Probiotics modulated gut microbiota suppresses hepatocellular carcinoma growth in mice.

The beneficial roles of probiotics in lowering the gastrointestinal inflammation and preventing colorectal cancer have been frequently demonstrated, but their immunomodulatory effects and mechanism in suppressing the growth of extraintestinal tumors remain unexplored. Here, we adopted a mouse model and metagenome sequencing to investigate the efficacy of probiotic feeding in controlling s.c. hepatocellular carcinoma (HCC) and the underlying mechanism suppressing the tumor progression. Our result demonstrated that Prohep, a novel probiotic mixture, slows down the tumor growth significantly and reduces the tumor size and weight by 40% compared with the control. From a mechanistic point of view the down-regulated IL-17 cytokine and its major producer Th17 cells, whose levels decreased drastically, played critical roles in tumor reduction upon probiotics feeding. Cell staining illustrated that the reduced Th17 cells in the tumor of the probiotic-treated group is mainly caused by the reduced frequency of migratory Th17 cells from the intestine and peripheral blood. In addition, shotgun-metagenome sequencing revealed the crosstalk between gut microbial metabolites and the HCC development. Probiotics shifted the gut microbial community toward certain beneficial bacteria, including Prevotella and Oscillibacter, that are known producers of antiinflammatory metabolites, which subsequently reduced the Th17 polarization and promoted the differentiation of antiinflammatory Treg/Tr1 cells in the gut. Overall, our study offers novel insights into the mechanism by which probiotic treatment modulates the microbiota and influences the regulation of the T-cell differentiation in the gut, which in turn alters the level of the proinflammatory cytokines in the extraintestinal tumor microenvironment.

COMAN: a web server for comprehensive metatranscriptomics analysis.

BACKGROUND: Microbiota-oriented studies based on metagenomic or metatranscriptomic sequencing have revolutionised our understanding on microbial ecology and the roles of both clinical and environmental microbes. The analysis of massive metatranscriptomic data requires extensive computational resources, a collection of bioinformatics tools and expertise in programming. RESULTS: We developed COMAN (Comprehensive Metatranscriptomics Analysis), a web-based tool dedicated to automatically and comprehensively analysing metatranscriptomic data. COMAN pipeline includes quality control of raw reads, removal of reads derived from non-coding RNA, followed by functional annotation, comparative statistical analysis, pathway enrichment analysis, co-expression network analysis and high-quality visualisation. The essential data generated by COMAN are also provided in tabular format for additional analysis and integration with other software. The web server has an easy-to-use interface and detailed instructions, and is freely available at http://sbb.hku.hk/COMAN/ CONCLUSIONS: COMAN is an integrated web server dedicated to comprehensive functional analysis of metatranscriptomic data, translating massive amount of reads to data tables and high-standard figures. It is expected to facilitate the researchers with less expertise in bioinformatics in answering microbiota-related biological questions and to increase the accessibility and interpretation of microbiota RNA-Seq data.

Developing a molecular roadmap of drug-food interactions.

Recent research has demonstrated that consumption of food -especially fruits and vegetables- can alter the effects of drugs by interfering either with their pharmacokinetic or pharmacodynamic processes. Despite the recognition of such drug-food associations as an important element for successful therapeutic interventions, a systematic approach for identifying, predicting and preventing potential interactions between food and marketed or novel drugs is not yet available. The overall objective of this work was to sketch a comprehensive picture of the interference of ∼ 4,000 dietary components present in ∼1800 plant-based foods with the pharmacokinetics and pharmacodynamics processes of medicine, with the purpose of elucidating the molecular mechanisms involved. By employing a systems chemical biology approach that integrates data from the scientific literature and online databases, we gained a global view of the associations between diet and dietary molecules with drug targets, metabolic enzymes, drug transporters and carriers currently deposited in DrugBank. Moreover, we identified disease areas and drug targets that are most prone to the negative effects of drug-food interactions, showcasing a platform for making recommendations in relation to foods that should be avoided under certain medications. Lastly, by investigating the correlation of gene expression signatures of foods and drugs we were able to generate a completely novel drug-diet interactome map.

mNFE: microbiome network flow entropy for detecting pre-disease states of type 1 diabetes.

