A meta-analysis study of the robustness and universality of gut microbiome-metabolome associations

A generic approach to infer community-level fitness of microbial genes

The gene content in a metagenomic pool defines the function potential of a microbial community. Natural selection, operating on the level of genomes or genes, shapes the evolution of community functions by enriching some genes while depriving the others. Despite the importance of microbiomes in the environment and health, a general metric to evaluate the community-wide fitness of microbial genes remains lacking. In this work, we adapt the classic neutral model of species and use it to predict how the abundances of different genes will be shaped by selection, regardless of at which level the selection acts. We establish a simple metric that quantitatively infers the average survival capability of each gene in a microbiome. We then experimentally validate the predictions using synthetic communities of barcoded Escherichia coli strains undergoing neutral assembly and competition. We further show that this approach can be applied to publicly available metagenomic datasets to gain insights into the environment-function interplay of natural microbiomes.

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.

Crosstalk between gut microbiome and neuroinflammation in pathogenesis of HIV-associated neurocognitive disorder

HIV-associated neurocognitive disorder (HAND) has become a chronic neurodegenerative disease affecting the quality of life in people living with HIV (PLWH). Despite an established association between HAND and neuroinflammation induced by HIV proteins (gp120, Tat, Rev., Nef, and Vpr), the pathogenesis of HAND remains to be fully elucidated. Accumulating evidence demonstrated that the gut microbiome is emerging as a critical regulator of various neurodegenerative diseases (e.g., Parkinson's disease, Alzheimer's disease), suggesting that the crosstalk between the gut microbiome and neuroinflammation may contribute to the development of these diseases, for example, gut dysbiosis and microbiota-derived metabolites can trigger inflammation in the brain. However, the potential role of the gut microbiome in the pathogenesis of HAND remains largely unexplored. In this review, we aim to discuss and elucidate the HAND pathogenesis correlated with gut microbiome and neuroinflammation, and intend to explore the probable intervention strategies for HAND.

A comprehensive overview of microbiome data in the light of machine learning applications: categorization, accessibility, and future directions

Metagenomics, Metabolomics, and Metaproteomics have significantly advanced our knowledge of microbial communities by providing culture-independent insights into their composition and functional potential. However, a critical challenge in this field is the lack of standard and comprehensive metadata associated with raw data, hindering the ability to perform robust data stratifications and consider confounding factors. In this comprehensive review, we categorize publicly available microbiome data into five types: shotgun sequencing, amplicon sequencing, metatranscriptomic, metabolomic, and metaproteomic data. We explore the importance of metadata for data reuse and address the challenges in collecting standardized metadata. We also, assess the limitations in metadata collection of existing public repositories collecting metagenomic data. This review emphasizes the vital role of metadata in interpreting and comparing datasets and highlights the need for standardized metadata protocols to fully leverage metagenomic data's potential. Furthermore, we explore future directions of implementation of Machine Learning (ML) in metadata retrieval, offering promising avenues for a deeper understanding of microbial communities and their ecological roles. Leveraging these tools will enhance our insights into microbial functional capabilities and ecological dynamics in diverse ecosystems. Finally, we emphasize the crucial metadata role in ML models development.

Gut microbiome-metabolome interactions predict host condition

BACKGROUND

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

RESULTS

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

CONCLUSION

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

Fndc5/irisin deficiency leads to dysbiosis of gut microbiota contributing to the depressive-like behaviors in mice

BACKGROUND

Depression is one of the most common mental diseases and the leading cause of disability worldwide. A dysfunctional gut microbiota-brain axis is one of the main pathological bases of depression. Irisin, an exercise-related myokine, reduces depression-like behaviors and may guide the relief of depressive symptoms by exercise. However, its underlying mechanism remains unclear.

METHODS

Fibronectin type III domain containing 5 (Fndc5)/Irisin was knocked out in male wide-type C57BL/6N mice using CRISPR-cas9. The depression and anxiety symptoms were examined in irisin knockout and control mice with or without chronic unpredictable mild stress by sucrose preference test (SPT), forced swimming test (FST), and tail suspension test (TST). Fecal microbiota was assessed by 16S rRNA sequencing and microbiota-related metabolites using liquid chromatography with tandem mass spectrometry. Differential metabolites were analyzed with the Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses.

