The fecal metabolome as a functional readout of the gut microbiome

Host genetics and gut microbiota synergistically regulate feed utilization in egg-type chickens

BACKGROUND

Feed efficiency is a crucial economic trait in poultry industry. Both host genetics and gut microbiota influence feed efficiency. However, the associations between gut microbiota and host genetics, as well as their combined contributions to feed efficiency in laying hens during the late laying period, remain largely unclear.

METHODS

In total, 686 laying hens were used for whole-genome resequencing and liver transcriptome sequencing. 16S rRNA gene sequencing was conducted on gut chyme (duodenum, jejunum, ileum, and cecum) and fecal samples from 705 individuals. Bioinformatic analysis was performed by integrating the genome, transcriptome, and microbiome to screen for key genetic variations, genes, and gut microbiota associated with feed efficiency.

RESULTS

The heritability of feed conversion ratio (FCR) and residual feed intake (RFI) was determined to be 0.28 and 0.48, respectively. The ileal and fecal microbiota accounted for 15% and 10% of the FCR variance, while the jejunal, cecal, and fecal microbiota accounted for 20%, 11%, and 10% of the RFI variance. Through SMR analysis based on summary data from liver eQTL mapping and GWAS, we further identified four protein-coding genes, SUCLA2, TNFSF13B, SERTM1, and MARVELD3, that influence feed efficiency in laying hens. The SUCLA2 and TNFSF13B genes were significantly associated with SNP 1:25664581 and SNP rs312433097, respectively. SERTM1 showed significant associations with rs730958360 and 1:33542680 and is a potential causal gene associated with the abundance of Corynebacteriaceae in feces. MARVELD3 was significantly associated with the 1:135348198 and was significantly correlated with the abundance of Enterococcus in ileum. Specifically, a lower abundance of Enterococcus in ileum and a higher abundance of Corynebacteriaceae in feces were associated with better feed efficiency.

CONCLUSIONS

This study confirms that both host genetics and gut microbiota can drive variations in feed efficiency. A small portion of the gut microbiota often interacts with host genes, collectively enhancing feed efficiency. Therefore, targeting both the gut microbiota and host genetic variation by supporting more efficient taxa and selective breeding could improve feed efficiency in laying hens during the late laying period.

Fecal microbiota transplantation accelerates restoration of florfenicol-disturbed intestinal microbiota in a fish model

Antibiotic-induced dysbiosis in the fish gut causes significant adverse effects. We use fecal microbiota transplantation (FMT) to accelerate the restoration of florfenicol-perturbed intestinal microbiota in koi carp, identifying key bacterial populations and metabolites involved in the recovery process through microbiome and metabolome analyses. We demonstrate that florfenicol disrupts intestinal microbiota, reducing beneficial genera such as Lactobacillus, Bifidobacterium, Bacteroides, Romboutsia, and Faecalibacterium, and causing mucosal injuries. Key metabolites, including aromatic amino acids and glutathione-related compounds, are diminished. We show that FMT effectively restores microbial populations, repairs intestinal damage, and normalizes critical metabolites, while natural recovery is less effective. Spearman correlation analyses reveal strong associations between the identified bacterial genera and the levels of aromatic amino acids and glutathione-related metabolites. This study underscores the potential of FMT to counteract antibiotic-induced dysbiosis and maintain fish intestinal health. The restored microbiota and normalized metabolites provide a basis for developing personalized probiotic therapies for fish.

Alterations of gut microbiota and its metabolomics in children with 6PPDQ, PBDE, PCB, and metal(loid) exposure

The composition and metabolites of the gut microbiota can be altered by environmental pollutants. However, the effect of co-exposure to multiple pollutants on the human gut microbiota has not been sufficiently studied. In this study, gut microorganisms and their metabolites were compared between 33 children from Guiyu, an e-waste dismantling and recycling area, and 34 children from Haojiang, a healthy environment. The exposure level was assessed by estimating the daily intake (EDI) of polybrominated diphenyl ethers (PBDEs), polychlorinated biphenyls (PCBs), 6PPD-quinone (6PPDQ), and metal(loid)s in kindergarten dust. Significant correlations were found between the EDIs of 6PPDQ, BDE28, PCB52, Ni, Cu, and the composition of gut microbiota and specific metabolites. The Bayesian kernel machine regression model showed negative correlations between the EDIs of five pollutants (6PPDQ, BDE28, PCB52, Ni, and Cu) and the composition of gut microbiota. The EDIs of these five pollutants were positively correlated with the levels of the metabolite 2,4-diaminobutyric acid, while negatively correlated with the levels of d-erythro-sphingosine and d-threitol. Our study suggests that exposure to 6PPDQ, BDE28, PCB52, Ni, and Cu in kindergarten dust is associated with alterations in the composition and metabolites of the gut microbiota. These alterations may be associated with children's health.

Landscapes of maternal and neonatal gut microbiome and plasma metabolome signatures and their interaction in gestational diabetes mellitus

Gestational diabetes mellitus (GDM) is prevalent among pregnant individuals and is linked to increased risks for both mothers and fetuses. Although GDM is known to cause disruptions in gut microbiota and metabolites, their potential transmission to the fetus has not been fully explored. This study aimed to characterize the similarities in microbial and metabolic signatures between mothers with GDM and their neonates as well as the interactions between these signatures. This study included 89 maternal-neonate pairs (44 in the GDM group and 45 in the normoglycemic group). We utilized 16S rRNA gene sequencing and untargeted metabolomics to analyze the gut microbiota and plasma metabolomics of mothers and neonates. Integrative analyses were performed to elucidate the interactions between these omics. Distinct microbial and metabolic signatures were observed in GDM mothers and their neonates compared to those in the normoglycemic group. Fourteen genera showed similar alterations across both groups. Metabolites linked to glucose, lipid, and energy metabolism were differentially influenced in GDM, with similar trends observed in both mothers and neonates in the GDM group. Network analysis indicated significant associations between Qipengyuania and metabolites related to bile acid metabolism in mothers and newborns. Furthermore, we observed a significant correlation between several genera and metabolites and clinical phenotypes in normoglycemic mothers and newborns, but these correlations were disrupted in the GDM group. Our findings suggest that GDM consistently affects both the microbiota and metabolome in mothers and neonates, thus elucidating the mechanism underlying metabolic transmission across generations. These insights contribute to knowledge regarding the multiomics interactions in GDM and underscore the need to further investigate the prenatal environmental impacts on offspring metabolism.

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.

The Food Sources in Western Diets Modulate Obesity Development, Insulin Sensitivity, and the Plasma and Cecal Metabolome in Mice

SCOPE

Dietary constituents modulate development of obesity and type 2 diabetes. The metabolic impact from different food sources in western diets (WD) on obesity development is not fully elucidated. This study aims to identify dietary sources that differentially affect obesity development and the metabolic processes involved.

METHODS AND RESULTS

Mice were fed isocaloric WDs with protein and fat from different food groups, including egg and dairy, terrestrial meat, game meat, marine, vegetarian, and a mixture of all. This study evaluates development of obesity, glucose tolerance, insulin sensitivity, and plasma and cecal metabolome. WD based on marine or vegetarian food sources protects male mice from obesity development and insulin resistance, whereas meat-based diets promote obesity. The intake of different food sources induces marked differences in the lipid-related plasma metabolome, particularly impacting phosphatidylcholines. Fifty-nine lipid-related plasma metabolites are positively associated with adiposity and a distinct cecal metabolome is found in mice fed a marine diet.

CONCLUSION

This study demonstrates differences in obesity development between the food groups. Diet specific metabolomic signatures in plasma and cecum associated with adiposity, where a marine based diet modulates the level of plasma and cecal phosphatidylcholines in addition to preventing obesity development.

Alteration of Fecal Microbiota, Fecal Metabolites, and Serum Metabolites in Dairy Cows with Pre-Retained Placenta

Retained placenta (RP) affects lactation and fertility in dairy cows and causes economic losses to the dairy industry. Therefore, screening for early warning of this disease is important. This study used multi omics techniques to reveal the metabolic differences of dairy cows before RP onset and to find potential warning markers. Fecal samples and serum samples of 90 healthy Holstein cows were collected 7 days pre-calving; 10 healthy and 10 RP cows were enrolled according to normal expulsion of fetal membranes after calving. Fecal samples were subjected to 16S rRNA sequencing and untargeted metabolomics analysis, while plasma was analyzed using targeted metabolomics. Pathogenic bacteria levels increased in the intestines of cows with RP compared to those in healthy cows. Lipid metabolites constituted the largest proportion of differential metabolites between feces and plasma. Six potential warning markers for RP in cows were identified, including two fecal microbiomics markers (Oscillospiraceae UCG-005 and Escherichia-Shigella), one fecal untargeted metabolomics marker (N-acetylmuramic acid), and three plasma targeted metabolomics markers (glycylcholic acid-3 sulfate, 7-ketolithocholic acid, and 12-ketolithocholic acid). These biomarkers can predict RP occurrence in the early perinatal period. These results lay a theoretical foundation for early nutritional intervention and pathogenesis research in dairy cows.

Untargeted faecal metabolomics for the discovery of biomarkers and treatment targets for inflammatory bowel diseases

The gut microbiome has been recognised as a key component in the pathogenesis of inflammatory bowel diseases (IBD), and the wide range of metabolites produced by gut bacteria are an important mechanism by which the human microbiome interacts with host immunity or host metabolism. High-throughput metabolomic profiling and novel computational approaches now allow for comprehensive assessment of thousands of metabolites in diverse biomaterials, including faecal samples. Several groups of metabolites, including short-chain fatty acids, tryptophan metabolites and bile acids, have been associated with IBD. In this Recent Advances article, we describe the contribution of metabolomics research to the field of IBD, with a focus on faecal metabolomics. We discuss the latest findings on the significance of these metabolites for IBD prognosis and therapeutic interventions and offer insights into the future directions of metabolomics research.