In the development of Type 1 diabetes (T1D), there are critical states just before drastic changes, and identifying these pre-disease states may predict T1D or provide crucial early-warning signals. Unlike gene expression data, gut microbiome data can be collected noninvasively from stool samples. Gut microbiome sequencing data contain different levels of phylogenetic information that can be utilized to detect the tipping point or critical state in a reliable manner, thereby providing accurate and effective early-warning signals. However, it is still difficult to detect the critical state of T1D based on gut microbiome data due to generally non-significant differences between healthy and critical states. To address this problem, we proposed a new method - microbiome network flow entropy (mNFE) based on a single sample from each individual - for detecting the critical state before seroconversion and abrupt transitions of T1D at various taxonomic levels. The numerical simulation validated the robustness of mNFE under different noise levels. Furthermore, based on real datasets, mNFE successfully identified the critical states and their dynamic network biomarkers (DNBs) at different taxonomic levels. In addition, we found some high-frequency species, which are closely related to the unique clinical characteristics of autoantibodies at the four levels, and identified some non-differential 'dark species' play important roles during the T1D progression. mNFE can robustly and effectively detect the pre-disease states at various taxonomic levels and identify the corresponding DNBs with only a single sample for each individual. Therefore, our mNFE method provides a new approach not only for T1D pre-disease diagnosis or preventative treatment but also for preventative medicine of other diseases by gut microbiome.

Resistant starch intake facilitates weight loss in humans by reshaping the gut microbiota.

Emerging evidence suggests that modulation of gut microbiota by dietary fibre may offer solutions for metabolic disorders. In a randomized placebo-controlled crossover design trial (ChiCTR-TTRCC-13003333) in 37 participants with overweight or obesity, we test whether resistant starch (RS) as a dietary supplement influences obesity-related outcomes. Here, we show that RS supplementation for 8 weeks can help to achieve weight loss (mean -2.8 kg) and improve insulin resistance in individuals with excess body weight. The benefits of RS are associated with changes in gut microbiota composition. Supplementation with Bifidobacterium adolescentis, a species that is markedly associated with the alleviation of obesity in the study participants, protects male mice from diet-induced obesity. Mechanistically, the RS-induced changes in the gut microbiota alter the bile acid profile, reduce inflammation by restoring the intestinal barrier and inhibit lipid absorption. We demonstrate that RS can facilitate weight loss at least partially through B. adolescentis and that the gut microbiota is essential for the action of RS.

Identification of robust and generalizable biomarkers for microbiome-based stratification in lifestyle interventions.

BACKGROUND: A growing body of evidence suggests that the gut microbiota is strongly linked to general human health. Microbiome-directed interventions, such as diet and exercise, are acknowledged as a viable and achievable strategy for preventing disorders and improving human health. However, due to the significant inter-individual diversity of the gut microbiota between subjects, lifestyle recommendations are expected to have distinct and highly variable impacts to the microbiome structure. RESULTS: Here, through a large-scale meta-analysis including 1448 shotgun metagenomics samples obtained longitudinally from 396 individuals during lifestyle studies, we revealed Bacteroides stercoris, Prevotella copri, and Bacteroides vulgatus as biomarkers of microbiota's resistance to structural changes, and aromatic and non-aromatic amino acid biosynthesis as important regulator of microbiome dynamics. We established criteria for distinguishing between significant compositional changes from normal microbiota fluctuation and classified individuals based on their level of response. We further developed a machine learning model for predicting "responders" and "non-responders" independently of the type of intervention with an area under the curve of up to 0.86 in external validation cohorts of different ethnicities. CONCLUSIONS: We propose here that microbiome-based stratification is possible for identifying individuals with highly plastic or highly resistant microbial structures. Identifying subjects that will not respond to generalized lifestyle therapeutic interventions targeting the restructuring of gut microbiota is important to ensure that primary end-points of clinical studies are reached. Video Abstract.