RESULTS

The knockout mice showed anxiety- and depression-like behaviors and altered diversity and richness of gut microbiota. At the phylum level, these mice had decreased Firmicutes and increased Bacteroidota populations, while at the genus level, they exhibited a low relative abundance of Lactobacillus and Bifidobacterium. Moreover, knocking out of Irisin gene in these mice significantly reduced N-desmethyl-mifepristone (RU 42633) and elevated (-)-stercobilin levels. The KEGG results showed that the microbiota-related metabolites affected by irisin mainly clustered into arginine and proline metabolism and affected the mechanistic target of rapamycin kinase (mTOR) signaling pathway.

CONCLUSION

Our findings show that Fndc5/irisin deficiency causes depression in mice by inducing dysbiosis of gut microbiota and changes in microbiota-related metabolites.

Microbiome and metabolome features in inflammatory bowel disease via multi-omics integration analyses across cohorts

The perturbations of the gut microbiota and metabolites are closely associated with the progression of inflammatory bowel disease (IBD). However, inconsistent findings across studies impede a comprehensive understanding of their roles in IBD and their potential as reliable diagnostic biomarkers. To address this challenge, here we comprehensively analyze 9 metagenomic and 4 metabolomics cohorts of IBD from different populations. Through cross-cohort integrative analysis (CCIA), we identify a consistent characteristic of commensal gut microbiota. Especially, three bacteria, namely Asaccharobacter celatus, Gemmiger formicilis, and Erysipelatoclostridium ramosum, which are rarely reported in IBD. Metagenomic functional analysis reveals that essential gene of Two-component system pathway, linked to fecal calprotectin, are implicated in IBD. Metabolomics analysis shows 36 identified metabolites with significant differences, while the roles of these metabolites in IBD are still unknown. To further elucidate the relationship between gut microbiota and metabolites, we construct multi-omics biological correlation (MOBC) maps, which highlights gut microbial biotransformation deficiencies and significant alterations in aminoacyl-tRNA synthetases. Finally, we identify multi-omics biomarkers for IBD diagnosis, validated across multiple global cohorts (AUROC values ranging from 0.92 to 0.98). Our results offer valuable insights and a significant resource for developing mechanistic hypotheses on host-microbiome interactions in IBD.

Impact of feeding dried distillers' grains with solubles diet on microbiome and metabolome of ruminal and cecal contents in Guanling yellow cattle

Dried distillers' grains with solubles (DDGS) are rich in nutrients, and partially alternative feeding of DDGS effectively reduces cost of feed and improves animals' growth. We used 16S rDNA gene sequencing and LC/MS-based metabolomics to explore the effect of feeding cattle with a basal diet (BD) and a Jiang-flavor DDGS diet (replaces 25% concentrate of the diet) on microbiome and metabolome of ruminal and cecal contents in Guanling yellow cattle. The results showed that the ruminal and cecal contents shared the same dominance of Bacteroidetes, Firmicutes and Proteobacteria in two groups. The ruminal dominant genera were Prevotella_1, Rikenellaceae_RC9_gut_group, and Ruminococcaceae_UCG-010; and the cecal dominant genera were Ruminococcaceae_UCG-005, Ruminococcaceae_UCG-010, and Rikenellaceae_RC9_gut_group. Linear discriminant analysis effect size analysis (LDA > 2, P < 0.05) revealed the significantly differential bacteria enriched in the DDGS group, including Ruminococcaceae_UCG_012, Prevotellaceae_UCG_004 and Anaerococcus in the ruminal contents, which was associated with degradation of plant polysaccharides. Besides, Anaerosporobacter, Anaerovibrio, and Caproiciproducens in the cecal contents were involved in fatty acid metabolism. Compared with the BD group, 20 significantly different metabolites obtained in the ruminal contents of DDGS group were down-regulated (P < 0.05), and based on them, 4 significantly different metabolic pathways (P < 0.05) were enriched including "Linoleic acid metabolism," "Biosynthesis of unsaturated fatty acids," "Taste transduction," and "Carbohydrate digestion and absorption." There were 65 significantly different metabolites (47 were upregulated, 18 were downregulated) in the cecal contents of DDGS group when compared with the BD group, and 4 significantly different metabolic pathways (P < 0.05) were enriched including "Longevity regulating pathway," "Bile secretion," "Choline metabolism in cancer," and "HIF-1 signaling pathway." Spearman analysis revealed close negative relationships between the top 20 significantly differential metabolites and Anaerococcus in the ruminal contents. Bacteria with high relevance to cecal differential metabolites were Erysipelotrichaceae_UCG-003, Dielma, and Solobacterium that affect specific metabolic pathways in cattle. Collectively, our results suggest that feeding cattle with a DDGS diet improves the microbial structure and the metabolic patterns of lipids and carbohydrates, thus contributing to the utilization efficiency of nutrients and physical health to some extent. Our findings will provide scientific reference for the utilization of DDGS as feed in cattle industry.