The individual response to antibiotics and diet - insights into gut microbial resilience and host metabolism

Antibiotic use disrupts microbial composition and activity in humans, but whether this disruption in turn affects host metabolic health is unclear. Cohort studies show associations between antibiotic use and an increased risk of developing obesity and type 2 diabetes mellitus. Here, we review available clinical trials and show the disruptive effect of antibiotic use on the gut microbiome in humans, as well as its impact on bile acid metabolism and microbial metabolites such as short-chain fatty acids. Placebo-controlled human studies do not show a consistent effect of antibiotic use on body weight and insulin sensitivity at a population level, but rather an individual-specific or subgroup-specific response. This response to antibiotic use is affected by the resistance and resilience of the gut microbiome, factors that determine the extent of disruption and the speed of recovery afterwards. Nutritional strategies to improve the composition and functionality of the gut microbiome, as well as its recovery after antibiotic use (for instance, with prebiotics), require a personalized approach to increase their efficacy. Improved insights into key factors that influence the individual-specific response to antibiotics and dietary intervention may lead to better efficacy in reversing or preventing antibiotic-induced microbial dysbiosis as well as strategies for preventing cardiometabolic diseases.

The dual role of 20(S)-protopanaxadiol in alleviating pulmonary fibrosis through the gut-lung axis

BACKGROUND

Pulmonary Fibrosis (PF) is a progressive lung disease characterized by the diffuse interstitial tissue, leading to severe breathing difficulties. The existing treatment methods are primarily aimed at slowing the progression of the disease, underscoring the urgent need to discover new drug interventions targeting novel sites. The "gut-lung axis" represents a complex bidirectional communication system where the gut microbiota not only influences lung immunity but also responds to lung-derived signals. Recent advances have uncovered that alterations in gut microbiota composition can significantly impact respiratory diseases, offering new insights into their pathogenesis and potential therapeutic approaches.

METHODS

This study is based on the fundamental concepts of the lung-gut axis and our previous research, further exploring the potential mechanisms of 20(S)-Protopanaxadiol (PPD) in ginseng against PF. We utilized a bleomycin-induced mouse model of PF and employed metabolomics and 16S rRNA sequencing to investigate the pathways through which PPD regulates the pulmonary fibrosis process via the gut-lung axis. Finally, we employed strategies such as antibiotic-induced microbiota disruption and fecal microbiota transplantation (FMT) to provide a comprehensive perspective on how PPD regulates pulmonary fibrosis through gut microbiota.

RESULTS

The results of the bleomycin (BLM) mouse model of PF proved that PPD can directly act on the glycolysis- related metabolic reprogramming process in lung and the AMPK/STING pathway to improve PF. Combined the analysis of gut microbiota and related metabolites, we found that PPD can regulate the process of PF through the gut-lung axis target points G6PD and SPHK1. FMT and antibiotic-induced microbiota disruption further confirmed intermediate effect of gut microbiota in PF process and the treatment of PPD. Our study suggests that PPD can alleviate the process of pulmonary fibrosis either by directly acting on the lungs or by regulating the gut microbiota.

CONCLUSION

This study positions PPD as a vanguard in the therapeutic landscape for pulmonary fibrosis, offering a dual mechanism of action that encompasses both modulation of gut microbiota and direct intervention at molecular targets. These insights highlight the immense therapeutic potential of harnessing the gut-lung axis.

Mapping the gut microecological multi-omics signatures to serum metabolome and their impact on cardiometabolic health in elderly adults

BACKGROUND

Mapping gut microecological features to serum metabolites (SMs) will help identify functional links between gut microbiome and cardiometabolic health.

METHODS

This study encompassed 836-1021 adults over 9.7 year in a cohort, assessing metabolic syndrome (MS), carotid atherosclerotic plaque (CAP), and other metadata triennially. We analyzed mid-term microbial metagenomics, targeted fecal and serum metabolomics, host genetics, and serum proteomics.

FINDINGS

Gut microbiota and metabolites (GMM) accounted for 15.1% overall variance in 168 SMs, with individual GMM factors explaining 5.65%-10.1%, host genetics 3.23%, and sociodemographic factors 5.95%. Specifically, GMM elucidated 5.5%-49.6% variance in the top 32 GMM-explained SMs. Each 20% increase in the 32 metabolite score (derived from the 32 SMs) correlated with 73% (95% confidence interval [CI]: 53%-95%) and 19% (95% CI: 11%-27%) increases in MS and CAP incidences, respectively. Among the 32 GMM-explained SMs, sebacic acid, indoleacetic acid, and eicosapentaenoic acid were linked to MS or CAP incidence. Serum proteomics revealed certain proteins, particularly the apolipoprotein family, mediated the relationship between GMM-SMs and cardiometabolic risks.

INTERPRETATION

This study reveals the significant influence of GMM on SM profiles and illustrates the intricate connections between GMM-explained SMs, serum proteins, and the incidence of MS and CAP, providing insights into the roles of gut dysbiosis in cardiometabolic health via regulating blood metabolites.

FUNDING

This study was jointly supported by the National Natural Science Foundation of China, Key Research and Development Program of Guangzhou, 5010 Program for Clinical Research of Sun Yat-sen University, and the 'Pioneer' and 'Leading goose' R&D Program of Zhejiang.

Comparative Metabolomics and Microbiome Analysis of Ethanol versus OMNImet/gene•GUT Fecal Stabilization

Metabolites from feces provide important insights into the functionality of the gut microbiome. As immediate freezing is not always feasible in gut microbiome studies, there is a need for sampling protocols that provide the stability of the fecal metabolome and microbiome at room temperature (RT). Here, we investigated the stability of various metabolites and the microbiome (16S rRNA) in feces collected in 95% ethanol (EtOH) and commercially available sample collection kits with specific preservatives OMNImet•GUT/OMNIgene•GUT. To simulate field-collection scenarios, the samples were stored at different temperatures at varying durations (24 h + 4 °C, 24 h RT, 36 h RT, 48 h RT, and 7 days RT) and compared to aliquots immediately frozen at -80 °C. We applied several targeted and untargeted metabolomics platforms to measure lipids, polar metabolites, endocannabinoids, short-chain fatty acids (SCFAs), and bile acids (BAs). We found that SCFAs in the nonstabilized samples increased over time, while a stable profile was recorded in sample aliquots stored in 95% EtOH and OMNImet•GUT. When comparing the metabolite levels between aliquots stored at room temperature and at +4 °C, we detected several changes in microbial metabolites, including multiple BAs and SCFAs. Taken together, we found that storing samples at RT and stabilizing them in 95% EtOH yielded metabolomic results comparable to those from flash freezing. We also found that the overall composition of the microbiome did not vary significantly between different storage types. However, notable differences were observed in the α diversity. Altogether, the stability of the metabolome and microbiome in 95% EtOH provided results similar to those of the validated commercial collection kits OMNImet•GUT and OMNIgene•GUT, respectively.

Machine Learning Metabolomics Profiling of Dietary Interventions from a Six-Week Randomised Trial

Metabolomics can uncover physiological responses to prebiotic fibre and omega-3 fatty acid supplements with known health benefits and identify response-specific metabolites. We profiled 534 stool and 799 serum metabolites in 64 healthy adults following a 6-week randomised trial comparing daily omega-3 versus inulin supplementation. Elastic net regressions were used to separately identify the serum and stool metabolites whose change in concentration discriminated between the two types of supplementations. Random forest was used to explore the gut microbiome's contribution to the levels of the identified metabolites from matching stool samples. Changes in serum 3-carboxy-4-methyl-5-propyl-2-furanpropanoate and indoleproprionate levels accurately discriminated between fibre and omega-3 (area under the curve (AUC) = 0.87 [95% confidence interval (CI): 0.63-0.99]), while stool eicosapentaenoate indicated omega-3 supplementation (AUC = 0.86 [95% CI: 0.64-0.98]). Univariate analysis also showed significant increases in indoleproprionate with fibre, 3-carboxy-4-methyl-5-propyl-2-furanpropanoate, and eicosapentaenoate with omega-3. Out of these, only the change in indoleproprionate was partly explained by changes in the gut microbiome composition (AUC = 0.61 [95% CI: 0.58-0.64] and Rho = 0.21 [95% CI: 0.08-0.34]) and positively correlated with the increase in the abundance of the genus Coprococcus (p = 0.005). Changes in three metabolites discriminated between fibre and omega-3 supplementation. The increase in indoleproprionate with fibre was partly explained by shifts in the gut microbiome, particularly Coprococcus, previously linked to better health.

Multiomics Reveals the Microbiota and Metabolites Associated with Sperm Quality in Rongchang Boars

In this study, we investigated the correlation between the composition and function of the gut microbiota and the semen quality of Rongchang boars. Significant differences in gut microbial composition between boars with high (group H) and low (group L) semen utilization rates were identified through 16S rRNA gene sequencing, with 18 differential microbes observed at the genus level. Boars with lower semen utilization rates exhibited a higher relative abundance of Treponema, suggesting its potential role in reducing semen quality. Conversely, boars with higher semen utilization rates showed increased relative abundances of Terrisporobacter, Turicibacter, Stenotrophomonas, Clostridium sensu stricto 3, and Bifidobacterium, with Stenotrophomonas and Clostridium sensu stricto 3 showing a significant positive correlation with semen utilization rates. The metabolomic analyses revealed higher levels of gluconolactone, D-ribose, and 4-pyridoxic acid in the H group, with 4 pyridoxic acid and D-ribose showing a significant positive correlation with Terrisporobacter and Clostridium sensu stricto 3, respectively. In contrast, the L group showed elevated levels of D-erythrose-4-phosphate, which correlated negatively with Bifidobacterium and Clostridium sensu stricto 3. These differential metabolites were enriched in the pentose phosphate pathway, vitamin B6 metabolism, and antifolate resistance, potentially influencing semen quality. These findings provide new insights into the complex interplay between the gut microbiota and boar reproductive health and may offer important information for the discovery of disease biomarkers and reproductive health management.

