ameliorated Hepatic Steatosis in High-Fat-Diet Mice by Modulating Gut Microbiota and Bile Acid Metabolism

Nonalcoholic fatty liver disease (NAFLD) is a worldwide public health issue. Changes in the gut microbiota structure and composition are closely related to host pathophysiology processes. Pectin is associated with several beneficial health effects. In the present study, we aimed at investigating the effect of tomato pectin (TP) on hepatic steatosis and exploring the underlying mechanisms by focusing on the regulation of the gut microbiota-bile acid axis. Our results showed that TP attenuated high-fat diet (HFD)-induced liver steatosis and inflammation. TP administration increased the diversity of gut microbiota, enhancing the abundance of beneficial bacteria and suppressing the abundance of harmful or conditional pathogenic bacteria. Further antibiotic-caused microbiome depletion confirmed that the anti-NAFLD activities of TP were dependent on the regulation of gut microbiota. Besides, TP intervention affected feces bile acid metabolism and caused significant changes in functional conjugated bile acids, which in turn inhibited the ileum FXR/FGF15 signaling, leading to stimulation of the hepatic bile acid (BA) production. Furthermore, TP treatment accelerated BA excretion, promoted BA transportation, inhibited BA reabsorption, and facilitated cholesterol efflux to relieve HFD-induced hyperlipidemia. These findings provide a potential dietary intervention strategy for TP against NAFLD via modulation of cross-talk between BAs and gut bacteria.

A Chemical Structure and Machine Learning Approach to Assess the Potential Bioactivity of Endogenous Metabolites and Their Association with Early Childhood Systemic Inflammation

Metabolomics has gained much attention due to its potential to reveal molecular disease mechanisms and present viable biomarkers. This work uses a panel of untargeted serum metabolomes from 602 children from the COPSAC2010 mother-child cohort. The annotated part of the metabolome consists of 517 chemical compounds curated using automated procedures. We created a filtering method for the quantified metabolites using predicted quantitative structure-bioactivity relationships for the Tox21 database on nuclear receptors and stress response in cell lines. The metabolites measured in the children's serums are predicted to affect specific targeted models, known for their significance in inflammation, immune function, and health outcomes. The targets from Tox21 have been used as targets with quantitative structure-activity relationships (QSARs). They were trained for ~7000 structures, saved as models, and then applied to the annotated metabolites to predict their potential bioactivities. The models were selected based on strict accuracy criteria surpassing random effects. After application, 52 metabolites showed potential bioactivity based on structural similarity with known active compounds from the Tox21 set. The filtered compounds were subsequently used and weighted by their bioactive potential to show an association with early childhood hs-CRP levels at six months in a linear model supporting a physiological adverse effect on systemic low-grade inflammation.

Gut microbiota, blood metabolites, and left ventricular diastolic dysfunction in US Hispanics/Latinos

BACKGROUND

Left ventricular diastolic dysfunction (LVDD) is an important precursor of heart failure (HF), but little is known about its relationship with gut dysbiosis and microbial-related metabolites. By leveraging the multi-omics data from the Hispanic Community Health Study/Study of Latinos (HCHS/SOL), a study with population at high burden of LVDD, we aimed to characterize gut microbiota associated with LVDD and identify metabolite signatures of gut dysbiosis and incident LVDD.

RESULTS

We included up to 1996 Hispanic/Latino adults (mean age: 59.4 years; 67.1% female) with comprehensive echocardiography assessments, gut microbiome, and blood metabolome data. LVDD was defined through a composite criterion involving tissue Doppler assessment and left atrial volume index measurements. Among 1996 participants, 916 (45.9%) had prevalent LVDD, and 212 out of 594 participants without LVDD at baseline developed incident LVDD over a median 4.3 years of follow-up. Using multivariable-adjusted analysis of compositions of microbiomes (ANCOM-II) method, we identified 7 out of 512 dominant gut bacterial species (prevalence > 20%) associated with prevalent LVDD (FDR-q < 0.1), with inverse associations being found for Intestinimonas_massiliensis, Clostridium_phoceensis, and Bacteroide_coprocola and positive associations for Gardnerella_vaginali, Acidaminococcus_fermentans, Pseudomonas_aeruginosa, and Necropsobacter_massiliensis. Using multivariable adjusted linear regression, 220 out of 669 circulating metabolites with detection rate > 75% were associated with the identified LVDD-related bacterial species (FDR-q < 0.1), with the majority being linked to Intestinimonas_massiliensis, Clostridium_phoceensis, and Acidaminococcus_fermentans. Furthermore, 46 of these bacteria-associated metabolites, mostly glycerophospholipids, secondary bile acids, and amino acids, were associated with prevalent LVDD (FDR-q < 0.1), 21 of which were associated with incident LVDD (relative risk ranging from 0.81 [p = 0.001, for guanidinoacetate] to 1.25 [p = 9 × 10-5, for 1-stearoyl-2-arachidonoyl-GPE (18:0/20:4)]). The inclusion of these 21 bacterial-related metabolites significantly improved the prediction of incident LVDD compared with a traditional risk factor model (the area under the receiver operating characteristic curve [AUC] = 0.73 vs 0.70, p = 0.001). Metabolite-based proxy association analyses revealed the inverse associations of Intestinimonas_massilliensis and Clostridium_phoceensis and the positive association of Acidaminococcus_fermentans with incident LVDD.

CONCLUSION

In this study of US Hispanics/Latinos, we identified multiple gut bacteria and related metabolites linked to LVDD, suggesting their potential roles in this preclinical HF entity. Video Abstract.