Faecal metabolome and its determinants in inflammatory bowel disease

OBJECTIVE

Inflammatory bowel disease (IBD) is a multifactorial immune-mediated inflammatory disease of the intestine, comprising Crohn's disease and ulcerative colitis. By characterising metabolites in faeces, combined with faecal metagenomics, host genetics and clinical characteristics, we aimed to unravel metabolic alterations in IBD.

DESIGN

We measured 1684 different faecal metabolites and 8 short-chain and branched-chain fatty acids in stool samples of 424 patients with IBD and 255 non-IBD controls. Regression analyses were used to compare concentrations of metabolites between cases and controls and determine the relationship between metabolites and each participant's lifestyle, clinical characteristics and gut microbiota composition. Moreover, genome-wide association analysis was conducted on faecal metabolite levels.

RESULTS

We identified over 300 molecules that were differentially abundant in the faeces of patients with IBD. The ratio between a sphingolipid and L-urobilin could discriminate between IBD and non-IBD samples (AUC=0.85). We found changes in the bile acid pool in patients with dysbiotic microbial communities and a strong association between faecal metabolome and gut microbiota. For example, the abundance of Ruminococcus gnavus was positively associated with tryptamine levels. In addition, we found 158 associations between metabolites and dietary patterns, and polymorphisms near NAT2 strongly associated with coffee metabolism.

CONCLUSION

In this large-scale analysis, we identified alterations in the metabolome of patients with IBD that are independent of commonly overlooked confounders such as diet and surgical history. Considering the influence of the microbiome on faecal metabolites, our results pave the way for future interventions targeting intestinal inflammation.

Meta-analysis reveals different functional characteristics of human gut Bifidobacteria associated with habitual diet

Dietary habits contribute to the composition and function of the gut microbiota. Different dietary structures, including vegan, vegetarian, and omnivorous diets, affect intestinal Bifidobacteria; however, the relationship between Bifidobacterial function and host metabolism in subjects with different dietary patterns is unclear. Here, we analyzed five metagenomics studies and six 16S sequencing studies, including 206 vegetarians (VG), 249 omnivores (O), and 270 vegans (V), through an unbiased theme-level meta-analysis framework and discovered that diet significantly affects the composition and functionality of intestinal Bifidobacteria. The relative abundance of Bifidobacterium pseudocatenulatum was significantly higher in V than in O and Bifidobacterium longum, Bifidobacterium adolescentis, and B. pseudocatenulatum differed significantly in carbohydrate transport and metabolism in subjects with different diet types. Diets high in fiber were associated with B. longum with increased capacity for carbohydrate catabolism and genes encoding GH29 and GH43_27 were significantly enriched in V. Bifidobacterium adolescentis and B. pseudocatenulatum, associated with O, had a higher prevalence of the genes related to carbohydrate transport and metabolism, which showed the enrichment of GH26 and GH27 families. The same Bifidobacterium species has different functions in subjects with different diet types, resulting in different physiological significance. The diversification and functionalities of Bifidobacterial species in the gut microbiome can be influenced by the host diet and this aspect should be considered when studying host-microbe associations.

mTOR Signaling Pathway and Gut Microbiota in Various Disorders: Mechanisms and Potential Drugs in Pharmacotherapy

The mammalian or mechanistic target of rapamycin (mTOR) integrates multiple intracellular and extracellular upstream signals involved in the regulation of anabolic and catabolic processes in cells and plays a key regulatory role in cell growth and metabolism. The activation of the mTOR signaling pathway has been reported to be associated with a wide range of human diseases. A growing number of in vivo and in vitro studies have demonstrated that gut microbes and their complex metabolites can regulate host metabolic and immune responses through the mTOR pathway and result in disorders of host physiological functions. In this review, we summarize the regulatory mechanisms of gut microbes and mTOR in different diseases and discuss the crosstalk between gut microbes and their metabolites and mTOR in disorders in the gastrointestinal tract, liver, heart, and other organs. We also discuss the promising application of multiple potential drugs that can adjust the gut microbiota and mTOR signaling pathways. Despite the limited findings between gut microbes and mTOR, elucidating their relationship may provide new clues for the prevention and treatment of various diseases.

Integration of genome-wide association studies (GWAS) and microbiome data highlights the impact of sulfate-reducing bacteria on Alzheimer's disease

BACKGROUND

observational studies have indicated that gut microbiome dysbiosis was associated with Alzheimer's disease (ad). However, the results are largely inconsistent and it remains unknown whether the association is causal in nature.