Impaired flux of bile acids from the liver to the gut reveals microbiome-immune interactions associated with liver damage.

Currently, there is evidence that alteration in the gut ecosystem contributes to the development of liver diseases, however, the complex mechanisms involved are still unclear. We induced cholestasis in mice by bile duct ligation (BDL), mirroring the phenotype of a bile duct obstruction, to understand how gut microbiota alterations caused by an impaired flow of bile acid to the gut contribute to the pathogenesis and progression of liver disease. We performed longitudinal stool, heart, and liver sampling using mice receiving BDL and controls receiving sham operation (ShamOP). Shotgun metagenomics profiling using fecal samples taken before and on day 1, day 3, and day 7 after surgery was performed, and the cytokines and clinical chemistry profiles from heart blood, as well as the liver bile acids profile, were measured. The BDL surgery reshaped the microbiome of mice, resulting in highly distinct characteristics compared to the ShamOP. Our analysis of the microbiome pathways and ECs revealed that BDL reduces the production of hepatoprotective compounds in the gut, such as biotin, spermidine, arginine, and ornithine, which were negatively associated with inflammatory cytokines (IL-6, IL-23, MCP-1). The reduction of the functional potential of the gut microbiota in producing those hepatoprotective compounds is associated with the decrease of beneficial bacteria species from Anaerotruncus, Blautia, Eubacterium, and Lachnoclostridium genera, as well as the increase of disease-associated bacteria e.g., Escherichia coli and Entercoccus faecalis. Our findings advances our knowledge of the gut microbiome-bile acids-liver triangle, which may serve as a potential therapeutic strategy for liver diseases.

Genome-scale metabolic modeling of Aspergillus fumigatus strains reveals growth dependencies on the lung microbiome.

Aspergillus fumigatus, an opportunistic human pathogen, frequently infects the lungs of people with cystic fibrosis and is one of the most common causes of infectious-disease death in immunocompromised patients. Here, we construct 252 strain-specific, genome-scale metabolic models of this important fungal pathogen to study and better understand the metabolic component of its pathogenic versatility. The models show that 23.1% of A. fumigatus metabolic reactions are not conserved across strains and are mainly associated with amino acid, nucleotide, and nitrogen metabolism. Profiles of non-conserved reactions and growth-supporting reaction fluxes are sufficient to differentiate strains, for example by environmental or clinical origin. In addition, shotgun metagenomics analysis of sputum from 40 cystic fibrosis patients (15 females, 25 males) before and after diagnosis with an A. fumigatus colonization suggests that the fungus shapes the lung microbiome towards a more beneficial fungal growth environment associated with aromatic amino acid availability and the shikimate pathway. Our findings are starting points for the development of drugs or microbiome intervention strategies targeting fungal metabolic needs for survival and colonization in the non-native environment of the human lung.

Resistant starch decreases intrahepatic triglycerides in patients with NAFLD via gut microbiome alterations.

Non-alcoholic fatty liver disease (NAFLD) is a hepatic manifestation of metabolic dysfunction for which effective interventions are lacking. To investigate the effects of resistant starch (RS) as a microbiota-directed dietary supplement for NAFLD treatment, we coupled a 4-month randomized placebo-controlled clinical trial in individuals with NAFLD (ChiCTR-IOR-15007519) with metagenomics and metabolomics analysis. Relative to the control (n = 97), the RS intervention (n = 99) resulted in a 9.08% absolute reduction of intrahepatic triglyceride content (IHTC), which was 5.89% after adjusting for weight loss. Serum branched-chain amino acids (BCAAs) and gut microbial species, in particular Bacteroides stercoris, significantly correlated with IHTC and liver enzymes and were reduced by RS. Multi-omics integrative analyses revealed the interplay among gut microbiota changes, BCAA availability, and hepatic steatosis, with causality supported by fecal microbiota transplantation and monocolonization in mice. Thus, RS dietary supplementation might be a strategy for managing NAFLD by altering gut microbiota composition and functionality.