Metabolomic Markers in Attention-Deficit/Hyperactivity Disorder (ADHD) among Children and Adolescents-A Systematic Review

Attention-Deficit/Hyperactivity Disorder (ADHD), characterized by clinical diversity, poses diagnostic challenges often reliant on subjective assessments. Metabolomics presents an objective approach, seeking biomarkers for precise diagnosis and targeted interventions. This review synthesizes existing metabolomic insights into ADHD, aiming to reveal biological mechanisms and diagnostic potentials. A thorough PubMed and Web of Knowledge search identified studies exploring blood/urine metabolites in ADHD-diagnosed or psychometrically assessed children and adolescents. Synthesis revealed intricate links between ADHD and altered amino acid metabolism, neurotransmitter dysregulation (especially dopamine and serotonin), oxidative stress, and the kynurenine pathway impacting neurotransmitter homeostasis. Sleep disturbance markers, notably in melatonin metabolism, and stress-induced kynurenine pathway activation emerged. Distinct metabolic signatures, notably in the kynurenine pathway, show promise as potential diagnostic markers. Despite limitations like participant heterogeneity, this review underscores the significance of integrated therapeutic approaches targeting amino acid metabolism, neurotransmitters, and stress pathways. While guiding future research, this overview of the metabolomic findings in ADHD suggests directions for precision diagnostics and personalized ADHD interventions.

Aldicarb disturbed bile acid, steroid hormone and oxylipin homeostasis in C57BL/6 J mice

Mounting evidence has shown that the gut microbiota plays a key role in human health. The homeostasis of the gut microbiota could be affected by many factors, including environmental chemicals. Aldicarb is a carbamate insecticide used to control a variety of insects and nematode pests in agriculture. Aldicarb is highly toxic and its wide existence has become a global public health concern. In our previous study, we have demonstrated that aldicarb disturbed the gut microbial community structure and composition. However, the impacts of aldicarb on gut microbiota-derived metabolites, bile acids, remain elusive. In present study, we performed targeted metabolomics analysis to explore the effects of aldicarb exposure on bile acids, as well as steroid hormones and oxylipins in the serum, feces and liver of C57BL/6 J mice. Our results showed that aldicarb exposure disturbed the level of various bile acids, steroid hormones and oxylipins in the serum and feces of C57BL/6 J mice. In the liver, the level of cortisol was decreased, meanwhile 15,16-dihydroxyoctadeca-9,12-dienoic acid was increased in aldicarb-treated mice. Metagenomic sequencing analysis showed that the relative abundance of a bile salt hydrolase, choloylglycine hydrolase (EC:3.5.1.24) and a sulfatase enzyme involved in steroid hormone metabolism, arylsulfatase, was significantly increased by aldicarb exposure. Furthermore, correlations were found between gut microbiota and various serum metabolites. The results from this study are helpful to improve the understanding of the impact of carbamate insecticides on host and microbial metabolism.

Longitudinal profiling of the microbiome at four body sites reveals core stability and individualized dynamics during health and disease

To understand the dynamic interplay between the human microbiome and host during health and disease, we analyzed the microbial composition, temporal dynamics, and associations with host multi-omics, immune, and clinical markers of microbiomes from four body sites in 86 participants over 6 years. We found that microbiome stability and individuality are body-site specific and heavily influenced by the host. The stool and oral microbiome are more stable than the skin and nasal microbiomes, possibly due to their interaction with the host and environment. We identify individual-specific and commonly shared bacterial taxa, with individualized taxa showing greater stability. Interestingly, microbiome dynamics correlate across body sites, suggesting systemic dynamics influenced by host-microbial-environment interactions. Notably, insulin-resistant individuals show altered microbial stability and associations among microbiome, molecular markers, and clinical features, suggesting their disrupted interaction in metabolic disease. Our study offers comprehensive views of multi-site microbial dynamics and their relationship with host health and disease.

Ginseng Glucosyl Oleanolate from Ginsenoside Ro, Exhibited Anti-Liver Cancer Activities via MAPKs and Gut Microbiota In Vitro/Vivo

Ginseng is widely recognized for its diverse health benefits and serves as a functional food ingredient with global popularity. Ginsenosides with a broad range of pharmacological effects are the most crucial active ingredients in ginseng. This study aimed to derive ginseng glucosyl oleanolate (GGO) from ginsenoside Ro through enzymatic conversion and evaluate its impact on liver cancer in vitro and in vivo. GGO exhibited concentration-dependent HepG2 cell death and markedly inhibited cell proliferation via the MAPK signaling pathway. It also attenuated tumor growth in immunocompromised mice undergoing heterograft transplantation. Furthermore, GGO intervention caused a modulation of gut microbiota composition by specific bacterial populations, including Lactobacillus, Bacteroides, Clostridium, Enterococcus, etc., and ameliorated SCFA metabolism and colonic inflammation. These findings offer promising evidence for the potential use of GGO as a natural functional food ingredient in the prevention and treatment of cancer.

Plasma metabolomic markers underlying skeletal muscle mitochondrial function relationships with cognition and motor function

BACKGROUND

Lower skeletal muscle mitochondrial function is associated with future cognitive impairment and mobility decline, but the biological underpinnings for these associations are unclear. We examined metabolomic markers underlying skeletal muscle mitochondrial function, cognition and motor function.

METHODS

We analysed data from 560 participants from the Baltimore Longitudinal Study of Aging (mean age: 68.4 years, 56% women, 28% Black) who had data on skeletal muscle oxidative capacity (post-exercise recovery rate of phosphocreatine, kPCr) via 31P magnetic resonance spectroscopy and targeted plasma metabolomics using LASSO model. We then examined which kPCr-related markers were also associated with cognition and motor function in a larger sample (n = 918, mean age: 69.4, 55% women, 27% Black).