METHODS

leveraging observational studies and genome-wide association studies (GWAS) on the gut microbiome in ad patients, we pooled the microbiome data (N = 1,109) to screen the microbiota significantly altered in ad patients and then conducted Mendelian randomisation (MR) study to determine the causal associations between altered microbiota (N = 18,340) and ad using two different ad GWAS datasets (N = 63,926 and N = 472,868) using the inverse variance-weighted (IVW) method.

RESULTS

the combined effect sizes from observational studies showed that 8 phyla, 18 classes, 22 orders, 37 families, 78 genera and 109 species significantly changed in ad patients. Using the MR analysis, we found that two classes, one order, one family and one genus were suggestively associated with ad consistently in two different GWAS datasets. Both observational studies and MR analysis simultaneously showed that Desulfovibrionales (order) and Desulfovibrionaceae (family), which were mainly implicated in dissimilatory sulfate reduction, were significantly associated with an elevated risk of ad.

CONCLUSIONS

our findings demonstrated that the abundance of sulfate-reducing bacteria was increased in ad patients, which was causally linked to an increased risk of ad. Further efforts are warranted to clarify the underlying mechanisms, which will provide new insight into the prevention and treatment of ad.

Gut microbiome dysbiosis in Alzheimer's disease and mild cognitive impairment: A systematic review and meta-analysis

BACKGROUND

Alzheimer's disease (AD) is a neurodegenerative disorder that causes gradual memory loss. AD and its prodromal stage of mild cognitive impairment (MCI) are marked by significant gut microbiome perturbations, also known as gut dysbiosis. However, the direction and extent of gut dysbiosis have not been elucidated. Therefore, we performed a meta-analysis and systematic review of 16S gut microbiome studies to gain insights into gut dysbiosis in AD and MCI.

METHODS

We searched MEDLINE, Scopus, EMBASE, EBSCO, and Cochrane for AD gut microbiome studies published between Jan 1, 2010 and Mar 31, 2022. This study has two outcomes: primary and secondary. The primary outcomes explored the changes in α-diversity and relative abundance of microbial taxa, which were analyzed using a variance-weighted random-effects model. The secondary outcomes focused on qualitatively summarized β-diversity ordination and linear discriminant analysis effect sizes. The risk of bias was assessed using a methodology appropriate for the included case-control studies. The geographic cohorts' heterogeneity was examined using subgroup meta-analyses if sufficient studies reported the outcome. The study protocol has been registered with PROSPERO (CRD42022328141).

FINDINGS

Seventeen studies with 679 AD and MCI patients and 632 controls were identified and analyzed. The cohort is 61.9% female with a mean age of 71.3±6.9 years. The meta-analysis shows an overall decrease in species richness in the AD gut microbiome. However, the phylum Bacteroides is consistently higher in US cohorts (standardised mean difference [SMD] 0.75, 95% confidence interval [CI] 0.37 to 1.13, p < 0.01) and lower in Chinese cohorts (SMD -0.79, 95% CI -1.32 to -0.25, p < 0.01). Moreover, the Phascolarctobacterium genus is shown to increase significantly, but only during the MCI stage.

DISCUSSION

Notwithstanding possible confounding from polypharmacy, our findings show the relevance of diet and lifestyle in AD pathophysiology. Our study presents evidence for region-specific changes in abundance of Bacteroides, a major constituent of the microbiome. Moreover, the increase in Phascolarctobacterium and the decrease in Bacteroides in MCI subjects shows that gut microbiome dysbiosis is initiated in the prodromal stage. Therefore, studies of the gut microbiome can facilitate early diagnosis and intervention in Alzheimer's disease and perhaps other neurodegenerative disorders.

Microbiome-Metabolomics Analysis of the Impacts of Cryptosporidium muris Infection in BALB/C Mice