Study on the differences of gut microbiota composition between phlegm-dampness syndrome and qi-yin deficiency syndrome in patients with metabolic syndrome.

Background: Metabolic syndrome (MS) is a group of complex medical conditions that can lead to serious cardiovascular and cerebrovascular diseases. According to the theory of traditional Chinese medicine (TCM), MS can be divided into two main subtypes termed 'phlegm-dampness syndrome' (TSZE) and 'qi-yin deficiency syndrome' (QYLX). At present, the research into intestinal microbiota of different TCM syndromes of MS and its association with clinical manifestation is lacking. Materials and methods: Using 16S rRNA sequencing, we performed a cross-sectional analysis of human gut microbiota between two different TCM syndromes (QYLX and TSZE, n=60) of MS, and their differences with healthy participants (n=30). Results: We found that the QYLX and TSZE groups differ from the healthy control group in the overall gut microbiota composition, and some specific microbial taxa and functional pathways. Moreover, significantly differentially abundant taxa and distinct BMI-correlated taxa were observed between QYLX and TSZE groups, suggesting the potential contribution of gut microbiota to the distinction between the two TCM syndromes. The predicted functional profiles also showed considerable differences, especially pathways related to amino acid metabolism and lipopolysaccharide synthesis. Conclusion: Our study highlights the gut microbiota's contribution to the differentiation between two TCM syndromes of MS and may provide the rationale for adopting different microbiota-directed treatment strategies for different TCM syndromes of MS in the future.

Risk assessment with gut microbiome and metabolite markers in NAFLD development.

A growing body of evidence suggests interplay between the gut microbiota and the pathogenesis of nonalcoholic fatty liver disease (NAFLD). However, the role of the gut microbiome in early detection of NAFLD is unclear. Prospective studies are necessary for identifying reliable, microbiome markers for early NAFLD. We evaluated 2487 individuals in a community-based cohort who were followed up 4.6 years after initial clinical examination and biospecimen sampling. Metagenomic and metabolomic characterizations using stool and serum samples taken at baseline were performed for 90 participants who progressed to NAFLD and 90 controls who remained NAFLD free at the follow-up visit. Cases and controls were matched for gender, age, body mass index (BMI) at baseline and follow-up, and 4-year BMI change. Machine learning models integrating baseline microbial signatures (14 features) correctly classified participants (auROCs of 0.72 to 0.80) based on their NAFLD status and liver fat accumulation at the 4-year follow up, outperforming other prognostic clinical models (auROCs of 0.58 to 0.60). We confirmed the biological relevance of the microbiome features by testing their diagnostic ability in four external NAFLD case-control cohorts examined by biopsy or magnetic resonance spectroscopy, from Asia, Europe, and the United States. Our findings raise the possibility of using gut microbiota for early clinical warning of NAFLD development.

Bifidobacterium adolescentis Alleviates Liver Steatosis and Steatohepatitis by Increasing Fibroblast Growth Factor 21 Sensitivity.

