Metagenomic analysis of gut microbiome reveals a dynamic change in Alistipes onderdonkii in the preclinical model of pancreatic cancer, suppressing its proliferation

Detection of typical indigenous gut bacteria related to kanpyo Lagenaria siceraria var. hispida powder in murine caecum and human faecal cultures

Kanpyo (KP) is an edible dried product produced by peeling the fruit of the gourd Lagenaria siceraria var. hispida; it is used in the traditional Japanese cuisine. The health functionality of KP due to its rich dietary fibre is expected to include a possible combined effect of KP-responsive indigenous gut bacteria (KP-RIB). However, its effect on the gut microbiota is unclear. To determine the effects of the KP on the gut microbiota and their host, Institute of Cancer Research mice were fed a high-sucrose diet containing no fibre (NF) or 5% (w/w) KP for 14 days, and their caecal microbiota was analysed by 16S rRNA (V4) amplicon sequencing. Higher faecal frequency and weight and lower spleen weight and spleen tumour necrosis factor-α levels were observed in KP-fed mice than in NF-fed mice (p < 0.05). KP increased and decreased the abundance of short-chain fatty acid producer Lachnospiraceae and obesity-inflammation related Allobaculum species, respectively. In the case of human faecal cultures, stool samples from five healthy volunteers were inoculated and incubated at 37 °C for 24 h anaerobically; 3.2% (w/v) KP suppressed putrefactive compounds (indole, phenol, and ammonia). KP increased butyrate-producer Faecalibacterium, acetate/lactate-producer Bifidobacterium, and Lachnospira. Furthermore, KP cultures showed high antioxidant and RAW264.7 macrophage cell activation capacities. These results suggest that KP-RIB and KP intake may synergistically affect host health. However, further studies are required to clarify the synergistic effects of KP and KP-RIB.

Gut microbiome modulates the effects of a personalised postprandial-targeting (PPT) diet on cardiometabolic markers: a diet intervention in pre-diabetes

OBJECTIVE

To explore the interplay between dietary modifications, microbiome composition and host metabolic responses in a dietary intervention setting of a personalised postprandial-targeting (PPT) diet versus a Mediterranean (MED) diet in pre-diabetes.

DESIGN

In a 6-month dietary intervention, adults with pre-diabetes were randomly assigned to follow an MED or PPT diet (based on a machine-learning algorithm for predicting postprandial glucose responses). Data collected at baseline and 6 months from 200 participants who completed the intervention included: dietary data from self-recorded logging using a smartphone application, gut microbiome data from shotgun metagenomics sequencing of faecal samples, and clinical data from continuous glucose monitoring, blood biomarkers and anthropometrics.

RESULTS

PPT diet induced more prominent changes to the gut microbiome composition, compared with MED diet, consistent with overall greater dietary modifications observed. Particularly, microbiome alpha-diversity increased significantly in PPT (p=0.007) but not in MED arm (p=0.18). Post hoc analysis of changes in multiple dietary features, including food-categories, nutrients and PPT-adherence score across the cohort, demonstrated significant associations between specific dietary changes and species-level changes in microbiome composition. Furthermore, using causal mediation analysis we detect nine microbial species that partially mediate the association between specific dietary changes and clinical outcomes, including three species (from Bacteroidales, Lachnospiraceae, Oscillospirales orders) that mediate the association between PPT-adherence score and clinical outcomes of hemoglobin A1c (HbA1c), high-density lipoprotein cholesterol (HDL-C) and triglycerides. Finally, using machine-learning models trained on dietary changes and baseline clinical data, we predict personalised metabolic responses to dietary modifications and assess features importance for clinical improvement in cardiometabolic markers of blood lipids, glycaemic control and body weight.

CONCLUSIONS

Our findings support the role of gut microbiome in modulating the effects of dietary modifications on cardiometabolic outcomes, and advance the concept of precision nutrition strategies for reducing comorbidities in pre-diabetes.

TRIAL REGISTRATION NUMBER

NCT03222791.

Gut microbial signature in lung cancer patients highlights specific taxa as predictors for durable clinical benefit

We aimed to determine microbial signature linked with lung cancer (LC) diagnosis and to define taxa linked with durable clinical benefit (DCB) of advanced LC patients. Stool samples for microbial 16S amplicon sequencing and clinical data were collected from 75 LC patients (50 of which were treated with checkpoint inhibitors) and 31 matched healthy volunteers. We compared LC to healthy controls and patients with DCB to those without. LC patients had lower α-diversity and higher between-subject diversity. Random Forests model to differentiate LC cases from controls ROC-AUC was 0.74. Clostridiales, Lachnospiraceae, and Faecalibacterium prausnitzii taxa abundance was decreased in LC compared to controls. High Akkermansia muciniphila correlated with DCB (HR 4.26, 95% CI 1.98-9.16), not only for the immunotherapy-treated patients. In addition, high Alistipes onderdonkii (HR 3.08, 95% CI 1.34-7.06) and high Ruminococcus (HR 7.76, 95% CI 3.23-18.65) correlated with DCB.Our results support the importance of gut microbiome in LC. We have validated the apparent predictive value of Akkermansia muciniphila, and highlighted Alistipes onderdonkii and Ruminococcus taxa correlation with DCB. Upon additional validations those can be used as biomarkers or as targets for future therapeutic interventions.

The Species of Gut Bacteria Associated with Antitumor Immunity in Cancer Therapy

Both preclinical and clinical studies have demonstrated that the modulation of gut microbiota could be a promising strategy for enhancing antitumor immune responses and reducing resistance to immunotherapy in cancer. Various mechanisms, including activation of pattern recognition receptors, gut commensals-produced metabolites and antigen mimicry, have been revealed. Different gut microbiota modulation strategies have been raised, such as fecal microbiota transplantation, probiotics, and dietary selection. However, the identification of gut bacteria species that are either favorable or unfavorable for cancer therapy remains a major challenge. Herein, we summarized the findings related to gut microbiota species observed in the modulation of antitumor immunity. We also discussed the different mechanisms underlying different gut bacteria's functions and the potential applications of these bacteria to cancer immunotherapy in the future.