RESULTS

The LASSO model revealed 24 metabolites significantly predicting kPCr, with the top 5 being asymmetric dimethylarginine, lactic acid, lysophosphatidylcholine a C18:1, indoleacetic acid and triacylglyceride (17:1_34:3), also significant in multivariable linear regression. The kPCr metabolite score was associated with cognitive or motor function, with 2.5-minute usual gait speed showing the strongest association (r = 0.182). Five lipids (lysophosphatidylcholine a C18:1, phosphatidylcholine ae C42:3, cholesteryl ester 18:1, sphingomyelin C26:0, octadecenoic acid) and 2 amino acids (leucine, cystine) were associated with both cognitive and motor function measures.

CONCLUSION

Our findings add evidence to the hypothesis that mitochondrial function is implicated in the pathogenesis of cognitive and physical decline with aging and suggest that targeting specific metabolites may prevent cognitive and mobility decline through their effects on mitochondria. Future omics studies are warranted to confirm these findings and explore mechanisms underlying mitochondrial dysfunction in aging phenotypes.

Effects of natural products on functional constipation: analysis of active ingredient and mechanism

Constipation is a prevalent clinical ailment of the gastrointestinal system, yet its pathogenesis remains ambiguous. Despite the availability of numerous treatment modalities, they are insufficient in resolving the issue for patients. This work conducted a comprehensive review of the existing literature pertaining to the utilization of natural products for the treatment of constipation, with a focus on the efficacy of natural products in treating constipation, and to provide a comprehensive summary of their underlying mechanisms of action. Upon conducting a thorough review of the extant literature, we found that natural products can effectively treat constipation as modern synthetic drugs and compounded drugs with acetylcholinesterase (AChE) effects, rich in fiber and mucus, and the effects of increasing the tension of the ileum and gastrointestinal tract muscle, mediating signaling pathways, cytokine, excitability of the smooth muscle of the gastrointestinal tract, and regulating the homeostasis of intestinal flora. However, there is a wide variety of natural products, and there are still relatively few studies; the composition of natural products is complex, and the mechanism of action of natural products cannot be clarified. In the future, we need to further improve the detailed mechanism of natural products for the treatment of constipation.

The transition from genomics to phenomics in personalized population health

Modern health care faces several serious challenges, including an ageing population and its inherent burden of chronic diseases, rising costs and marginal quality metrics. By assessing and optimizing the health trajectory of each individual using a data-driven personalized approach that reflects their genetics, behaviour and environment, we can start to address these challenges. This assessment includes longitudinal phenome measures, such as the blood proteome and metabolome, gut microbiome composition and function, and lifestyle and behaviour through wearables and questionnaires. Here, we review ongoing large-scale genomics and longitudinal phenomics efforts and the powerful insights they provide into wellness. We describe our vision for the transformation of the current health care from disease-oriented to data-driven, wellness-oriented and personalized population health.

Microbial imidazole propionate affects glomerular filtration rate in patients with diabetic nephropathy through association with HSP90α

Imidazole propionate (ImP) is a detrimental metabolite produced by the fermentation of histidine intermediates via the intestinal flora. Here, the untargeted metabolite analysis of plasma metabolites from patients with diabetic nephropathy (DN), in combination with the Human Metabolome Database, revealed significantly increased levels of ImP in patients with DN, with a positive correlation with patients' blood creatinine concentration and urinary albumin-to-creatinine ratio, and a negative correlation with the glomerular filtration rate. RNA-seq was applied to detect the effects of ImP on renal tissue transcriptome in mice with DN. It demonstrated that ImP exacerbated renal injury in mice with DN and promoted renal tubular epithelial-mesenchymal transition (EMT), leading to renal mesenchymal fibrosis and renal impairment. Furthermore, ImP was found to directly target HAP90α and activate the PI3K-Akt signalling pathway, which is involved in EMT, by the drug affinity response target stability method. The findings showed that ImP may provide a novel target for DN quality, as it can directly bind to and activate HSP90, thereby facilitating the development of DN while acting as a potential indicator for the clinical diagnosis of DN.

Identifying plasma metabolic characteristics of major depressive disorder, bipolar disorder, and schizophrenia in adolescents

Major depressive disorder (MDD), bipolar disorder (BD), and schizophrenia (SCZ) are classified as major mental disorders and together account for the second-highest global disease burden, and half of these patients experience symptom onset in adolescence. Several studies have reported both similar and unique features regarding the risk factors and clinical symptoms of these three disorders. However, it is still unclear whether these disorders have similar or unique metabolic characteristics in adolescents. We conducted a metabolomics analysis of plasma samples from adolescent healthy controls (HCs) and patients with MDD, BD, and SCZ. We identified differentially expressed metabolites between patients and HCs. Based on the differentially expressed metabolites, correlation analysis, metabolic pathway analysis, and potential diagnostic biomarker identification were conducted for disorders and HCs. Our results showed significant changes in plasma metabolism between patients with these mental disorders and HCs; the most distinct changes were observed in SCZ patients. Moreover, the metabolic differences in BD patients shared features with those in both MDD and SCZ, although the BD metabolic profile was closer to that of MDD than to SCZ. Additionally, we identified the metabolites responsible for the similar and unique metabolic characteristics in multiple metabolic pathways. The similar significant differences among the three disorders were found in fatty acid, steroid-hormone, purine, nicotinate, glutamate, tryptophan, arginine, and proline metabolism. Interestingly, we found unique characteristics of significantly altered glycolysis, glycerophospholipid, and sphingolipid metabolism in SCZ; lysine, cysteine, and methionine metabolism in MDD and BD; and phenylalanine, tyrosine, and aspartate metabolism in SCZ and BD. Finally, we identified five panels of potential diagnostic biomarkers for MDD-HC, BD-HC, SCZ-HC, MDD-SCZ, and BD-SCZ comparisons. Our findings suggest that metabolic characteristics in plasma vary across psychiatric disorders and that critical metabolites provide new clues regarding molecular mechanisms in these three psychiatric disorders.