Offline Two-Dimensional Liquid Chromatography-Mass Spectrometry for Deep Annotation of the Fecal Metabolome Following Fecal Microbiota Transplantation

Biological interpretation of untargeted LC-MS-based metabolomics data depends on accurate compound identification, but current techniques fall short of identifying most features that can be detected. The human fecal metabolome is complex, variable, incompletely annotated, and serves as an ideal matrix to evaluate novel compound identification methods. We devised an experimental strategy for compound annotation using multidimensional chromatography and semiautomated feature alignment and applied these methods to study the fecal metabolome in the context of fecal microbiota transplantation (FMT) for recurrent C. difficile infection. Pooled fecal samples were fractionated using semipreparative liquid chromatography and analyzed by an orthogonal LC-MS/MS method. The resulting spectra were searched against commercial, public, and local spectral libraries, and annotations were vetted using retention time alignment and prediction. Multidimensional chromatography yielded more than a 2-fold improvement in identified compounds compared to conventional LC-MS/MS and successfully identified several rare and previously unreported compounds, including novel fatty-acid conjugated bile acid species. Using an automated software-based feature alignment strategy, most metabolites identified by the new approach could be matched to features that were detected but not identified in single-dimensional LC-MS/MS data. Overall, our approach represents a powerful strategy to enhance compound identification and biological insight from untargeted metabolomics data.

Integrated UHPLC-MS untargeted metabolomics and gut microbe metabolism pathway-targeted metabolomics to reveal the prevention mechanism of Gushudan on kidney-yang-deficiency-syndrome rats

Gushudan (GSD) was a traditional Chinese prescription with the remarkable effect of kidney-tonifying and bone-strengthening. However, the potential prevention mechanisms of the GSD on kidney-yang-deficiency-syndrome (KYDS) and its regulation on gut microbe metabolism still need to be further systematically investigated. This study established untargeted urinary metabolomics based on RP/HILIC-UHPLC-Q-Orbitrap HRMS and combined with multivariate statistical analysis to discover differential metabolites and key metabolic pathways. And the gut microbe metabolism pathway-targeted metabolomic based on HILIC-UHPLC-MS/MS was developed and validated to simultaneously determine 15 gut microbe-mediated metabolites in urine samples from the control group (CON), KYDS model group (MOD), GSD-treatment group (GSD) and positive group (POS). The results showed that a total of 36 differential metabolites were discovered in untargeted metabolomics. These differential metabolites included proline, cytosine, butyric acid and nicotinic acid, which were primarily involved in the gut microbe metabolism, amino acid metabolism, energy metabolism and nucleotide metabolism. And GSD played a role in preventing KYDS by regulating these metabolic pathways. The targeted metabolomics found that the levels of 10 gut microbe-mediated metabolites had significant differences in different groups. Among them, compared with the CON group, the levels of lysine, tryptophan, phenylacetylglycine and hippuric acid were increased in the MOD group, while the levels of threonine, leucine, dimethylamine, trimethylamine, succinic acid and butyric acid were decreased, which verified the disorders of gut microbe metabolism in the KYDS rats and GSD had a significant regulatory effect on this disorder. As well as by comparing analysis, it was found that the experimental results were consistent with previous metabolomics and microbiomics of fecal samples. Therefore, this integrated strategy of untargeted and targeted metabolomics not only elucidated the potential prevention mechanism of GSD on KYDS, but also provided a scientific basis for GSD preventing KYDS via the "gut-kidney" axis.

Unveiling the oral-gut connection: chronic apical periodontitis accelerates atherosclerosis via gut microbiota dysbiosis and altered metabolites in apoE-/- Mice on a high-fat diet

The aim of this study was to explore the impact of chronic apical periodontitis (CAP) on atherosclerosis in apoE-/- mice fed high-fat diet (HFD). This investigation focused on the gut microbiota, metabolites, and intestinal barrier function to uncover potential links between oral health and cardiovascular disease (CVD). In this study, CAP was shown to exacerbate atherosclerosis in HFD-fed apoE-/- mice, as evidenced by the increase in plaque size and volume in the aortic walls observed via Oil Red O staining. 16S rRNA sequencing revealed significant alterations in the gut microbiota, with harmful bacterial species thriving while beneficial species declining. Metabolomic profiling indicated disruptions in lipid metabolism and primary bile acid synthesis, leading to elevated levels of taurochenodeoxycholic acid (TCDCA), taurocholic acid (TCA), and tauroursodeoxycholic acid (TDCA). These metabolic shifts may contribute to atherosclerosis development. Furthermore, impaired intestinal barrier function, characterized by reduced mucin expression and disrupted tight junction proteins, was observed. The increased intestinal permeability observed was positively correlated with the severity of atherosclerotic lesions, highlighting the importance of the intestinal barrier in cardiovascular health. In conclusion, this research underscores the intricate interplay among oral health, gut microbiota composition, metabolite profiles, and CVD incidence. These findings emphasize the importance of maintaining good oral hygiene as a potential preventive measure against cardiovascular issues, as well as the need for further investigations into the intricate mechanisms linking oral health, gut microbiota, and metabolic pathways in CVD development.

Campylobacter infection of young children in Colombia and its impact on the gastrointestinal environment

Campylobacter infections are a leading cause of bacterial-derived gastroenteritis worldwide with particularly profound impacts on pediatric patients in low-and-middle income countries. It remains unclear how Campylobacter impacts these hosts, though it is becoming increasingly evident that it is a multifactorial process that depends on the host immune response, the gastrointestinal microbiota, various bacterial factors, and host nutritional status. Since these factors likely vary between adult and pediatric patients in different regions of the world, it is important that studies define these attributes in well characterized clinical cohorts in diverse settings. In this study, we analyzed the fecal microbiota and the metabolomic and micronutrient profiles of asymptomatic and symptomatic pediatric patients in Colombia that were either infected or uninfected with Campylobacter during a case-controlled study on acute diarrheal disease. Here, we report that the microbiome of Campylobacter- infected children only changed in their abundance of Campylobacter spp. despite the inclusion of children with or without diarrhea. In addition to increased Campylobacter, computational models were used to identify fecal metabolites that were associated with Campylobacter infection and found that glucose-6-phosphate and homovanillic acid were the strongest predictors of infection in these pediatric patients, which suggest that colonocyte metabolism are impacted during infection. Despite changes to the fecal metabolome, the concentrations of intestinal minerals and trace elements were not significantly impacted by Campylobacter infection, but were elevated in uninfected children with diarrhea.

Importance

Gastrointestinal infection with pathogenic Campylobacter species has long been recognized as a significant cause of human morbidity. Recently, it has been observed that pediatric populations in low-and-middle income countries are uniquely impacted by these organisms in that infected children can be persistently colonized, develop enteric dysfunction, and exhibit reduced development and growth. While the association of Campylobacter species with these long-term effects continues to emerge, the impact of infection on the gastrointestinal environment of these children remains uncharacterized. To address this knowledge gap, our group leveraged clinical samples collected during a previous study on gastrointestinal infections in pediatric patients to examine the fecal microbiota, metabolome, and micronutrient profiles of those infected with Campylobacter species, and found that the metabolome was impacted in a way that suggests gastrointestinal cell metabolism is affected during infection, which is some of the first data indicating how gastrointestinal health in these patients may be affected.

Effect of 1-year lifestyle intervention with energy-reduced Mediterranean diet and physical activity promotion on the gut metabolome and microbiota: a randomized clinical trial

BACKGROUND

The health benefits of the Mediterranean diet (MedDiet) have been linked to the presence of beneficial gut microbes and related metabolites. However, its impact on the fecal metabolome remains poorly understood.

OBJECTIVES

Our goal was to investigate the weight-loss effects of a 1-y lifestyle intervention based on an energy-reduced MedDiet coupled with physical activity (intervention group), compared with an ad libitum MedDiet (control group), on fecal metabolites, fecal microbiota, and their potential association with cardiovascular disease risk factors.

METHODS

A total of 400 participants (200 from each study group), aged 55-75 y, and at high cardiovascular disease risk, were included. Dietary and lifestyle information, anthropometric measurements, blood biochemical parameters, and stool samples were collected at baseline and after 1 y of follow-up. Liquid chromatography-tandem mass spectrometry was used to profile endogenous fecal metabolites, and 16S amplicon sequencing was employed to profile the fecal microbiota.

RESULTS

Compared with the control group, the intervention group exhibited greater weight loss and improvement in various cardiovascular disease risk factors. We identified intervention effects on 4 stool metabolites and subnetworks primarily composed of bile acids, ceramides, and sphingosines, fatty acids, carnitines, nucleotides, and metabolites of purine and the Krebs cycle. Some of these were associated with changes in several cardiovascular disease risk factors. In addition, we observed a reduction in the abundance of the genera Eubacterium hallii group and Dorea, and an increase in alpha diversity in the intervention group after 1 y of follow-up. Changes in the intervention-related microbiota profiles were also associated with alterations in different fecal metabolite subnetworks and some cardiovascular disease risk factors.

CONCLUSIONS

An intervention based on an energy-reduced MedDiet and physical activity promotion, compared with an ad libitum MedDiet, was associated with improvements in cardiometabolic risk factors, potentially through modulation of the fecal microbiota and metabolome. This trial was registered at https://www.isrctn.com/ as ISRCTN89898870 (https://doi.org/10.1186/ISRCTN89898870).