The gut microbiota is a newly identified contributor to the development of non-alcoholic fatty liver disease (NAFLD). Previous studies of Bifidobacterium adolescentis (B. adolescentis), a species of Bifidobacterium that is common in the human intestinal tract, have demonstrated that it can alleviate liver steatosis and steatohepatitis. Fibroblast growth factor 21 (FGF21) has long been considered as a biomarker of NAFLD, and recent studies have shown the protective effect of FGF21 analogs on NAFLD. We wondered whether B. adolescentis treatment would alleviate NAFLD via the interaction with FGF21. To this end, male C57BL/6J mice on a choline-deficient high-fat diet (CDHFD) were treated with drinking water supplemented with B. adolescentis for 8 weeks, followed by the acute administration of recombinant mouse FGF21 protein (rmFGF21) to conduct the FGF21 response test. Consistent with previous studies, B. adolescentis supplementation reversed the CDHFD-induced liver steatosis and steatohepatitis. This was evaluated on the NAFLD activity score (NAS), reduced liver enzymes, and lipid accumulation. Further studies demonstrated that B. adolescentis supplementation preserved the gut barrier, reduced the gut microbiota-derived lipopolysaccharide (LPS), and inhibited the hepatic TLR4/NF-κB pathway. This was accompanied by the elevated expressions of the receptors of FGF21, fibroblast growth factor receptor 1 (FGFR1) and ß-klotho (KLB), in the liver and the decreased expression of FGF21. The results of FGF21 response test showed that B. adolescentis supplementation alleviated the CDHFD-induced FGF21 resistance. In vivo experiments suggested that LPS could suppress the expression of FGF21 and KLB in a dose-dependent manner. Collectively, this study showed that B. adolescentis supplementation could alleviate NAFLD by increasing FGF21 sensitivity.

Decreased Abundance of Akkermansia muciniphila Leads to the Impairment of Insulin Secretion and Glucose Homeostasis in Lean Type 2 Diabetes.

Although obesity occurs in most of the patients with type 2 diabetes (T2D), a fraction of patients with T2D are underweight or have normal weight. Several studies have linked the gut microbiome to obesity and T2D, but the role of gut microbiota in lean individuals with T2D having unique clinical characteristics remains unclear. A metagenomic and targeted metabolomic analysis is conducted in 182 lean and abdominally obese individuals with and without newly diagnosed T2D. The abundance of Akkermansia muciniphila (A. muciniphila) significantly decreases in lean individuals with T2D than without T2D, but not in the comparison of obese individuals with and without T2D. Its abundance correlates inversely with serum 3ß-chenodeoxycholic acid (ßCDCA) levels and positively with insulin secretion and fibroblast growth factor 15/19 (FGF15/19) concentrations. The supplementation with A. muciniphila is sufficient to protect mice against high sucrose-induced impairment of glucose intolerance by decreasing ßCDCA and increasing insulin secretion and FGF15/19. Furthermore, ßCDCA inhibits insulin secretion and FGF15/19 expression. These findings suggest that decreased abundance of A. muciniphila is linked to the impairment of insulin secretion and glucose homeostasis in lean T2D, paving the way for new therapeutic options for the prevention or treatment of diabetes.

Gut microbiome functionality might be associated with exercise tolerance and recurrence of resected early-stage lung cancer patients.

Impaired exercise tolerance and lung function is a marker for increased mortality in lung cancer patients undergoing lung resection surgery. Recent data suggest that the gut-lung axis regulates systemic metabolic and immune functions, and microbiota might alter exercise tolerance. Here, we aimed to evaluate the associations between gut microbiota and outcomes in lung cancer patients who underwent lung resection surgery. We analysed stool samples, from 15 early-stage lung cancer patients, collected before and after surgical resection using shotgun metagenomic and Internal Transcribed Spacer (ITS) sequencing. We analysed microbiome and mycobiome associations with post-surgery lung function and cardiopulmonary exercise testing (CPET) to assess the maximum level of work achieved. There was a significant difference, between pre- and post-surgical resection samples, in microbial community functional profiles and several species from Alistipes and Bacteroides genus, associated with the production of SCFAs, increased significantly in abundance. Interestingly, an increase in VO2 coincides with an increase in certain species and the "GABA shunt" pathway, suggesting that treatment outcome might improve by enriching butyrate-producing species. Here, we revealed associations between specific gut bacteria, fungi, and their metabolic pathways with the recovery of lung function and exercise capacity.

An integrative understanding of the large metabolic shifts induced by antibiotics in critical illness.