Generally-healthy individuals with aberrant bowel movement frequencies show enrichment for microbially-derived blood metabolites associated with reduced kidney function

Bowel movement frequency (BMF) has been linked to changes in the composition of the human gut microbiome and to many chronic conditions, like metabolic disorders, neurodegenerative diseases, chronic kidney disease (CKD), and other intestinal pathologies like irritable bowel syndrome and inflammatory bowel disease. Lower BMF (constipation) can lead to compromised intestinal barrier integrity and a switch from saccharolytic to proteolytic fermentation within the microbiota, giving rise to microbially-derived toxins that may make their way into circulation and cause damage to organ systems. However, the connections between BMF, gut microbial metabolism, and the early-stage development and progression of chronic disease remain underexplored. Here, we examined the phenotypic impact of BMF variation in a cohort of generally-healthy, community dwelling adults with detailed clinical, lifestyle, and multi-omic data. We showed significant differences in microbially-derived blood plasma metabolites, gut bacterial genera, clinical chemistries, and lifestyle factors across BMF groups that have been linked to inflammation, cardiometabolic health, liver function, and CKD severity and progression. We found that the higher plasma levels of 3-indoxyl sulfate (3-IS), a microbially-derived metabolite associated with constipation, was in turn negatively associated with estimated glomerular filtration rate (eGFR), a measure of kidney function. Causal mediation analysis revealed that the effect of BMF on eGFR was significantly mediated by 3-IS. Finally, we identify self-reported diet, lifestyle, and psychological factors associated with BMF variation, which indicate several common-sense strategies for mitigating constipation and diarrhea. Overall, we suggest that aberrant BMF is an underappreciated risk factor in the development of chronic diseases, even in otherwise healthy populations.

Inflammatory bowel disease (ulcerative colitis type) severity shows inverse correlation with semen parameters and testosterone levels

Individuals with inflammatory bowel disease (IBD) have been reported to be at an increased risk of infertility and sexual dysfunction. Although the relationship between them remains unclear, IBD severity is suspected to affect hormone levels and fertility. To analyze the impact of IBD severity on semen parameters and sex hormone levels in ulcerative colitis-type IBD (UC-IBD), we conducted a cross-sectional study involving 120 patients with UC-IBD in Adam Malik General Hospital, Medan, Indonesia. The patients were classified into three groups based on the Mayo score for UC, followed by a comparison of various semen and hormone parameters among these groups. In addition to the cross-sectional analysis, a simple correlation test was conducted irrespective of the patient grouping. Sperm concentration, motility, and morphology were found to decline significantly with an increase in IBD severity. Without classifying patients with IBD into subgroups, the Mayo score showed negative correlations with sperm concentration ( r = -0.375, P < 0.0001), rapid progressive motility ( r = -0.660, P < 0.0001), free testosterone ( r = -0.732, P < 0.0001), and total testosterone ( r = -0.721, P < 0.0001), and positive correlations with immotile sperm ( r = 0.660, P < 0.0001), abnormal morphology ( r = 0.657, P < 0.0001), and sex hormone-binding globulin (SHBG; r = 0.278, P = 0.002). Sperm concentration, motility, and morphology declined significantly with the severity of IBD. This study suggests a significant negative impact of IBD severity on semen quality and sex hormones.

Investigation of the mechanism of silica-induced pulmonary fibrosis: The role of lung microbiota dysbiosis and the LPS/TLR4 signaling pathway

The widespread manufacture of silica and its extensive use, and potential release of silica into the environment pose a serious human health hazard. Silicosis, a severe global public health issue, is caused by exposure to silica, leading to persistent inflammation and fibrosis of the lungs. The underlying pathogenic mechanisms of silicosis remain elusive. Lung microbiota dysbiosis is associated with the development of inflammation and fibrosis. However, limited information is currently available regarding the role of lung microbiota in silicosis. The study therefore is designed to conduct a comprehensive analysis of the role of lung microbiota dysbiosis and establish a basis for future investigations into the potential mechanisms underlying silicosis. Here, the pathological and biochemical parameters were used to systematically assessed the degree of inflammation and fibrosis following silica exposure and treatment with combined antibiotics. The underlying mechanisms were studied via integrative multi-omics analyses of the transcriptome and microbiome. Analysis of 16S ribosomal DNA revealed dysbiosis of the microbial community in silicosis, characterized by a predominance of gram-negative bacteria. Exposure to silica has been shown to trigger lung inflammation and fibrosis, leading to an increased concentration of lipopolysaccharides in the bronchoalveolar lavage fluid. Furthermore, Toll-like receptor 4 was identified as a key molecule in the lung microbiota dysbiosis associated with silica-induced lung fibrosis. All of these outcomes can be partially controlled through combined antibiotic administration. The study findings demonstrate that the dysbiosis of lung microbiota enhances silica-induced fibrosis associated with the lipopolysaccharides/Toll-like receptor 4 pathway and provided a promising target for therapeutic intervention of silicosis.

Gut microbiome-metabolome interactions predict host condition

BACKGROUND

The effect of microbes on their human host is often mediated through changes in metabolite concentrations. As such, multiple tools have been proposed to predict metabolite concentrations from microbial taxa frequencies. Such tools typically fail to capture the dependence of the microbiome-metabolite relation on the environment.

RESULTS

We propose to treat the microbiome-metabolome relation as the equilibrium of a complex interaction and to relate the host condition to a latent representation of the interaction between the log concentration of the metabolome and the log frequencies of the microbiome. We develop LOCATE (Latent variables Of miCrobiome And meTabolites rElations), a machine learning tool to predict the metabolite concentration from the microbiome composition and produce a latent representation of the interaction. This representation is then used to predict the host condition. LOCATE's accuracy in predicting the metabolome is higher than all current predictors. The metabolite concentration prediction accuracy significantly decreases cross datasets, and cross conditions, especially in 16S data. LOCATE's latent representation predicts the host condition better than either the microbiome or the metabolome. This representation is strongly correlated with host demographics. A significant improvement in accuracy (0.793 vs. 0.724 average accuracy) is obtained even with a small number of metabolite samples ([Formula: see text]).