A metabolomic perspective on the mechanisms by which environmental pollutants and lifestyle lead to male infertility

The incidence of male infertility (MI) is rising annually. According to epidemiological studies, environmental pollution (e.g., organic, inorganic, and air pollutants), occupational exposure (e.g., high temperature, organic solvents, and pesticides), and poor lifestyle (e.g., diet, sleep, smoking, alcohol consumption, and exercise) are important non-genetic causative factors of MI. Due to multiple and complex causative factors, the dose-effect relationship, and the uncertainty of pathogenicity, the pathogenesis of MI is far from fully clarified. Recent data show that the pathogenesis of MI can be monitored by the metabolites in serum, seminal plasma, urine, testicular tissue, sperm, and other biological samples. It is considered that these metabolites are closely related to MI phenotypes and can directly reflect the individual pathological and physiological conditions. Therefore, qualitative and quantitative analysis of the metabolome, the related metabolic pathways, and the identification of biomarkers will help to explore the MI-related metabolic problems and provide valuable insights into its pathogenic mechanisms. Here, we summarized new findings in MI metabolomics biomarkers research and their abnormal metabolic pathways triggered by the presented non-genetic risk factors, providing a metabolic landscape of semen and seminal plasma in general MI patients. Then, we compared the similarities and differences in semen and seminal plasma biomarkers between MI patients exposed to environmental and poor lifestyle factors and MI patients in general, and summarized some common biomarkers. We provide a better understanding of the biological underpinnings of MI pathogenesis, which might offer novel diagnostic, prognostic, and precise treatment approaches to MI.

Approach to the diagnosis and management of dysbiosis

All microorganisms like bacteria, viruses and fungi that reside within a host environment are considered a microbiome. The number of bacteria almost equal that of human cells, however, the genome of these bacteria may be almost 100 times larger than the human genome. Every aspect of the physiology and health can be influenced by the microbiome living in various parts of our body. Any imbalance in the microbiome composition or function is seen as dysbiosis. Different types of dysbiosis are seen and the corresponding symptoms depend on the site of microbial imbalance. The contribution of the intestinal and extra-intestinal microbiota to influence systemic activities is through interplay between different axes. Whole body dysbiosis is a complex process involving gut microbiome and non-gut related microbiome. It is still at the stage of infancy and has not yet been fully understood. Dysbiosis can be influenced by genetic factors, lifestyle habits, diet including ultra-processed foods and food additives, as well as medications. Dysbiosis has been associated with many systemic diseases and cannot be diagnosed through standard blood tests or investigations. Microbiota derived metabolites can be analyzed and can be useful in the management of dysbiosis. Whole body dysbiosis can be addressed by altering lifestyle factors, proper diet and microbial modulation. The effect of these interventions in humans depends on the beneficial microbiome alteration mostly based on animal studies with evolving evidence from human studies. There is tremendous potential for the human microbiome in the diagnosis, treatment, and prognosis of diseases, as well as, for the monitoring of health and disease in humans. Whole body system-based approach to the diagnosis of dysbiosis is better than a pure taxonomic approach. Whole body dysbiosis could be a new therapeutic target in the management of various health conditions.

Alterations in the gut microbiota and its metabolites contribute to metabolic maladaptation in dairy cows during the development of hyperketonemia

Metabolic maladaptation in dairy cows after calving can lead to long-term elevation of ketones, such as β-hydroxybutyrate (BHB), representing the condition known as hyperketonemia, which greatly influences the health and production performance of cows during the lactation period. Although the gut microbiota is known to alter in dairy cows with hyperketonemia, the association of microbial metabolites with development of hyperketonemia remains unknown. In this study, we performed a multi-omics analysis to investigate the associations between fecal microbial community, fecal/plasma metabolites, and serum markers in hyperketonemic dairy cows during the transition period. Dynamic changes in the abundance of the phyla Verrucomicrobiota and Proteobacteria were detected in the gut microbiota of dairy cows, representing an adaptation to enhanced lipolysis and abnormal glucose metabolism after calving. Random forest and univariate analyses indicated that Frisingicoccus is a key bacterial genus in the gut of cows during the development of hyperketonemia, and its abundance was positively correlated with circulating branched-chain amino acid levels and the ketogenesis pathway. Taurodeoxycholic acid, belonging to the microbial metabolite, was strongly correlated with an increase in blood BHB level, and the levels of other secondary bile acid in the feces and plasma were altered in dairy cows prior to the diagnosis of hyperketonemia, which link the gut microbiota and hyperketonemia. Our results suggest that alterations in the gut microbiota and its metabolites contribute to excessive lipolysis and insulin insensitivity during the development of hyperketonemia, providing fundamental knowledge about manipulation of gut microbiome to improve metabolic adaptability in transition dairy cows.IMPORTANCEAccumulating evidence is pointing to an important association between gut microbiota-derived metabolites and metabolic disorders in humans and animals; however, this association in dairy cows from late gestation to early lactation is poorly understood. To address this gap, we integrated longitudinal gut microbial (feces) and metabolic (feces and plasma) profiles to characterize the phenotypic differences between healthy and hyperketonemic dairy cows from late gestation to early lactation. Our results demonstrate that cows underwent excessive lipid mobilization and insulin insensitivity before hyperketonemia was evident. The bile acids are functional readouts that link gut microbiota and host phenotypes in the development of hyperketonemia. Thus, this work provides new insight into the mechanisms involved in metabolic adaptation during the transition period to adjust to the high energy and metabolic demands after calving and during lactation, which can offer new strategies for livestock management involving intervention of the gut microbiome to facilitate metabolic adaptation.

Mapping multi-omics characteristics related to short-term PM2.5 trajectory and their impact on type 2 diabetes in middle-aged and elderly adults in Southern China

The relationship between PM2.5 and metabolic diseases, including type 2 diabetes (T2D), has become increasingly prominent, but the molecular mechanism needs to be further clarified. To help understand the mechanistic association between PM2.5 exposure and human health, we investigated short-term PM2.5 exposure trajectory-related multi-omics characteristics from stool metagenome and metabolome and serum proteome and metabolome in a cohort of 3267 participants (age: 64.4 ± 5.8 years) living in Southern China. And then integrate these features to examine their relationship with T2D. We observed significant differences in overall structure in each omics and 193 individual biomarkers between the high- and low-PM2.5 groups. PM2.5-related features included the disturbance of microbes (carbohydrate metabolism-associated Bacteroides thetaiotaomicron), gut metabolites of amino acids and carbohydrates, serum biomarkers related to lipid metabolism and reducing n-3 fatty acids. The patterns of overall network relationships among the biomarkers differed between T2D and normal participants. The subnetwork membership centered on the hub nodes (fecal rhamnose and glycylproline, serum hippuric acid, and protein TB182) related to high-PM2.5, which well predicted higher T2D prevalence and incidence and a higher level of fasting blood glucose, HbA1C, insulin, and HOMA-IR. Our findings underline crucial PM2.5-related multi-omics biomarkers linking PM2.5 exposure and T2D in humans.

Atherosclerosis, gut microbiome, and exercise in a meta-omics perspective: a literature review

Background

Cardiovascular diseases are the leading cause of death worldwide, significantly impacting public health. Atherosclerotic cardiovascular diseases account for the majority of these deaths, with atherosclerosis marking the initial and most critical phase of their pathophysiological progression. There is a complex relationship between atherosclerosis, the gut microbiome's composition and function, and the potential mediating role of exercise. The adaptability of the gut microbiome and the feasibility of exercise interventions present novel opportunities for therapeutic and preventative approaches.

Methodology

We conducted a comprehensive literature review using professional databases such as PubMed and Web of Science. This review focuses on the application of meta-omics techniques, particularly metagenomics and metabolomics, in studying the effects of exercise interventions on the gut microbiome and atherosclerosis.

Results

Meta-omics technologies offer unparalleled capabilities to explore the intricate connections between exercise, the microbiome, the metabolome, and cardiometabolic health. This review highlights the advancements in metagenomics and metabolomics, their applications in research, and examines how exercise influences the gut microbiome. We delve into the mechanisms connecting these elements from a metabolic perspective. Metagenomics provides insight into changes in microbial strains post-exercise, while metabolomics sheds light on the shifts in metabolites. Together, these approaches offer a comprehensive understanding of how exercise impacts atherosclerosis through specific mechanisms.

Conclusions

Exercise significantly influences atherosclerosis, with the gut microbiome serving as a critical intermediary. Meta-omics technology holds substantial promise for investigating the gut microbiome; however, its methodologies require further refinement. Additionally, there is a pressing need for more extensive cohort studies to enhance our comprehension of the connection among these element.

Lactobacillus johnsonii CPN23 vis-à-vis Lactobacillus acidophilus NCDC15 Improves Gut Health, Intestinal Morphometry, and Histology in Weaned Wistar Rats

The present investigation was carried out with the aim to establish the comparative efficacy of a canine-sourced probiotic meant for canine feeding and a conventional dairy-sourced probiotic. For this purpose, canine-origin Lactobacillus johnsonii CPN23 and dairy-origin Lactobacillus acidophilus NCDC15 were evaluated for potential probiotics health benefits in the rat model. Forty-eight weaned Wistar rats enrolled in this experiment of 8 weeks were fed a basal diet and divided into three dietary treatments. Rats of group I enrolled as control (CON) were given MRS placebo at 1 mL/head/day, while rats of group II (LAJ) and III (LAC) were administered with overnight MRS broth grown-culture of L. johnsonii CPN23 and L. acidophilus NCDC15, respectively, at 1 mL/head/day (108 cfu/mL). The average daily gain and net gain in body weight were significantly higher (p < 0.05) in LAJ and LAC than in CON. Fecal and digesta biochemical attributes altered (p < 0.05) positively in response to both probiotics. Total fecal and pooled digesta SCFAs were higher (p < 0.05) in both LAJ and LAC than in CON. The microbial population in cecal and colonic digesta responded (p < 0.05) positively to both probiotics. The diameter of intestinal segments was higher (p < 005) in LAJ as compared to CON. The number and height of villi in jejunum tended to be higher in LAJ as compared to CON. The humoral immune response to sheep erythrocytes as well as chicken egg-white lysozyme was higher in LAJ as compared to CON. Overall, the results of the study have demonstrated the effectiveness of the canine-sourced L. johnsonii CPN23 as a potential probiotic, with a comparatively better response than the dairy-sourced L. acidophilus NCDC15. It could thus be recommended for use in feeding dogs to help augment their health.