Antibiotics are commonly used in the Intensive Care Unit (ICU); however, several studies showed that the impact of antibiotics to prevent infection, multi-organ failure, and death in the ICU is less clear than their benefit on course of infection in the absence of organ dysfunction. We characterized here the compositional and metabolic changes of the gut microbiome induced by critical illness and antibiotics in a cohort of 75 individuals in conjunction with 2,180 gut microbiome samples representing 16 different diseases. We revealed an "infection-vulnerable" gut microbiome environment present only in critically ill treated with antibiotics (ICU+). Feeding of Caenorhabditis elegans with Bifidobacterium animalis and Lactobacillus crispatus, species that expanded in ICU+ patients, revealed a significant negative impact of these microbes on host viability and developmental homeostasis. These results suggest that antibiotic administration can dramatically impact essential functional activities in the gut related to immune responses more than critical illness itself, which might explain in part untoward effects of antibiotics in the critically ill.

Distinct composition and metabolic functions of human gut microbiota are associated with cachexia in lung cancer patients.

Cachexia is associated with decreased survival in cancer patients and has a prevalence of up to 80%. The etiology of cachexia is poorly understood, and limited treatment options exist. Here, we investigated the role of the human gut microbiome in cachexia by integrating shotgun metagenomics and plasma metabolomics of 31 lung cancer patients. The cachexia group showed significant differences in the gut microbial composition, functional pathways of the metagenome, and the related plasma metabolites compared to non-cachectic patients. Branched-chain amino acids (BCAAs), methylhistamine, and vitamins were significantly depleted in the plasma of cachexia patients, which was also reflected in the depletion of relevant gut microbiota functional pathways. The enrichment of BCAAs and 3-oxocholic acid in non-cachectic patients were positively correlated with gut microbial species Prevotella copri and Lactobacillus gasseri, respectively. Furthermore, the gut microbiota capacity for lipopolysaccharides biosynthesis was significantly enriched in cachectic patients. The involvement of the gut microbiome in cachexia was further observed in a high-performance machine learning model using solely gut microbial features. Our study demonstrates the links between cachectic host metabolism and specific gut microbial species and functions in a clinical setting, suggesting that the gut microbiota could have an influence on cachexia with possible therapeutic applications.

Metabolic modeling predicts specific gut bacteria as key determinants for Candida albicans colonization levels.

Candida albicans is a leading cause of life-threatening hospital-acquired infections and can lead to Candidemia with sepsis-like symptoms and high mortality rates. We reconstructed a genome-scale C. albicans metabolic model to investigate bacterial-fungal metabolic interactions in the gut as determinants of fungal abundance. We optimized the predictive capacity of our model using wild type and mutant C. albicans growth data and used it for in silico metabolic interaction predictions. Our analysis of more than 900 paired fungal-bacterial metabolic models predicted key gut bacterial species modulating C. albicans colonization levels. Among the studied microbes, Alistipes putredinis was predicted to negatively affect C. albicans levels. We confirmed these findings by metagenomic sequencing of stool samples from 24 human subjects and by fungal growth experiments in bacterial spent media. Furthermore, our pairwise simulations guided us to specific metabolites with promoting or inhibitory effect to the fungus when exposed in defined media under carbon and nitrogen limitation. Our study demonstrates that in silico metabolic prediction can lead to the identification of gut microbiome features that can significantly affect potentially harmful levels of C. albicans.

Expansion and persistence of antibiotic-specific resistance genes following antibiotic treatment.