Cryptosporidium is a leading cause of diarrheal disease and mortality in young children worldwide. Cryptosporidium invades small intestinal epithelial cells and forms a unique intracellular niche, a process that may alter gut microbes and their production metabolites. However, the mechanism of interactions between gut microbes, metabolites, and parasites is poorly understood. Here, we first characterized the impacts of Cryptosporidium infection on gut microbiota using a microbiome-to-metabolome association study. BALB/c mice were gavaged with Cryptosporidium muris, and fecal samples were collected at 0, 7, 14, 21, and 28 days postinfection (dpi) to observe changes in the intestinal microbes of the body during parasite infection. The infected group had a significantly increased relative abundance of bacterial taxa, such as Lachnospiraceae and Prevotella (P < 0.05), associated with the biosynthesis of short-chain fatty acids (SCFAs). Metabolites related to the metabolic pathways, steroid hormone biosynthesis, and biosynthesis of unsaturated fatty acids pathway were upregulated at 7 dpi, indicating that related metabolites in the biosynthesis of unsaturated fatty acids may be essential for C. muris reproduction in vivo. The metabolites involved in metabolic pathways, bile secretion, and primary bile acid biosynthesis were upregulated at 14 dpi, and we speculate that these metabolites may be critical to the growth and development of Cryptosporidium oocysts in the host. Correlation analysis revealed that Firmicutes bacteria are significantly associated with α-linolenic acid metabolism pathways (P< 0.05). The gut microbiota changes dynamically, and the metabolites involved in fatty acid and bile acid biosynthesis may play important roles during cryptosporidiosis. Details of the gut microbiota and the metabolome after infection with Cryptosporidium may aid in the discovery of specific diagnostic markers and help us understand the changes in parasite metabolic pathways. IMPORTANCE Cryptosporidiosis is a gastrointestinal disease in humans and animals caused by the protozoan parasite Cryptosporidium. Control and treatment of the disease is challenging due to the lack of sensitive diagnostic tools and effective chemotherapy. The dynamics of gut microbiota and metabolites during Cryptosporidium infection may be the key to finding drugs and targets for parasite infection control. Our results indicate that C. muris infection can disrupt gut microbiota and metabolites, resulting in decreased bacterial abundance at the parasitic site. Unsaturated fatty acid pathway biosynthesis-related metabolites are significantly elevated at the patent period. Interestingly, the metabolite pathway that significantly elevated during peak parasite growth was bile acid, the metabolites of which may be important for the circulation of infection of Cryptosporidium oocysts in the host. The enhancing effects of short-chain fatty acid and bile acid metabolism on the growth and development of Cryptosporidium proposed in this study may provide a theoretical basis for future research on novel drugs and vaccines against this intestinal parasite.

Comparison of fecal and blood metabolome reveals inconsistent associations of the gut microbiota with cardiometabolic diseases

Blood metabolome is commonly used in human studies to explore the associations of gut microbiota-derived metabolites with cardiometabolic diseases. Here, in a cohort of 1007 middle-aged and elderly adults with matched fecal metagenomic (149 species and 214 pathways) and paired fecal and blood targeted metabolomics data (132 metabolites), we find disparate associations with taxonomic composition and microbial pathways when using fecal or blood metabolites. For example, we observe that fecal, but not blood butyric acid significantly associates with both gut microbiota and prevalent type 2 diabetes. These findings are replicated in an independent validation cohort involving 103 adults. Our results suggest that caution should be taken when inferring microbiome-cardiometabolic disease associations from either blood or fecal metabolome data.

Immunometabolism and microbial metabolites at the gut barrier: Lessons for therapeutic intervention in inflammatory bowel disease

The concept of immunometabolism has emerged recently whereby the repolarizing of inflammatory immune cells toward anti-inflammatory profiles by manipulating cellular metabolism represents a new potential therapeutic approach to controlling inflammation. Metabolic pathways in immune cells are tightly regulated to maintain immune homeostasis and appropriate functional specificity. Because effector and regulatory immune cell populations have different metabolic requirements, this allows for cellular selectivity when regulating immune responses based on metabolic pathways. Gut microbes have a major role in modulating immune cell metabolic profiles and functional responses through extensive interactions involving metabolic products and crosstalk between gut microbes, intestinal epithelial cells, and mucosal immune cells. Developing strategies to target metabolic pathways in mucosal immune cells through the modulation of gut microbial metabolism has the potential for new therapeutic approaches for human autoimmune and inflammatory diseases, such as inflammatory bowel disease. This review will give an overview of the relationship between metabolic reprogramming and immune responses, how microbial metabolites influence these interactions, and how these pathways could be harnessed in the treatment of inflammatory bowel disease.

Fecal Metabolites as Biomarkers for Predicting Food Intake by Healthy Adults

BACKGROUND

The fecal metabolome is affected by diet and includes metabolites generated by human and microbial metabolism. Advances in -omics technologies and analytic approaches have allowed researchers to identify metabolites and better utilize large data sets to generate usable information. One promising aspect of these advancements is the ability to determine objective biomarkers of food intake.

OBJECTIVES

We aimed to utilize a multivariate, machine learning approach to identify metabolite biomarkers that accurately predict food intake.