Integrated gut metabolome and microbiome fingerprinting reveals that dysbiosis precedes allergic inflammation in IgE-mediated pediatric cow's milk allergy

BACKGROUND

IgE-mediated cow's milk allergy (IgE-CMA) is one of the first allergies to arise in early childhood and may result from exposure to various milk allergens, of which β-lactoglobulin (BLG) and casein are the most important. Understanding the underlying mechanisms behind IgE-CMA is imperative for the discovery of novel biomarkers and the design of innovative treatment and prevention strategies.

METHODS

We report a longitudinal in vivo murine model, in which two mice strains (BALB/c and C57Bl/6) were sensitized to BLG using either cholera toxin or an oil emulsion (n = 6 per group). After sensitization, mice were challenged orally, their clinical signs monitored, antibody (IgE and IgG1) and cytokine levels (IL-4 and IFN-γ) measured, and fecal samples subjected to metabolomics. The results of the murine models were further extrapolated to fecal microbiome-metabolome data from our population of IgE-CMA (n = 22) and healthy (n = 23) children (Trial: NCT04249973), on which polar metabolomics, lipidomics and 16S rRNA metasequencing were performed. In vitro gastrointestinal digestions and multi-omics corroborated the microbial origin of proposed metabolic changes.

RESULTS

During mice sensitization, we observed multiple microbially derived metabolic alterations, most importantly bile acid, energy and tryptophan metabolites, that preceded allergic inflammation. We confirmed microbial dysbiosis, and its associated effect on metabolic alterations in our patient cohort, through in vitro digestions and multi-omics, which was accompanied by metabolic signatures of low-grade inflammation.

CONCLUSION

Our results indicate that gut dysbiosis precedes allergic inflammation and nurtures a chronic low-grade inflammation in children on elimination diets, opening important new opportunities for future prevention and treatment strategies.

Integrated annotation prioritizes metabolites with bioactivity in inflammatory bowel disease

Microbial biochemistry is central to the pathophysiology of inflammatory bowel diseases (IBD). Improved knowledge of microbial metabolites and their immunomodulatory roles is thus necessary for diagnosis and management. Here, we systematically analyzed the chemical, ecological, and epidemiological properties of ~82k metabolic features in 546 Integrative Human Microbiome Project (iHMP/HMP2) metabolomes, using a newly developed methodology for bioactive compound prioritization from microbial communities. This suggested >1000 metabolic features as potentially bioactive in IBD and associated ~43% of prevalent, unannotated features with at least one well-characterized metabolite, thereby providing initial information for further characterization of a significant portion of the fecal metabolome. Prioritized features included known IBD-linked chemical families such as bile acids and short-chain fatty acids, and less-explored bilirubin, polyamine, and vitamin derivatives, and other microbial products. One of these, nicotinamide riboside, reduced colitis scores in DSS-treated mice. The method, MACARRoN, is generalizable with the potential to improve microbial community characterization and provide therapeutic candidates.

Integrated 16S rRNA sequencing and metabolomic analysis reveals the potential protective mechanism of Germacrone on diabetic nephropathy in mice

Diabetic nephropathy (DN) is a severe complication of diabetes and the leading cause of end-stage renal disease and death. Germacrone (Ger) possesses anti-inflammatory, antioxidant and anti-DN properties. However, it is unclear whether the improvement in kidney damage caused by Ger in DN mice is related to abnormal compositions and metabolites of the gut microbiota. This study generates a mouse model of DN to explore the potent therapeutic ability and mechanism of Ger in renal function by 16S rRNA sequencing and untargeted fecal metabolomics. Although there is no significant change in microbiota diversity, the structure of the gut microbiota in the DN group is quite different. Serratia_marcescens and Lactobacillus_iners are elevated in the model group but significantly decreased after Ger intervention ( P<0.05). Under the treatment of Ger, no significant differences in the diversity and richness of the gut microbiota are observed. An imbalance in the intestinal flora leads to the dysregulation of metabolites, and non-targeted metabolomics data indicate high expression of stearic acid in the DN group, and oleic acid could serve as a potential marker of the therapeutic role of Ger in the DN model. Overall, Ger improves kidney injury in diabetic mice, in part potentially by reducing the abundance of Serratia_marcescens and Lactobacillus_iners, as well as regulating the associated increase in metabolites such as oleic acid, lithocholic acid and the decrease in stearic acid. Our research expands the understanding of the relationship between the gut microbiota and metabolites in Ger-treated DN. This contributes to the usage of natural products as a therapeutic approach for the treatment of DN via microbiota regulation.

Multi-omic integration of microbiome data for identifying disease-associated modules

Multi-omic studies of the human gut microbiome are crucial for understanding its role in disease across multiple functional layers. Nevertheless, integrating and analyzing such complex datasets poses significant challenges. Most notably, current analysis methods often yield extensive lists of disease-associated features (e.g., species, pathways, or metabolites), without capturing the multi-layered structure of the data. Here, we address this challenge by introducing "MintTea", an intermediate integration-based approach combining canonical correlation analysis extensions, consensus analysis, and an evaluation protocol. MintTea identifies "disease-associated multi-omic modules", comprising features from multiple omics that shift in concord and that collectively associate with the disease. Applied to diverse cohorts, MintTea captures modules with high predictive power, significant cross-omic correlations, and alignment with known microbiome-disease associations. For example, analyzing samples from a metabolic syndrome study, MintTea identifies a module with serum glutamate- and TCA cycle-related metabolites, along with bacterial species linked to insulin resistance. In another dataset, MintTea identifies a module associated with late-stage colorectal cancer, including Peptostreptococcus and Gemella species and fecal amino acids, in line with these species' metabolic activity and their coordinated gradual increase with cancer development. This work demonstrates the potential of advanced integration methods in generating systems-level, multifaceted hypotheses underlying microbiome-disease interactions.

Characterization of the gut microbiota and fecal and blood metabolomes under various factors in urban children from Northwest China

Introduction

Children have regional dynamics in the gut microbiota development trajectory. Hitherto, the features and influencing factors of the gut microbiota and fecal and plasma metabolites in children from Northwest China remain unclear.

Methods

Shotgun metagenomic sequencing and untargeted metabolomics were performed on 100 healthy volunteers aged 2-12 years.

Results

Age, body mass index (BMI), regular physical exercise (RPE), and delivery mode (DM) significantly affect gut microbiota and metabolites. Lactobacillus, Butyricimonas, Prevotella, Alistipes, and predicted pathway propanoate production were significantly increased with age while Bifidobacterium breve, B. animalis, B. pseudocatenulatum, Streptococcus infantis, and carbohydrate degradation were decreased. Fecal metabolome revealed that the metabolism of caffeine, amino acids, and lipid significantly increased with age while galactose metabolism decreased. Noticeably, BMI was positively associated with pathogens including Erysipelatoclostridium ramosum, Parabacteroides distasonis, Ruminococcus gnavus, and amino acid metabolism but negatively associated with beneficial Akkermansia muciniphila, Alistipes finegoldii, Eubacterium ramulus, and caffeine metabolism. RPE has increased probiotic Faecalibacterium prausnitzii and Anaerostipes hadrus, acetate and lactate production, and major nutrient metabolism in gut and plasma, but decreased pathobiont Bilophila wadsworthia, taurine degradation, and pentose phosphate pathway. Interestingly, DM affects the gut microbiota and metabolites throughout the whole childhood. Bifidobacterium animalis, Lactobacillus mucosae, L. ruminis, primary bile acid, and neomycin biosynthesis were enriched in eutocia, while anti-inflammatory Anaerofustis stercorihominis, Agathobaculum butyriciproducens, Collinsella intestinalis, and pathogenic Streptococcus salivarius, Catabacter hongkongensis, and amino acid metabolism were enriched in Cesarean section children.

Discussion

Our results provided theoretical and data foundation for the gut microbiota and metabolites in preadolescent children's growth and development in Northwest China.

Extracellular vesicles derived from Lactobacillus johnsonii promote gut barrier homeostasis by enhancing M2 macrophage polarization

INTRODUCTION

Diarrheic disease is a common intestinal health problem worldwide, causing great suffering to humans and animals. Precise manipulation strategies based on probiotics to combat diarrheic diseases have not been fully developed.

OBJECTIVES

The aim of this study was to investigate the molecular mechanisms by which probiotics manipulate macrophage against diarrheic disease.

METHODS

Metagenome reveals gut microbiome profiles of healthy and diarrheic piglets. Fecal microbial transplantation (FMT) was employed to explore the causal relationship between gut microbes and diarrhea. The protective role of probiotics and their derived extracellular vesicles (EVs) was investigated in ETEC K88-infected mice. Macrophage depletion was performed to assess the role of macrophages in EVs against diarrhea. Execution of in vitro cell co-culture and transcriptome analyses elucidated the molecular mechanisms by which EVs modulate the macrophage and intestinal epithelial barrier.

RESULTS

Escherichia coli was enriched in weaned diarrheic piglets, while Lactobacillus johnsonii (L. john) showed a negative correlation with Escherichia coli. The transmission of diarrheic illness symptoms was achieved by transferring fecal microbiota, but not metabolites, from diarrheic pigs to germ-free (GF) mice. L. john's intervention prevented the transmission of disease phenotypes from diarrheic piglets to GF mice. L. john also reduces the gut inflammation induced by ETEC K88. The EVs secreted by L. john demonstrated enhanced efficacy in mitigating the adverse impacts induced by ETEC K88 through the modulation of macrophage phenotype. In vitro experiments have revealed that EVs activate M2 macrophages in a manner that shuts down ERK, thereby inhibiting NLRP3 activation in intestinal epithelial cells.