CONCLUSION

These results suggest that a latent representation of the microbiome-metabolome interaction leads to a better association with the host condition than any of the two separated or the simple combination of the two. Video Abstract.

Longitudinal profiling of the microbiome at four body sites reveals core stability and individualized dynamics during health and disease

To understand dynamic interplay between the human microbiome and host during health and disease, we analyzed the microbial composition, temporal dynamics, and associations with host multi-omics, immune and clinical markers of microbiomes from four body sites in 86 participants over six years. We found that microbiome stability and individuality are body-site-specific and heavily influenced by the host. The stool and oral microbiome were more stable than the skin and nasal microbiomes, possibly due to their interaction with the host and environment. Also, we identified individual-specific and commonly shared bacterial taxa, with individualized taxa showing greater stability. Interestingly, microbiome dynamics correlated across body sites, suggesting systemic coordination influenced by host-microbial-environment interactions. Notably, insulin-resistant individuals showed altered microbial stability and associations between microbiome, molecular markers, and clinical features, suggesting their disrupted interaction in metabolic disease. Our study offers comprehensive views of multi-site microbial dynamics and their relationship with host health and disease.

Study Highlights

The stability of the human microbiome varies among individuals and body sites.Highly individualized microbial genera are more stable over time.At each of the four body sites, systematic interactions between the environment, the host and bacteria can be detected.Individuals with insulin resistance have lower microbiome stability, a more diversified skin microbiome, and significantly altered host-microbiome interactions.

Vitamin D3 supplementation shapes the composition of gut microbiota and improves some obesity parameters induced by high-fat diet in mice

PURPOSE

Individuals with vitamin D (VD) insufficiency have a greater tendency to develop obesity and have increased systemic inflammation. Gut microbiota are involved in the regulation of host inflammation and energy metabolism, which plays a role in the pathogenesis of obesity. Thus, we aimed to evaluate the effects of different doses of VD3 on body weight, serum lipids, inflammatory factors, and intestinal barrier function in obese mice and to explore the regulatory effect of VD3 on gut microbiota in obese mice.

METHODS

Male C57BL/6 J mice received a normal chow diet (NCD, 10% fat) or high-fat diet (HFD, 60% fat) to induce obesity within 10 weeks. Then, HFD mice were supplemented with 5650, 8475, or 11,300 IU VD3/kg diet for 8 weeks. Finally, 16 s rRNA analysis was performed to analyze gut microbiota composition in cecal contents. In addition, body weight, serum lipids, inflammatory factors, and intestinal barrier function were analyzed.

RESULTS

VD3 supplementation reduced body weight and the levels of TG, TC, HDL-C, TNF-α, IL-1β and LPS, and increased ZO-1 in HFD-fed mice. Moreover, it increased α-diversity, reduced F/B ratio and altered microbiota composition by increasing relative abundance of Bacteroidetes, Proteobacteria, Desulfovibrio, Dehalobacterium, Odoribacter, and Parabacteroides and reducing relative abundance of Firmicutes and Ruminococcus. There were significant differences between HFD and NCD groups in several metabolic pathways, including endotoxin biosynthesis, tricarboxylic acid cycle, lipid synthesis and metabolism, and glycolysis.

CONCLUSIONS

Low, medium, and high doses of VD3 inhibited weight gain, reduced levels of blood lipids and inflammatory factors, and improved endotoxemia and gut barrier function in obese mice. It also increased the α-diversity of gut microbiota in obese mice and reduced the relative abundance of some intestinal pathogenic bacteria, increased the relative abundance of some beneficial bacteria, and corrected the intestinal flora disorder of obese mice, with the low- and high-dose groups showing better effects than the medium-dose group.

Proteomic and Metabolomic Signatures of Diet Quality in Young Adults

The assessment of "omics" signatures may contribute to personalized medicine and precision nutrition. However, the existing literature is still limited in the homogeneity of participants' characteristics and in limited assessments of integrated omics layers. Our objective was to use post-prandial metabolomics and fasting proteomics to identify biological pathways and functions associated with diet quality in a population of primarily Hispanic young adults. We conducted protein and metabolite-wide association studies and functional pathway analyses to assess the relationships between a priori diet indices, Healthy Eating Index-2015 (HEI) and Dietary Approaches to Stop Hypertension (DASH) diets, and proteins (n = 346) and untargeted metabolites (n = 23,173), using data from the MetaAIR study (n = 154, 61% Hispanic). Analyses were performed for each diet quality index separately, adjusting for demographics and BMI. Five proteins (ACY1, ADH4, AGXT, GSTA1, F7) and six metabolites (undecylenic acid, betaine, hyodeoxycholic acid, stearidonic acid, iprovalicarb, pyracarbolid) were associated with both diets (p < 0.05), though none were significant after adjustment for multiple comparisons. Overlapping proteins are involved in lipid and amino acid metabolism and in hemostasis, while overlapping metabolites include amino acid derivatives, bile acids, fatty acids, and pesticides. Enriched biological pathways were involved in macronutrient metabolism, immune function, and oxidative stress. These findings in young Hispanic adults contribute to efforts to develop precision nutrition and medicine for diverse populations.