METHODS

Data were aggregated from 5 controlled feeding studies in adults that tested the impact of specific foods (almonds, avocados, broccoli, walnuts, barley, and oats) on the gastrointestinal microbiota. Fecal samples underwent GC-MS metabolomic analysis; 344 metabolites were detected in preintervention samples, whereas 307 metabolites were detected postintervention. After removing metabolites that were only detected in either pre- or postintervention and those undetectable in ≥80% of samples in all study groups, changes in 96 metabolites relative concentrations (treatment postintervention minus preintervention) were utilized in random forest models to 1) examine the relation between food consumption and fecal metabolome changes and 2) rank the fecal metabolites by their predictive power (i.e., feature importance score).

RESULTS

Using the change in relative concentration of 96 fecal metabolites, 6 single-food random forest models for almond, avocado, broccoli, walnuts, whole-grain barley, and whole-grain oats revealed prediction accuracies between 47% and 89%. When comparing foods with one another, almond intake was differentiated from walnut intake with 91% classification accuracy.

CONCLUSIONS

Our findings reveal promise in utilizing fecal metabolites as objective complements to certain self-reported food intake estimates. Future research on other foods at different doses and dietary patterns is needed to identify biomarkers that can be applied in feeding study compliance and clinical settings.

A fast kernel independence test for cluster-correlated data

Cluster-correlated data receives a lot of attention in biomedical and longitudinal studies and it is of interest to assess the generalized dependence between two multivariate variables under the cluster-correlated structure. The Hilbert-Schmidt independence criterion (HSIC) is a powerful kernel-based test statistic that captures various dependence between two random vectors and can be applied to an arbitrary non-Euclidean domain. However, the existing HSIC is not directly applicable to cluster-correlated data. Therefore, we propose a HSIC-based test of independence for cluster-correlated data. The new test statistic combines kernel information so that the dependence structure in each cluster is fully considered and exhibits good performance under high dimensions. Moreover, a rapid p value approximation makes the new test fast applicable to large datasets. Numerical studies show that the new approach performs well in both synthetic and real world data.

Potential role of gut microbiota and its metabolites in radiation-induced intestinal damage

Radiation-induced intestinal damage (RIID) is a serious disease with limited effective treatment. Nuclear explosion, nuclear release, nuclear application and especially radiation therapy are all highly likely to cause radioactive intestinal damage. The intestinal microecology is an organic whole with a symbiotic relationship formed by the interaction between a relatively stable microbial community living in the intestinal tract and the host. Imbalance and disorders of intestinal microecology are related to the occurrence and development of multiple systemic diseases, especially intestinal diseases. Increasing evidence indicates that the gut microbiota and its metabolites play an important role in the pathogenesis and prevention of RIID. Radiation leads to gut microbiota imbalance, including a decrease in the number of beneficial bacteria and an increase in the number of harmful bacteria that cause RIID. In this review, we describe the pathological mechanisms of RIID, the changes in intestinal microbiota, the metabolites induced by radiation, and their mechanism in RIID. Finally, the mechanisms of various methods for regulating the microbiota in the treatment of RIID are summarized.

Standardized multi-omics of Earth's microbiomes reveals microbial and metabolite diversity

Despite advances in sequencing, lack of standardization makes comparisons across studies challenging and hampers insights into the structure and function of microbial communities across multiple habitats on a planetary scale. Here we present a multi-omics analysis of a diverse set of 880 microbial community samples collected for the Earth Microbiome Project. We include amplicon (16S, 18S, ITS) and shotgun metagenomic sequence data, and untargeted metabolomics data (liquid chromatography-tandem mass spectrometry and gas chromatography mass spectrometry). We used standardized protocols and analytical methods to characterize microbial communities, focusing on relationships and co-occurrences of microbially related metabolites and microbial taxa across environments, thus allowing us to explore diversity at extraordinary scale. In addition to a reference database for metagenomic and metabolomic data, we provide a framework for incorporating additional studies, enabling the expansion of existing knowledge in the form of an evolving community resource. We demonstrate the utility of this database by testing the hypothesis that every microbe and metabolite is everywhere but the environment selects. Our results show that metabolite diversity exhibits turnover and nestedness related to both microbial communities and the environment, whereas the relative abundances of microbially related metabolites vary and co-occur with specific microbial consortia in a habitat-specific manner. We additionally show the power of certain chemistry, in particular terpenoids, in distinguishing Earth's environments (for example, terrestrial plant surfaces and soils, freshwater and marine animal stool), as well as that of certain microbes including Conexibacter woesei (terrestrial soils), Haloquadratum walsbyi (marine deposits) and Pantoea dispersa (terrestrial plant detritus). This Resource provides insight into the taxa and metabolites within microbial communities from diverse habitats across Earth, informing both microbial and chemical ecology, and provides a foundation and methods for multi-omics microbiome studies of hosts and the environment.