CONCLUSION

Our results reveal that intestinal microbiota drives the onset of diarrheic disease and that probiotic-derived EVs ameliorate diarrheic disease symptoms by modulating macrophage phenotypes. These findings can enhance the advancement of innovative therapeutic approaches for diarrheic conditions based on probiotic-derived EVs.

Associations of gut microbiome richness and diversity with objective and subjective sleep measures in a population sample

STUDY OBJECTIVES

Alterations in gut microbiota composition have been associated with several conditions, and there is emerging evidence that sleep quantity and quality are associated with the composition of the gut microbiome. Therefore, this study aimed to assess the associations between several measures of sleep and the gut microbiome in a large, population-based sample.

METHODS

Data were collected from participants in the Survey of the Health of Wisconsin from 2016 to 2017 (N = 720). Alpha diversity was estimated using Chao1 richness, Shannon's diversity, and Inverse Simpson's diversity. Beta diversity was estimated using Bray-Curtis dissimilarity. Models for each of the alpha-diversity outcomes were calculated using linear mixed effects models. Permutational multivariate analysis of variance tests were performed to test whether gut microbiome composition differed by sleep measures. Negative binomial models were used to assess whether sleep measures were associated with individual taxa relative abundance.

RESULTS

Participants were a mean (SD) age of 55 (16) years and 58% were female. The sample was 83% non-Hispanic white, 10.6% non-Hispanic black, and 3.5% Hispanic. Greater actigraphy-measured night-to-night sleep duration variability, wake-after-sleep onset, lower sleep efficiency, and worse self-reported sleep quality were associated with lower microbiome richness and diversity. Sleep variables were associated with beta-diversity, including actigraphy-measured night-to-night sleep duration variability, sleep latency and efficiency, and self-reported sleep quality, sleep apnea, and napping. Relative abundance of several taxa was associated with night-to-night sleep duration variability, average sleep latency and sleep efficiency, and sleep quality.

CONCLUSIONS

This study suggests that sleep may be associated with the composition of the gut microbiome. These results contribute to the body of evidence that modifiable health habits can influence the human gut microbiome.

An engineered bacterial symbiont allows noninvasive biosensing of the honey bee gut environment

The honey bee is a powerful model system to probe host-gut microbiota interactions, and an important pollinator species for natural ecosystems and for agriculture. While bacterial biosensors can provide critical insight into the complex interplay occurring between a host and its associated microbiota, the lack of methods to noninvasively sample the gut content, and the limited genetic tools to engineer symbionts, have so far hindered their development in honey bees. Here, we built a versatile molecular tool kit to genetically modify symbionts and reported for the first time in the honey bee a technique to sample their feces. We reprogrammed the native bee gut bacterium Snodgrassella alvi as a biosensor for IPTG, with engineered cells that stably colonize the gut of honey bees and report exposure to the molecules in a dose-dependent manner through the expression of a fluorescent protein. We showed that fluorescence readout can be measured in the gut tissues or noninvasively in the feces. These tools and techniques will enable rapid building of engineered bacteria to answer fundamental questions in host-gut microbiota research.

Fecal microbiota characterization of an Italian local horse breed

The Bardigiano horse is a traditional native Italian breed with a rich history and peculiar characteristics. Local breeds are proven to have unique genetic traits developed over generations to adapt to defined geographical regions and/or conditions. The specific microbial communities that coexist within these animals are unraveled by studying their microbiota, which permits a further step in the characterization of local heritage. This work aimed to characterize Bardigiano horse fecal microbiota composition. The data obtained were then compared with published data of a mix of athlete breeds to evaluate potential differences among local and specialized breeds. The study involved 11 Bardigiano mares between 3 and 4 years of age, from which stool was sampled for the study. Samples were processed for 16S rRNA sequencing. Data obtained were analyzed and plotted using R, RStudio, and FastTree software. The samples analyzed were similar to what literature has reported on horses of other breeds and attitudes at higher taxonomic levels (from phylum to genera). While at lower taxonomic levels, the difference was more marked highlighting specific families found in the Bardigiano breed only. Weight, province of origin, and breeding sites significantly affected microbiota composition (p-value ≤0.02, p-value ≤0.04, and p-value ≤0.05, respectively). The comparison with athlete breed showed a significant difference confirming that animal and environmental factors are crucial in determining fecal microbiota composition (p-value <0.001). Understanding the microbiota composition in local breeds like the Bardigiano horse is crucial for preserving biodiversity, managing animal health, and promoting sustainable farming practices.

Longitudinal Profiling of Fasting Plasma Metabolome in Response to Weight-Loss Interventions in Patients with Morbid Obesity

It is well recognized that patients with severe obesity exhibit remarkable heterogeneity in response to different types of weight-loss interventions. Those who undergo Roux-en-Y gastric bypass (RYGB) usually exhibit more favorable glycemic outcomes than those who receive adjustable gastric banding (BAND) or intensive medical intervention (IMI). The molecular mechanisms behind these observations, however, remain largely unknown. To identify the plasma metabolites associated with differential glycemic outcomes induced by weight-loss intervention, we studied 75 patients with severe obesity (25 each in RYGB, BAND, or IMI). Using untargeted metabolomics, we repeatedly measured 364 metabolites in plasma samples at baseline and 1-year after intervention. Linear regression was used to examine whether baseline metabolites or changes in metabolites are associated with differential glycemic outcomes in response to different types of weight-loss intervention, adjusting for sex, baseline age, and BMI as well as weight loss. Network analyses were performed to identify differential metabolic pathways involved in the observed associations. After correction for multiple testing (q < 0.05), 33 (RYGB vs. IMI) and 28 (RYGB vs. BAND) baseline metabolites were associated with changes in fasting plasma glucose (FPG) or glycated hemoglobin (HbA1c). Longitudinal changes in 38 (RYGB vs. IMI) and 38 metabolites (RYGB vs. BAND) were significantly associated with changes in FPG or HbA1c. The identified metabolites are enriched in pathways involved in the biosynthesis of aminoacyl-tRNA and branched-chain amino acids. Weight-loss intervention evokes extensive changes in plasma metabolites, and the altered metabolome may underlie the differential glycemic outcomes in response to different types of weight-loss intervention, independent of weight loss itself.

Intestinal metabolites predict treatment resistance of patients with depression and anxiety

BACKGROUND

The impact of the gut microbiota on neuropsychiatric disorders has gained much attention in recent years; however, comprehensive data on the relationship between the gut microbiome and its metabolites and resistance to treatment for depression and anxiety is lacking. Here, we investigated intestinal metabolites in patients with depression and anxiety disorders, and their possible roles in treatment resistance.

RESULTS

We analyzed fecal metabolites and microbiomes in 34 participants with depression and anxiety disorders. Fecal samples were obtained three times for each participant during the treatment. Propensity score matching led us to analyze data from nine treatment responders and nine non-responders, and the results were validated in the residual sample sets. Using elastic net regression analysis, we identified several metabolites, including N-ε-acetyllysine; baseline levels of the former were low in responders (AUC = 0.86; 95% confidence interval, 0.69-1). In addition, fecal levels of N-ε-acetyllysine were negatively associated with the abundance of Odoribacter. N-ε-acetyllysine levels increased as symptoms improved with treatment.

CONCLUSION

Fecal N-ε-acetyllysine levels before treatment may be a predictive biomarker of treatment-refractory depression and anxiety. Odoribacter may play a role in the homeostasis of intestinal L-lysine levels. More attention should be paid to the importance of L-lysine metabolism in those with depression and anxiety.

Strategy for Comprehensive Detection and Annotation of Gut Microbiota-Related Metabolites Based on Liquid Chromatography-High-Resolution Mass Spectrometry

Gut microbiota, widely populating the mammalian gastrointestinal tract, plays an important role in regulating diverse pathophysiological processes by producing bioactive molecules. Extensive detection of these molecules contributes to probing microbiota function but is limited by insufficient identification of existing analytical methods. In this study, a systematic strategy was proposed to detect and annotate gut microbiota-related metabolites on a large scale. A pentafluorophenyl (PFP) column-based liquid chromatography-high-resolution mass spectrometry (LC-HRMS) method was first developed for high-coverage analysis of gut microbiota-related metabolites, which was verified to be stable and robust with a wide linearity range, high sensitivity, satisfactory recovery, and repeatability. Then, an informative database integrating 968 knowledge-based microbiota-related metabolites and 282 sample-sourced ones defined by germ-free (GF)/antibiotic-treated (ABX) models was constructed and subsequently used for targeted extraction and annotation in biological samples. Using pooled feces, plasma, and urine of mice for demonstration application, 672 microbiota-related metabolites were annotated, including 21% neglected by routine nontargeted peak detection. This strategy serves as a useful tool for the comprehensive capture of the intestinal flora metabolome, contributing to our deeper understanding of microbe-host interactions.

Unraveling the potential of segment scan mass spectral acquisition for chemical isotope labeling LC-MS-based metabolome analysis: Performance assessment across different types of biological samples

BACKGROUND

Chemical isotope labeling (CIL) LC-MS is a powerful tool for metabolome analysis with high metabolomic coverage and quantification accuracy. In CIL LC-MS, the overall metabolite detection efficiency using Orbitrap MS can be further improved by employing a segment scan method where the full m/z range is divided into multiple segments for spectral acquisition with a significant increase in the in-spectrum dynamic range. Considering the metabolic complexity in different types of biological samples (e.g., feces, urine, serum/plasma, cell/tissue extracts, saliva, etc.), we report the development and evaluation of the segment scan method for metabolome analysis of different sample types.

RESULTS

It was found that sample complexity significantly influenced the performance of the segment scan method. In metabolically complex samples such as feces and urine, the method yielded a substantial increase (up to 94 %) in detected peak pairs or metabolites, compared to conventional full scan. Conversely, less complex samples like saliva exhibited more modest gains (approximately 25 %). Based on the observations, a 120-m/z segment scan method was determined as a routine approach for CIL LC-Orbitrap-MS-based metabolomics with good compatibility with different types of biological samples. For this method, a further investigation on relative quantification accuracy was done. The peak area ratios of 12C-/13-labeled metabolites were slightly reduced with 72%-84 % of peak pairs falling within the ±25 % range of the anticipated peak ratio of 1.0 among different samples, as opposed to 81%-90 % in the full scan, which was attributed to the inclusion of more low-abundance peak pairs within the narrow MS segments. However, the overall peak ratio measurement precision was not significantly affected by the segment scan.