OMICs Signatures Linking Persistent Organic Pollutants to Cardiovascular Disease in the Swedish Mammography Cohort

Cardiovascular disease (CVD) development may be linked to persistent organic pollutants (POPs), including organochlorine compounds (OCs) and perfluoroalkyl and polyfluoroalkyl substances (PFAS). To explore underlying mechanisms, we investigated metabolites, proteins, and genes linking POPs with CVD risk. We used data from a nested case-control study on myocardial infarction (MI) and stroke from the Swedish Mammography Cohort - Clinical (n = 657 subjects). OCs, PFAS, and multiomics (9511 liquid chromatography-mass spectrometry (LC-MS) metabolite features; 248 proteins; 8110 gene variants) were measured in baseline plasma. POP-related omics features were selected using random forest followed by Spearman correlation adjusted for confounders. From these, CVD-related omics features were selected using conditional logistic regression. Finally, 29 (for OCs) and 12 (for PFAS) unique features associated with POPs and CVD. One omics subpattern, driven by lipids and inflammatory proteins, associated with MI (OR = 2.03; 95% CI = 1.47; 2.79), OCs, age, and BMI, and correlated negatively with PFAS. Another subpattern, driven by carnitines, associated with stroke (OR = 1.55; 95% CI = 1.16; 2.09), OCs, and age, but not with PFAS. This may imply that OCs and PFAS associate with different omics patterns with opposite effects on CVD risk, but more research is needed to disentangle potential modifications by other factors.

Island biogeography theory provides a plausible explanation for why larger vertebrates and taller humans have more diverse gut microbiomes

Prior work has shown a positive scaling relationship between vertebrate body size, human height, and gut microbiome alpha diversity. This observation mirrors commonly observed species area relationships (SARs) in many other ecosystems. Here, we expand these observations to several large datasets, showing that this size-diversity scaling relationship is independent of relevant covariates, like diet, body mass index, age, sex, bowel movement frequency, antibiotic usage, and cardiometabolic health markers. Island biogeography theory (IBT), which predicts that larger islands tend to harbor greater species diversity through neutral demographic processes, provides a simple mechanism for positive SARs. Using a gut-adapted IBT model, we demonstrated that increasing the length of a flow-through ecosystem led to increased species diversity, closely matching our empirical observations. We delve into the possible clinical implications of these SARs in the American Gut cohort. Consistent with prior observations that lower alpha diversity is a risk factor for Clostridioides difficile infection (CDI), we found that individuals who reported a history of CDI were shorter than those who did not and that this relationship was mediated by alpha diversity. We observed that vegetable consumption had a much stronger association with CDI history, which was also partially mediated by alpha diversity. In summary, we find that the positive scaling observed between body size and gut alpha diversity can be plausibly explained by a gut-adapted IBT model, may be related to CDI risk, and vegetable intake appears to independently mitigate this risk, although additional work is needed to validate the potential disease risk implications.

Personalized Clostridioides difficile engraftment risk prediction and probiotic therapy assessment in the human gut

Clostridioides difficile colonizes up to 30-40% of community-dwelling adults without causing disease. C. difficile infections (CDIs) are the leading cause of antibiotic-associated diarrhea in the U.S. and typically develop in individuals following disruption of the gut microbiota due to antibiotic or chemotherapy treatments. Further treatment of CDI with antibiotics is not always effective and can lead to antibiotic resistance and recurrent infections (rCDI). The most effective treatment for rCDI is the reestablishment of an intact microbiota via fecal microbiota transplants (FMTs). However, the success of FMTs has been difficult to generalize because the microbial interactions that prevent engraftment and facilitate the successful clearance of C. difficile are still only partially understood. Here we show how microbial community-scale metabolic models (MCMMs) accurately predicted known instances of C. difficile colonization susceptibility or resistance in vitro and in vivo. MCMMs provide detailed mechanistic insights into the ecological interactions that govern C. difficile engraftment, like cross-feeding or competition involving metabolites like succinate, trehalose, and ornithine, which differ from person to person. Indeed, three distinct C. difficile metabolic niches emerge from our MCMMs, two associated with positive growth rates and one that represents non-growth, which are consistently observed across 15,204 individuals from five independent cohorts. Finally, we show how MCMMs can predict personalized engraftment and C. difficile growth suppression for a probiotic cocktail (VE303) designed to replace FMTs for the treatment rCDI. Overall, this powerful modeling approach predicts personalized C. difficile engraftment risk and can be leveraged to assess probiotic treatment efficacy. MCMMs could be extended to understand the mechanistic underpinnings of personalized engraftment of other opportunistic bacterial pathogens, beneficial probiotic organisms, or more complex microbial consortia.

Implications of Jatropha curcas L. cake feed on swine health: A microbiota-gut-brain axis perspective

The safety of Jatropha curcas L. cake (JCC) in animal feed remains under scrutiny, despite the advent of low phorbol ester (PE) variants. This study investigates the impact of low PE JCC on swine health when used as a protein feed. Pigs were fed a 5% JCC diet with a PE concentration of 0.98 mg/kg, which surprisingly still induced toxicity. Symptoms included depression, decreased food intake, increased diarrhea, along with hypothalamus and colon lesions. The toxicity was associated with a decrease in antioxidant enzymes, an increase in inflammatory cytokines in the hypothalamus, plasma, and colon, and a rise in pro-inflammatory colon microbes and metabolites. Disturbances in neurotransmitters further suggest that this toxicity is related to disruption of the microbiota-gut-brain axis, indicating that JCC's toxic elements are not solely due to PE. The sensitivity of pigs to JCC underscores the need for thorough detoxification prior to its use as feed. These findings significantly contribute to the discourse on the safety of low PE JCC in animal feed, highlighting implications for both the feed industry and public health.

Temporal and geographic distribution of gut microbial enterotypes associated with host thermogenesis characteristics in plateau pikas

IMPORTANCE

The gut microbiotas of small mammals play an important role in host energy homeostasis. However, it is still unknown whether small mammals with different enterotypes show differences in thermogenesis characteristics. Our study confirmed that plateau pikas with different bacterial enterotypes harbored distinct thermogenesis capabilities and employed various strategies against cold environments. Additionally, we also found that pikas with different fungal enterotypes may display differences in coprophagy.