Oral antibiotics are commonly prescribed to non-hospitalized adults. However, antibiotic-induced changes in the human gut microbiome are often investigated in cohorts with preexisting health conditions and/or concomitant medication, leaving the effects of antibiotics not completely understood. We used a combination of omic approaches to comprehensively assess the effects of antibiotics on the gut microbiota and particularly the gut resistome of a small cohort of healthy adults. We observed that 3 to 19 species per individual proliferated during antibiotic treatment and Gram-negative species expanded significantly in relative abundance. While the overall relative abundance of antibiotic resistance gene homologs did not significantly change, antibiotic-specific gene homologs with presumed resistance toward the administered antibiotics were common in proliferating species and significantly increased in relative abundance. Virome sequencing and plasmid analysis showed an expansion of antibiotic-specific resistance gene homologs even 3 months after antibiotic administration, while paired-end read analysis suggested their dissemination among different species. These results suggest that antibiotic treatment can lead to a persistent expansion of antibiotic resistance genes in the human gut microbiota and provide further data in support of good antibiotic stewardship.Abbreviation: ARG - Antibiotic resistance gene homolog; AsRG - Antibiotic-specific resistance gene homolog; AZY - Azithromycin; CFX - Cefuroxime; CIP - Ciprofloxacin; DOX - Doxycycline; FDR - False discovery rate; GRiD - Growth rate index value; HGT - Horizontal gene transfer; NMDS - Non-metric multidimensional scaling; qPCR - Quantitative polymerase chain reaction; RPM - Reads per million mapped reads; TA - Transcriptional activity; TE - Transposable element; TPM - Transcripts per million mapped reads.

A metagenome-wide association study of gut microbiome and visceral fat accumulation.

PURPOSE: Visceral fat is an independent risk factor for metabolic and cardiovascular disease. The study aimed to investigate the associations between gut microbiome and visceral fat. METHODS: We recruited 32 obese adults and 30 healthy controls at baseline. Among the obese subjects, 14 subjects underwent laparoscopic sleeve gastrectomy (LSG) and were followed 6 months after surgery. Abdominal visceral fat area (VFA) and subcutaneous fat area (SFA) were measured by magnetic resonance imaging. Waist, hipline, waist-to-hip ratio (WHR) and body mass index (BMI) were included as simple obese parameters. Gut microbiome was analyzed by metagenomic sequencing. RESULTS: Among the obese parameters, VFA had the largest number of correlations with the species that were differentially enriched between obese and healthy subjects, following by waist, WHR, BMI, hipline, and SFA. Within the species negatively correlated with VFA, Eubacterium eligens had the strongest correlation, following by Clostridium citroniae, C. symbiosum, Bacteroides uniformis, E. ventriosum, Ruminococcaceae bacterium D16, C. hathewayi, etc. C. hathewayi and C. citroniae were increased after LSG. Functional analyses showed that among all the obese parameters, VFA had strongest correlation coefficients with the obesity-related microbial pathways. Microbial pathways involved in carbohydrate fermentation and biosynthesis of L-glutamate and L-glutamine might contribute to visceral fat accumulation. CONCLUSIONS: Visceral fat was more closely correlated with gut microbiome compared with subcutaneous fat, suggesting an intrinsic connection between gut microbiome and metabolic cardiovascular diseases. Specific microbial species and pathways which were closely associated with visceral fat accumulation might contribute to new targeted therapies for metabolic disorders.

Predictable modulation of cancer treatment outcomes by the gut microbiota.

The gut microbiota has the potential to influence the efficacy of cancer therapy. Here, we investigated the contribution of the intestinal microbiome on treatment outcomes in a heterogeneous cohort that included multiple cancer types to identify microbes with a global impact on immune response. Human gut metagenomic analysis revealed that responder patients had significantly higher microbial diversity and different microbiota compositions compared to non-responders. A machine-learning model was developed and validated in an independent cohort to predict treatment outcomes based on gut microbiota composition and functional repertoires of responders and non-responders. Specific species, Bacteroides ovatus and Bacteroides xylanisolvens, were positively correlated with treatment outcomes. Oral gavage of these responder bacteria significantly increased the efficacy of erlotinib and induced the expression of CXCL9 and IFN-γ in a murine lung cancer model. These data suggest a predictable impact of specific constituents of the microbiota on tumor growth and cancer treatment outcomes with implications for both prognosis and therapy.