Material Engineering in Gut Microbiome and Human Health

Tremendous progress has been made in the past decade regarding our understanding of the gut microbiome's role in human health. Currently, however, a comprehensive and focused review marrying the two distinct fields of gut microbiome and material research is lacking. To bridge the gap, the current paper discusses critical aspects of the rapidly emerging research topic of "material engineering in the gut microbiome and human health." By engaging scientists with diverse backgrounds in biomaterials, gut-microbiome axis, neuroscience, synthetic biology, tissue engineering, and biosensing in a dialogue, our goal is to accelerate the development of research tools for gut microbiome research and the development of therapeutics that target the gut microbiome. For this purpose, state-of-the-art knowledge is presented here on biomaterial technologies that facilitate the study, analysis, and manipulation of the gut microbiome, including intestinal organoids, gut-on-chip models, hydrogels for spatial mapping of gut microbiome compositions, microbiome biosensors, and oral bacteria delivery systems. In addition, a discussion is provided regarding the microbiome-gut-brain axis and the critical roles that biomaterials can play to investigate and regulate the axis. Lastly, perspectives are provided regarding future directions on how to develop and use novel biomaterials in gut microbiome research, as well as essential regulatory rules in clinical translation. In this way, we hope to inspire research into future biomaterial technologies to advance gut microbiome research and gut microbiome-based theragnostics.

The Relationship Between Gut Microbiome and Bile Acids in Primates With Diverse Diets

Primates have evolved a variety of feeding habits and intestinal physiological structure. Gut microbiome act as metabolic organs in many biological processes and play a vital role in adaptation to dietary niches. Gut microbiome also convert primary bile acids (BAs) to secondary. BAs profile and gut microbiome are together influenced by diets and play a significant role in nutrient absorption. The regulation between gut microbiome and BAs metabolism is bidirectional although the relationship in primates consuming diverse diets is still unclear. Here, we investigated gut microbiome structures, fecal BAs profile, and their relationship in primates preferring three distinct diets. We found that gut microbiome communities are well differentiated among dietary groups. Folivorous primates had higher Firmicutes abundance and lower Prevotella to Bacaeroides ratios, possibly related to fiber consumption. Frugivorous primates are colonized predominantly by Prevotella and Bacteroides, pointing to an increased adaptation to high-sugar and simple carbohydrate diets. Likewise, BA profiles differ according to diet in a manner predictable from the known effects of BAs on metabolism. Folivorous primates have high conjugated bile acid levels and low unconjugated to conjugated BA ratios, consistent with their fiber-rich leaf-eating diet. Much of the differentiation in secondary and unconjugated BAs is associated with microbiome composition shifts and individual bile acid concentrations are correlated with the abundance of distinct bacterial taxonomic groups. Omnivores have higher concentrations of secondary BAs, mainly lithocholic acid (LCA). These levels are significantly positively correlated with the presence of Clostrida species, showing that the digestion requirements of omnivores are different from plant-eating primates. In conclusion, gut microbiome and BAs can respond to changes in diet and are associated with nutrient component consumption in each diet primate group. Our study is the first to demonstrate BA profile differentiation among primates preferring diverse diets. BAs thus appear to work with gut microbiome to help primates adapt to their diet.

A meta-analysis study of the robustness and universality of gut microbiota-shrimp diseases relationship

Intensive case study has shown dysbiosis in the gut microbiota-shrimp disease relationship, however, variability in experimental design and the diversity of diseases arise the question whether some gut indicators are robust and universal in response to shrimp health status, irrespective of causal agents. Through an unbiased subject-level meta-analysis framework, we re-analyzed 10 studies including 261 samples, 4 lifestages, 6 different diseases (the causal agents are virus, bacterial, eukaryotic pathogens, or unknown). Results showed that shrimp diseases reproducibly altered the structure of gut bacterial community, but not diversity. After ruling out the lifestage- and disease specific- discriminatory taxa (different diseases dependent indicators), we identify 18 common disease-discriminatory taxa (indicative of health status, irrespective of causal agents) that accurately diagnosed (90.0% accuracy) shrimp health status, regardless of different diseases. These optimizations substantially improved the performance (62.6% vs. 90.0%) diagnosing model. The robustness and universality of model was validated for effectiveness via leave-one-dataset-out validation and independent cohorts. Interspecies interaction and stability of the gut microbiotas were consistently compromised in diseased shrimp compared with corresponding healthy cohorts, while stochasticity and beta-dispersion exhibited the opposite trend. Collectively, our findings exemplify the utility of microbiome meta-analyses in identifying robust and reproducible features for quantitatively diagnosing disease incidence, and the downstream consequences for shrimp pathogenesis from an ecological prospective. This article is protected by copyright. All rights reserved.