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

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

Analysis of gut microbiome, host genetics, and plasma metabolites reveals gut microbiome-host interactions in the Japanese population

Interaction between the gut microbiome and host plays a key role in human health. Here, we perform a metagenome shotgun-sequencing-based analysis of Japanese participants to reveal associations between the gut microbiome, host genetics, and plasma metabolome. A genome-wide association study (GWAS) for microbial species (n = 524) identifies associations between the PDE1C gene locus and Bacteroides intestinalis and between TGIF2 and TGIF2-RAB5IF gene loci and Bacteroides acidifiaciens. In a microbial gene ortholog GWAS, agaE and agaS, which are related to the metabolism of carbohydrates forming the blood group A antigen, are associated with blood group A in a manner depending on the secretor status determined by the East Asian-specific FUT2 variant. A microbiome-metabolome association analysis (n = 261) identifies associations between bile acids and microbial features such as bile acid metabolism gene orthologs including bai and 7β-hydroxysteroid dehydrogenase. Our publicly available data will be a useful resource for understanding gut microbiome-host interactions in an underrepresented population.

Sex differences in associations of plasma metabolites with blood pressure and heart rate variability: The HELIUS study

BACKGROUND AND AIMS

Since plasma metabolites can modulate blood pressure (BP) and vary between men and women, we examined sex differences in plasma metabolite profiles associated with BP and sympathicovagal balance. Our secondary aim was to investigate associations between gut microbiota composition and plasma metabolites predictive of BP and heart rate variability (HRV).

METHODS

From the HELIUS cohort, we included 196 women and 173 men. Office systolic BP and diastolic BP were recorded, and heart rate variability (HRV) and baroreceptor sensitivity (BRS) were calculated using finger photoplethysmography. Plasma metabolomics was measured using untargeted LC-MS/MS. Gut microbiota composition was determined using 16S sequencing. We used machine learning models to predict BP and HRV from metabolite profiles, and to predict metabolite levels from gut microbiota composition.

RESULTS

In women, best predicting metabolites for systolic BP included dihomo-lineoylcarnitine, 4-hydroxyphenylacetateglutamine and vanillactate. In men, top predictors included sphingomyelins, N-formylmethionine and conjugated bile acids. Best predictors for HRV in men included phenylacetate and gentisate, which were associated with lower HRV in men but not in women. Several of these metabolites were associated with gut microbiota composition, including phenylacetate, multiple sphingomyelins and gentisate.

CONCLUSIONS

Plasma metabolite profiles are associated with BP in a sex-specific manner. Catecholamine derivatives were more important predictors for BP in women, while sphingomyelins were more important in men. Several metabolites were associated with gut microbiota composition, providing potential targets for intervention.

Machine learning: a powerful tool for identifying key microbial agents associated with specific cancer types

Machine learning (ML) includes a broad class of computer programs that improve with experience and shows unique strengths in performing tasks such as clustering, classification and regression. Over the past decade, microbial communities have been implicated in influencing the onset, progression, metastasis, and therapeutic response of multiple cancers. Host-microbe interaction may be a physiological pathway contributing to cancer development. With the accumulation of a large number of high-throughput data, ML has been successfully applied to the study of human cancer microbiomics in an attempt to reveal the complex mechanism behind cancer. In this review, we begin with a brief overview of the data sources included in cancer microbiomics studies. Then, the characteristics of the ML algorithm are briefly introduced. Secondly, the application progress of ML in cancer microbiomics is also reviewed. Finally, we highlight the challenges and future prospects facing ML in cancer microbiomics. On this basis, we conclude that the development of cancer microbiomics can not be achieved without ML, and that ML can be used to develop tumor-targeting microbial therapies, ultimately contributing to personalized and precision medicine.

Metabolomics and lipidomics strategies in modern drug discovery and development

Metabolomics and lipidomics have an increasingly pivotal role in drug discovery and development. In the context of drug discovery, monitoring changes in the levels or composition of metabolites and lipids relative to genetic variations yields functional insights, bolstering human genetics and (meta)genomic methodologies. This approach also sheds light on potential novel targets for therapeutic intervention. In the context of drug development, metabolite and lipid biomarkers contribute to enhanced success rates, promising a transformative impact on precision medicine. In this review, we deviate from analytical chemist-focused perspectives, offering an overview tailored to drug discovery. We provide introductory insight into state-of-the-art mass spectrometry (MS)-based metabolomics and lipidomics techniques utilized in drug discovery and development, drawing from the collective expertise of our research teams. We comprehensively outline the application of metabolomics and lipidomics in advancing drug discovery and development, spanning fundamental research, target identification, mechanisms of action, and the exploration of biomarkers.

Distinctive metabolic remodeling in TYMP deficiency beyond mitochondrial dysfunction

Mitochondrial neurogastrointestinal encephalomyopathy (MNGIE) is caused by mutations in the TYMP gene, which encodes thymidine phosphorylase (TP). As a cytosolic metabolic enzyme, TP defects affect biological processes that are thought to not be limited to the abnormal replication of mitochondrial DNA. This study aimed to elucidate the characteristic metabolic alterations and associated homeostatic regulation caused by TYMP deficiency. The pathogenicity of novel TYMP variants was evaluated in terms of clinical features, genetic analysis, and structural instability. We analyzed plasma samples from three patients with MNGIE; three patients with m.3243A > G mitochondrial encephalopathy, lactic acidosis, and stroke-like episodes (MELAS); and four healthy controls (HC) using both targeted and untargeted metabolomics techniques. Transcriptomics analysis and bioenergetic studies were performed on skin fibroblasts from participants in these three groups. A TYMP overexpression experiment was conducted to rescue the observed changes. Compared with controls, specific alterations in nucleosides, bile acids, and steroid metabolites were identified in the plasma of MNGIE patients. Comparable mitochondrial dysfunction was present in fibroblasts from patients with TYMP deficiency and in those from patients with the m.3243A > G mutation. Distinctively decreased sterol regulatory element binding protein (SREBP) regulated cholesterol metabolism and fatty acid (FA) biosynthesis as well as reduced FA degradation were revealed in fibroblasts with TYMP deficiency. The restoration of thymidine phosphorylase activity rescued the observed changes in MNGIE fibroblasts. Our findings indicated that more widespread metabolic disturbance may be caused by TYMP deficiency in addition to mitochondrial dysfunction, which expands our knowledge of the biochemical outcome of TYMP deficiency. KEY MESSAGES: Distinct metabolic profiles in patients with TYMP deficiency compared to those with m.3243A > G mutation. TYMP deficiency leads to a global disruption of nucleoside metabolism. Cholesterol and fatty acid metabolism are inhibited in individuals with MNGIE. TYMP is functionally related to SREBP-regulated pathways. Potential metabolite biomarkers that could be valuable clinical tools to improve the diagnosis of MNGIE.