SIGNIFICANCE AND NOVELTY

The segment scan method was found to be useful for CIL LC-Orbitrap-MS-based metabolome analysis of different types of samples with significant improvement in metabolite detectability (25-94 % increase), compared to the conventional full scan method.

Gut microbiota dynamics interacting with gastrointestinal evacuation of Apostichopus japonicus: novel insights into promising strategies for environmental improvement

As an important input of environmental micropollutants into aquaculture environment, feed is now considered to be a critical factor in shaping gastrointestinal evacuation characteristics of animals. We analyzed the gastrointestinal evacuation characteristics and gut bacteria of Apostichopus japonicus within 30 h after feeding in recirculating aquaculture system (RAS) and explored the evacuation mechanism interacting by bacteria. The Gauss model was the most precise gastrointestinal evacuation curve, and 80% of gastrointestinal evacuation time was 27.81 h after feeding. Linear discriminant analysis effect size analysis revealed that gut microbial abundance associated significantly with time (P < 0.05), and 42 biomarkers that could predict gastrointestinal evacuation were totally detected, such as Lutibacter and Vibrio. Biomarkers at 25 h after feeding were related to harmful bacteria. A dynamic response between gastrointestinal content ratio and gut microbial abundance was detected. Taken together, we could discharge sewage about 25 h after feeding and carry out the next round of feeding activities.

Efficacy and mechanism study of Baichanting compound, a combination of Acanthopanax senticosus (Rupr. and Maxim.) Harms, Paeonia lactiflora Pall and Uncaria rhynchophylla (Miq.) Miq. ex Havil, on Parkinson's disease based on metagenomics and metabolomics

ETHNOPHARMACOLOGICAL RELEVANCE

Parkinson's disease (PD) is a rapidly progressing neurological disorder. Currently, Medication for PD has numerous limitations. Baichanting Compound (BCT) is a Chinese herbal prescription, a Combination of Acanthopanax senticosus (Rupr. and Maxim.) Harms, Paeonia lactiflora Pall and Uncaria rhynchophylla (Miq.) Miq. ex Havil, that was developed to treat PD and holds a national patent (ZL, 201110260536.3).

AIM OF THE STUDY

To clarify the therapeutic effect of BCT on PD and explore its possible mechanism based on metabolomics and metagenomics.

MATERIALS AND METHODS

C57BL/6 mice were used as a control group, and α-syn transgenic C57BL/6 mice were randomly assigned to the PD (without treatment) or BCT (with BCT treatment) group. UPLC-MS was performed to detect dopamine levels in brain tissue, while ELISA was used to determine inflammatory factors such as IL-1β, IL-6, TNF-α, IFN-γ and NO, and oxidative stress indicators such as malondialdehyde, superoxide dismutase and glutathione peroxidase enzyme activity. Fecal metabolomics was used to detect fecal metabolic profiles, screen differential metabolic markers, and predict metabolic pathways by KEGG enrichment analysis. Metagenomics was used to determine the intestinal microbial composition, and KO enrichment analysis was performed to predict the potential function of different gut microbiota. Finally, Spearman correlation analysis was used to find the possible relationships among intestinal flora, metabolic markers, inflammatory factors, oxidative stress and dopamine levels.

RESULTS

BCT increased the superoxide dismutase activity of α-Syn transgenic C57BL/6 mice (P < 0.01), decreased the levels of TNF-α, IFN-γ, IL-1β, IL-6, NO and malondialdehyde (P < 0.01, 0.05), and increased the release of dopamine (P < 0.01). Metabolomics results show that BCT could regulate Acetatifactor, Marvinbryantia, Faecalitalea, Anaeromassilibacillus, Anaerobium, Pseudobutyrivibrio and Lachnotalea and Acetatifactor_muris, Marvinbryantia_formatexigens, Lachnotalea_sp_AF33_28, Faecalitalea_sp_Marseille_P3755 and Anaerobium_acetethylicum, Gemmiger_sp_An120 abundance to restore intestinal flora function, and reverse fecal metabolism trend, restoring the content of α-D-glucose, cytidine, L-glutamate, L-glutamine, N-acetyl-L-glutamate, raffinose and uracil. In addition, it regulates arginine biosynthesis, D-glutamine and D-glutamate, pyrimidine, galactose and alanine, aspartate and glutamate metabolic pathways.

CONCLUSION

BCT may regulate the composition of the gut microbiota to reverse fecal metabolism in PD mice to protect the substantia nigra and striatum from oxidative stress and inflammatory factors and ultimately play an anti-PD role.

Microbiota and Metabolite Profiles in the Feces of Juvenile Sika Deer (Cervus nippon) from Birth to Weaning

The gut microbiota establishment in young ruminants has a profound impact on their adult production performance. However, the critical phase for the succession of the gut microbial composition and metabolic profiles of juvenile sika deer still needs to be further investigated. Here, we analyzed the fecal microbiota and metabolites of juvenile sika deer during the birth (D1), transition (D42), and rumination (D70) periods based on 16S rRNA sequencing and gas chromatography-time-of-flight mass spectrometry (GC-TOF-MS). The results showed that the fecal bacteria and metabolites composition were significantly different in D1 compared to D42 and D70, and the number of OTUs and the Shannon index were significantly higher in D70 than in D1 (p < 0.05). The relative abundances of Lactobacillus, Lactococcus, and Lachnoclostridium showed a significant increase in D1 compared to D42 and D70, whereas the relative abundances of Ruminococcaceae UCG-005, Ruminococcaceae UCG-010, Ruminococcaceae UCG-014, Christensenellaceae R-7, and Eubacterium coprostanoligenes group were significantly decreased in D1 compared to D42 and D70 (p < 0.05). The amounts of serine, phenylalanine, aspartic acid, ornithine, citrulline, creatine, isoleucine, galactose, and ribose in the feces were significantly higher in D1 compared to D42 and D70. In contrast, the concentrations of cortexolone, resveratrol, piceatannol, fumaric acid, alpha-ketoglutarate, glycerol, uracil-5-carboxylic acid, and maleic acid were significantly decreased in D1. The enrichment analysis showed that amino acid metabolism and carbohydrate metabolism were significantly changed in D1 compared to D42 and D70. The glycine, serine and threonine metabolism; alanine, aspartate and glutamate metabolism; arginine biosynthesis; glyoxylate and dicarboxylate metabolism; citrate cycle; and pyruvate metabolism were significantly enriched across the three periods (p < 0.05). In conclusion, our results suggested that the birth-transition period is a critical phase for the gut bacterial community and metabolic function shift in juvenile sika deer.

The Role of the FODMAP Diet in IBS

The low FODMAP (fermentable oligosaccharide, disaccharide, monosaccharide, and polyol) diet is a beneficial therapeutic approach for patients with irritable bowel syndrome (IBS). However, how the low FODMAP diet works is still not completely understood. These mechanisms encompass not only traditionally known factors such as luminal distension induced by gas and water but also recent evidence on the role of FOMAPs in the modulation of visceral hypersensitivity, increases in intestinal permeability, the induction of microbiota changes, and the production of short-chain fatty acids (SCFAs), as well as metabolomics and alterations in motility. Although most of the supporting evidence is of low quality, recent trials have confirmed its effectiveness, even though the majority of the evidence pertains only to the restriction phase and its effectiveness in relieving abdominal bloating and pain. This review examines potential pathophysiological mechanisms and provides an overview of the existing evidence on the effectiveness of the low FODMAP diet across various IBS subtypes. Key considerations for its use include the challenges and disadvantages associated with its practical implementation, including the need for professional guidance, variations in individual responses, concerns related to microbiota, nutritional deficiencies, the development of constipation, the necessity of excluding an eating disorder before commencing the diet, and the scarcity of long-term data. Despite its recognized efficacy in symptom management, acknowledging these limitations becomes imperative for a nuanced comprehension of the role of a low FODMAP diet in managing IBS. By investigating its potential mechanisms and evidence across IBS subtypes and addressing emerging modulations alongside limitations, this review aims to serve as a valuable resource for healthcare practitioners, researchers, and patients navigating the intricate landscape of IBS.

Intestinal microbiota and metabolome perturbations in ischemic and idiopathic dilated cardiomyopathy

BACKGROUND

Various clinical similarities are present in ischemic (ICM) and idiopathic dilated cardiomyopathy (IDCM), leading to ambiguity on some occasions. Previous studies have reported that intestinal microbiota appeared dysbiosis in ICM, whether implicating in the IDCM remains unclear. The aim of this study was to assess the alterations in intestinal microbiota and fecal metabolites in ICM and IDCM.

METHODS

ICM (n = 20), IDCM (n = 22), and healthy controls (HC, n = 20) were enrolled in this study. Stool samples were collected for 16S rRNA gene sequencing and gas chromatography-mass spectrometry (GC-MS) analysis.

RESULTS

Both ICM and IDCM exhibited reduced alpha diversity and altered microbial community structure compared to HC. At the genus level, nine taxa including Blautia, [Ruminococcus]_torques_group, Christensenellaceae_R-7_group, UCG-002, Corynebacterium, Oceanobacillus, Gracilibacillus, Klebsiella and Citrobacter was specific to ICM, whereas one taxa Alistipes uniquely altered in IDCM. Likewise, these changes were accompanied by significant metabolic differences. Further differential analysis displayed that 18 and 14 specific metabolites uniquely changed in ICM and IDCM, respectively. The heatmap was generated to display the association between genera and metabolites. Receiver operating characteristic curve (ROC) analysis confirmed the predictive value of the distinct microbial-metabolite features in disease status. The results showed that microbial (area under curve, AUC = 0.95) and metabolic signatures (AUC = 0.84) were effective in discriminating ICM from HC. Based on the specific microbial and metabolic features, the patients with IDCM could be separated from HC with an AUC of 0.80 and 0.87, respectively. Furthermore, the gut microbial genus (AUC = 0.88) and metabolite model (AUC = 0.89) were comparable in predicting IDCM from ICM. Especially, the combination of fecal microbial-metabolic features improved the ability to differentiate IDCM from ICM with an AUC of 0.96.