Gut microbial metabolome in inflammatory bowel disease: From association to therapeutic perspectives

Inflammatory bowel disease (IBD), comprising Crohn's disease (CD) and ulcerative colitis (UC), is a set of clinically chronic, relapsing gastrointestinal inflammatory disease and lacks of an absolute cure. Although the precise etiology is unknown, developments in high-throughput microbial genomic sequencing significantly illuminate the changes in the intestinal microbial structure and functions in patients with IBD. The application of microbial metabolomics suggests that the microbiota can influence IBD pathogenesis by producing metabolites, which are implicated as crucial mediators of host-microbial crosstalk. This review aims to elaborate the current knowledge of perturbations of the microbiome-metabolome interface in IBD with description of altered composition and metabolite profiles of gut microbiota. We emphasized and elaborated recent findings of several potentially protective metabolite classes in IBD, including fatty acids, amino acids and derivatives and bile acids. This article will facilitate a deeper understanding of the new therapeutic approach for IBD by applying metabolome-based adjunctive treatment.

MIMOSA2: a metabolic network-based tool for inferring mechanism-supported relationships in microbiome-metabolome data

MOTIVATION

Recent technological developments have facilitated an expansion of microbiome-metabolome studies, in which samples are assayed using both genomic and metabolomic technologies to characterize the abundances of microbial taxa and metabolites. A common goal of these studies is to identify microbial species or genes that contribute to differences in metabolite levels across samples. Previous work indicated that integrating these datasets with reference knowledge on microbial metabolic capacities may enable more precise and confident inference of microbe-metabolite links.

RESULTS

We present MIMOSA2, an R package and web application for model-based integrative analysis of microbiome-metabolome datasets. MIMOSA2 uses genomic and metabolic reference databases to construct a community metabolic model based on microbiome data and uses this model to predict differences in metabolite levels across samples. These predictions are compared with metabolomics data to identify putative microbiome-governed metabolites and taxonomic contributors to metabolite variation. MIMOSA2 supports various input data types and customization with user-defined metabolic pathways. We establish MIMOSA2's ability to identify ground truth microbial mechanisms in simulation datasets, compare its results with experimentally inferred mechanisms in honeybee microbiota, and demonstrate its application in two human studies of inflammatory bowel disease. Overall, MIMOSA2 combines reference databases, a validated statistical framework, and a user-friendly interface to facilitate modeling and evaluating relationships between members of the microbiota and their metabolic products.

AVAILABILITY AND IMPLEMENTATION

MIMOSA2 is implemented in R under the GNU General Public License v3.0 and is freely available as a web server at http://elbo-spice.cs.tau.ac.il/shiny/MIMOSA2shiny/ and as an R package from http://www.borensteinlab.com/software_MIMOSA2.html.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

The Effects of Consuming White Button Mushroom Agaricus bisporus on the Brain and Liver Metabolome Using a Targeted Metabolomic Analysis

A targeted metabolomic analysis was performed on tissues derived from pigs fed diets supplemented with white button mushrooms (WBM) to determine the effect on the liver and brain metabolome. Thirty-one pigs were fed a grower diet alone or supplemented with either three or six servings of freeze-dried WBM for six weeks. Tissue metabolomes were analyzed using targeted liquid chromatography-mass spectrometry (LC-MS) combined with chemical similarity enrichment analysis (ChemRICH) and correlated to WBM-induced changes in fecal microbiome composition. Results indicated that WBM can differentially modulate metabolites in liver, brain cortex and hippocampus of healthy pigs. Within the glycero-phospholipids, there was an increase in alkyl-acyl-phosphatidyl-cholines (PC-O 40:3) in the hippocampus of pigs fed six servings of WBM. A broader change in glycerophospholipids and sphingolipids was detected in the liver with a reduction in several lipid species in pigs fed both WBM diets but with an increase in amino acids known as precursors of neurotransmitters in the cortex of pigs fed six servings of WBM. Metabolomic changes were positively correlated with increased abundance of Cryomorphaceae, Lachnospiraceae, Flammeovirgaceae and Ruminococcaceae in the microbiome suggesting that WBM can also positively impact tissue metabolite composition.