Plasma metabolomic profiling in two rabbit lines divergently selected for intramuscular fat content

This study provides a thorough comparison of the plasma metabolome of two rabbit lines divergently selected for intramuscular fat content (IMF). The divergent selection led to a correlated response in the overall adiposity, turning these lines into a valuable animal material to study also the genetics of obesity. Over 900 metabolites were detected, and the adjustment of multivariate models, both discriminant and linear, allowed to identify 322 with differential abundances between lines, which also adjusted linearly to the IMF content. The most affected pathways were those of lipids and amino acids, with differences between lines ranging from 0.23 to 6.04 standard deviations, revealing a limited capacity of the low-IMF line to obtain energy from lipids, and a greater branched-chain amino acids catabolism in the high-IMF line related to its increased IMF content. Additionally, changes in metabolites derived from microbial activity supported its relevant role in the lipid deposition. Future research will focus on the analysis of the metabolomic profile of the cecum content, and on the integration of the several -omics datasets available for these lines, to help disentangle the host and microbiome biological mechanisms involved in the IMF deposition.

Non-invasive monitoring of microbiota and host metabolism using secondary electrospray ionization-mass spectrometry

The metabolic "handshake" between the microbiota and its mammalian host is a complex, dynamic process with major influences on health. Dissecting the interaction between microbial species and metabolites found in host tissues has been a challenge due to the requirement for invasive sampling. Here, we demonstrate that secondary electrospray ionization-mass spectrometry (SESI-MS) can be used to non-invasively monitor metabolic activity of the intestinal microbiome of a live, awake mouse. By comparing the headspace metabolome of individual gut bacterial culture with the "volatilome" (metabolites released to the atmosphere) of gnotobiotic mice, we demonstrate that the volatilome is characteristic of the dominant colonizing bacteria. Combining SESI-MS with feeding heavy-isotope-labeled microbiota-accessible sugars reveals the presence of microbial cross-feeding within the animal intestine. The microbiota is, therefore, a major contributor to the volatilome of a living animal, and it is possible to capture inter-species interaction within the gut microbiota using volatilome monitoring.

Island biogeography theory and the gut: why taller people tend to harbor more diverse gut microbiomes

Prior work has shown a positive scaling relationship between vertebrate body size and gut microbiome alpha-diversity. This observation mirrors commonly observed species area relationships (SAR) in many other ecosystems. Here, we show a similar scaling relationship between human height and gut microbiome alpha-diversity across two large, independent cohorts, controlling for a wide range of relevant covariates, such as body mass index, age, sex, and bowel movement frequency. Island Biogeography Theory (IBT), which predicts that larger islands tend to harbor greater species diversity through neutral demographic processes, provides a simple mechanism for these positive SARs. Using an individual-based model of IBT adapted to the gut, we demonstrate that increasing the length of a flow-through ecosystem is associated with increased species diversity. We delve into the possible clinical implications of these SARs in the American Gut Cohort. Consistent with prior observations that lower alpha-diversity is a risk factor for Clostridioides difficile infection (CDI), we found that individuals who reported a history of CDI were shorter than those who did not and that this relationship appeared to be mediated by alpha-diversity. We also observed that vegetable consumption mitigated this risk increase, also by mediation through alpha-diversity. In summary, we find that body size and gut microbiome diversity show a robust positive association, that this macroecological scaling relationship is related to CDI risk, and that greater vegetable intake can mitigate this effect.

Identification of Bacterial Metabolites Modulating Breast Cancer Cell Proliferation and Epithelial-Mesenchymal Transition

Breast cancer patients are characterized by the oncobiotic transformation of multiple microbiome communities, including the gut microbiome. Oncobiotic transformation of the gut microbiome impairs the production of antineoplastic bacterial metabolites. The goal of this study was to identify bacterial metabolites with antineoplastic properties. We constructed a 30-member bacterial metabolite library and screened the library compounds for effects on cell proliferation and epithelial-mesenchymal transition. The metabolites were applied to 4T1 murine breast cancer cells in concentrations corresponding to the reference serum concentrations. However, yric acid, glycolic acid, d-mannitol, 2,3-butanediol, and trans-ferulic acid exerted cytostatic effects, and 3-hydroxyphenylacetic acid, 4-hydroxybenzoic acid, and vanillic acid exerted hyperproliferative effects. Furthermore, 3-hydroxyphenylacetic acid, 4-hydroxybenzoic acid, 2,3-butanediol, and hydrocinnamic acid inhibited epithelial-to-mesenchymal (EMT) transition. We identified redox sets among the metabolites (d-mannitol-d-mannose, 1-butanol-butyric acid, ethylene glycol-glycolic acid-oxalic acid), wherein only one partner within the set (d-mannitol, butyric acid, glycolic acid) possessed bioactivity in our system, suggesting that changes to the local redox potential may affect the bacterial secretome. Of the nine bioactive metabolites, 2,3-butanediol was the only compound with both cytostatic and anti-EMT properties.