CONCLUSION

Our findings highlighted the alterations of gut microbiota and metabolites in different types of cardiomyopathies, providing insights into the pathophysiological mechanisms of myocardial diseases. Moreover, multi-omics analysis of fecal samples holds promise as a non-invasive tool for distinguishing disease status.

Mechanisms of hepatic steatosis in chickens: integrated analysis of the host genome, molecular phenomics and gut microbiome

Hepatic steatosis is the initial manifestation of abnormal liver functions and often leads to liver diseases such as nonalcoholic fatty liver disease in humans and fatty liver syndrome in animals. In this study, we conducted a comprehensive analysis of a large chicken population consisting of 705 adult hens by combining host genome resequencing; liver transcriptome, proteome, and metabolome analysis; and microbial 16S ribosomal RNA gene sequencing of each gut segment. The results showed the heritability (h2 = 0.25) and duodenal microbiability (m2 = 0.26) of hepatic steatosis were relatively high, indicating a large effect of host genetics and duodenal microbiota on chicken hepatic steatosis. Individuals with hepatic steatosis had low microbiota diversity and a decreased genetic potential to process triglyceride output from hepatocytes, fatty acid β-oxidation activity, and resistance to fatty acid peroxidation. Furthermore, we revealed a molecular network linking host genomic variants (GGA6: 5.59-5.69 Mb), hepatic gene/protein expression (PEMT, phosphatidyl-ethanolamine N-methyltransferase), metabolite abundances (folate, S-adenosylmethionine, homocysteine, phosphatidyl-ethanolamine, and phosphatidylcholine), and duodenal microbes (genus Lactobacillus) to hepatic steatosis, which could provide new insights into the regulatory mechanism of fatty liver development.

Diagnosis of Esophageal Squamous Cell Carcinoma by High-Performance Serum Metabolic Fingerprints: A Retrospective Study

Esophageal squamous cell carcinoma (ESCC) is a highly prevalent and aggressive malignancy, and timely diagnosis of ESCC contributes to an increased cancer survival rate. However, current detection methods for ESCC mainly rely on endoscopic examination, limited by a relatively low participation rate. Herein, ferric-particle-enhanced laser desorption/ionization mass spectrometry (FPELDI MS) is utilized to record the serum metabolic fingerprints (SMFs) from a retrospective cohort (523 non-ESCC participants and 462 ESCC patients) to build diagnostic models toward ESCC. The PFELDI MS achieved high speed (≈30 s per sample), desirable reproducibility (coefficients of variation < 15%), and high throughput (985 samples with ≈124 200 data points for each spectrum). Desirable diagnostic performance with area-under-the-curves (AUCs) of 0.925-0.966 is obtained through machine learning of SMFs. Further, a metabolic biomarker panel is constructed, exhibiting superior diagnostic sensitivity (72.2-79.4%, p < 0.05) as compared with clinical protein biomarker tests (4.3-22.9%). Notably, the biomarker panel afforded an AUC of 0.844 (95% confidence interval [CI]: 0.806-0.880) toward early ESCC diagnosis. This work highlighted the potential of metabolic analysis for accurate screening and early detection of ESCC and offered insights into the metabolic characterization of diseases including but not limited to ESCC.

Integrated analysis of gut metabolome, microbiome, and brain function reveal the role of gut-brain axis in longevity

The role of microbiota-gut-brain axis in modulating longevity remains undetermined. Here, we performed a multiomics analysis of gut metagenomics, gut metabolomics, and brain functional near-infrared spectroscopy (fNIRS) in a cohort of 164 participants, including 83 nonagenarians (NAs) and 81 non-nonagenarians (NNAs) matched with their spouses and offspring. We found that 438 metabolites were significantly different between the two groups; among them, neuroactive compounds and anti-inflammatory substances were enriched in NAs. In addition, increased levels of neuroactive metabolites in NAs were significantly associated with NA-enriched species that had three corresponding biosynthetic potentials: Enterocloster asparagiformis, Hungatella hathewayi and Oxalobacter formigenes. Further analysis showed that the altered gut microbes and metabolites were linked to the enhanced brain connectivity in NAs, including the left dorsolateral prefrontal cortex (DLPFC)-left premotor cortex (PMC), left DLPFC-right primary motor area (M1), and right inferior frontal gyrus (IFG)-right M1. Finally, we found that neuroactive metabolites, altered microbe and enhanced brain connectivity contributed to the cognitive preservation in NAs. Our findings provide a comprehensive understanding of the microbiota-gut-brain axis in a long-lived population and insights into the establishment of a microbiome and metabolite homeostasis that can benefit human longevity and cognition by enhancing functional brain connectivity.

Spatio-temporal dynamics of the human small intestinal microbiome and its response to a synbiotic

Although fecal microbiota composition is considered to preserve relevant and representative information for distal colonic content, it is evident that it does not represent microbial communities inhabiting the small intestine. Nevertheless, studies investigating the human small intestinal microbiome and its response to dietary intervention are still scarce. The current study investigated the spatio-temporal dynamics of the small intestinal microbiome within a day and over 20 days, as well as its responses to a 14-day synbiotic or placebo control supplementation in 20 healthy subjects. Microbial composition and metabolome of luminal content of duodenum, jejunum, proximal ileum and feces differed significantly from each other. Additionally, differences in microbiota composition along the small intestine were most pronounced in the morning after overnight fasting, whereas differences in composition were not always measurable around noon or in the afternoon. Although overall small intestinal microbiota composition did not change significantly within 1 day and during 20 days, remarkable, individual-specific temporal dynamics were observed in individual subjects. In response to the synbiotic supplementation, only the microbial diversity in jejunum changed significantly. Increased metabolic activity of probiotic strains during intestinal passage, as assessed by metatranscriptome analysis, was not observed. Nevertheless, synbiotic supplementation led to a short-term spike in the relative abundance of genera included in the product in the small intestine approximately 2 hours post-ingestion. Collectively, small intestinal microbiota are highly dynamic. Ingested probiotic bacteria could lead to a transient spike in the relative abundance of corresponding genera and ASVs, suggesting their passage through the entire gastrointestinal tract. This study was registered to http://www.clinicaltrials.gov, NCT02018900.

An integrated analysis of the fecal metabolome and metagenome reveals the distinct effects of differentially charged nanoplastics on the gut microbiota-associated metabolites in mice

Whether nanoplastics with differential charges cause intestinal impairment via distinct mechanisms remains unclear. We investigated the relationship between fecal metabolites and the gut microbiome, and potential biomarkers thereof, in mice following exposure to differentially charged polystyrene nanoplastics (PS-NPs). Metagenomic analysis revealed that exposure to differentially charged PS-NPs resulted in alterations in the abundances of Bilophila_wadsworthia, Helicobacter apodemus, and Helicobacter typhlonius. A total of 237 fecal metabolites were significantly altered in mice that exhibited intestinal impairment, and these included 10 gut microbiota-related fecal metabolites that accurately discriminated impaired intestinal samples from the control. Additionally, the specific gut microbiome-related fecal metabolite-based model approach for the prediction of intestinal impairment in mice had an area under the curve (AUC) of 1.0 in the PS (without charge) group, an AUC of 0.94 in the PS-NH2 (positive charge) group, and an AUC of 0.86 in the PS-COOH (negative charge) group. Thus, the model showed promising evaluable accuracy for the prediction of intestinal impairment induced by nanoplastics in a charge-specific manner. Our study demonstrates that the fecal metabolome of mice with intestinal impairment following exposure to differentially charged nanoplastics is associated with changes in the gut microbiome. The identified biomarkers have potential application for the detection of intestinal impairment after exposure to negative, positive, or noncharged nanomaterials.

The potential role of early life feeding patterns in shaping the infant fecal metabolome: implications for neurodevelopmental outcomes

Infant fecal metabolomics can provide valuable insights into the associations of nutrition, dietary patterns, and health outcomes in early life. Breastmilk is typically classified as the best source of nutrition for nearly all infants. However, exclusive breastfeeding may not always be possible for all infants. This study aimed to characterize associations between levels of mixed breastfeeding and formula feeding, along with solid food consumption and the infant fecal metabolome at 1- and 6-months of age. As a secondary aim, we examined how feeding-associated metabolites may be associated with early life neurodevelopmental outcomes. Fecal samples were collected at 1- and 6-months, and metabolic features were assessed via untargeted liquid chromatography/high-resolution mass spectrometry. Feeding groups were defined at 1-month as 1) exclusively breastfed, 2) breastfed >50% of feedings, or 3) formula fed ≥50% of feedings. Six-month groups were defined as majority breastmilk (>50%) or majority formula fed (≥50%) complemented by solid foods. Neurodevelopmental outcomes were assessed using the Bayley Scales of Infant Development at 2 years. Changes in the infant fecal metabolome were associated with feeding patterns at 1- and 6-months. Feeding patterns were associated with the intensities of a total of 57 fecal metabolites at 1-month and 25 metabolites at 6-months, which were either associated with increased breastmilk or increased formula feeding. Most breastmilk-associated metabolites, which are involved in lipid metabolism and cellular processes like cell signaling, were associated with higher neurodevelopmental scores, while formula-associated metabolites were associated with lower neurodevelopmental scores. These findings offer preliminary evidence that feeding patterns are associated with altered infant fecal metabolomes, which may be associated with cognitive development later in life.