Need for prospective cohort studies to establish human gut microbiome contributions to disease risk

Gastrointestinal disorders and intestinal bacteria: Advances in research and applications in therapy

Intestinal bacteria coexist with humans and play a role in suppressing the invasion of pathogens, producing short-chain fatty acids, producing vitamins, and controlling the immune system. Studies have been carried out on culturable bacterial species using bacterial culture methods for many years. However, as metagenomic analysis of bacterial genes has been developed since the 1990s, it has recently revealed that many bacteria in the intestine cannot be cultured and that approximately 1,000 species and 40 trillion bacteria are present in the gut microbiota. Furthermore, the composition of the microbiota is different in each disease state compared with the healthy state, and dysbiosis has received much attention as a cause of various diseases. Regarding gastrointestinal diseases, dysbiosis has been reported to be involved in inflammatory bowel disease, irritable bowel syndrome, and non-alcoholic steatohepatitis. Recent findings have also suggested that dysbiosis is involved in colon cancer, liver cancer, pancreatic cancer, esophageal cancer, and so on. This review focuses on the relationship between the gut microbiota and gastrointestinal/hepatobiliary diseases and also discusses new therapies targeting the gut microbiota.

How longitudinal data can contribute to our understanding of host genetic effects on the gut microbiome

A key component of microbiome research is understanding the role of host genetic influence on gut microbial composition. However, it can be difficult to link host genetics with gut microbial composition because host genetic similarity and environmental similarity are often correlated. Longitudinal microbiome data can supplement our understanding of the relative role of genetic processes in the microbiome. These data can reveal environmentally contingent host genetic effects, both in terms of controlling for environmental differences and in comparing how genetic effects differ by environment. Here, we explore four research areas where longitudinal data could lend new insights into host genetic effects on the microbiome: microbial heritability, microbial plasticity, microbial stability, and host and microbiome population genetics. We conclude with a discussion of methodological considerations for future studies.

Dysbiosis of the duodenal microbiota as a diagnostic marker for pancreaticobiliary cancer

BACKGROUND

Pancreaticobiliary cancer (PB Ca) is a lethal disease, and a useful diagnostic marker is urgently needed. A correlation between the human microbiota and malignant gastrointestinal diseases was recently reported.

AIM

To investigate the efficacy of the duodenal microbiota for diagnosing PB Ca.

METHODS

We recruited 22 patients with benign pancreaticobiliary diseases (benign group) and 12 patients with PB Ca (malignant group). The duodenal microbiota of each patient was analyzed by the 16S rDNA terminal restriction fragment length polymorphism method. Patient characteristics, tumor markers, and relative abundances of the duodenal microbiota were compared between the benign and malignant groups.

RESULTS

Cancer antigen 19-9 (CA19-9), Bifidobacterium, Clostridium cluster XVIII, and Prevotella levels differed significantly between the benign and malignant groups. Clostridium cluster XVIII had the greatest area under the receiver operating characteristic curve (AUC) among the four factors with respect to diagnosing PB Ca (cutoff value: 3.038%; sensitivity: 58.3%; specificity: 95.2%; AUC: 0.81). The combination of Clostridium cluster XVIII (cutoff value: 3.038%) and CA19-9 Levels (cutoff value: 18.8 U/mL) showed 91.7% sensitivity and 71.4% specificity for diagnosing PB Ca.

CONCLUSION

The duodenal microbiota may be useful for PB Ca screening.

Combinatorial Effects of Soluble, Insoluble, and Organic Extracts from Jerusalem Artichokes on Gut Microbiota in Mice

Jerusalem artichokes contain high amounts of inulin, which is a prebiotic that supports digestive health, as well as a variety of insoluble fibers and caffeoylquinic acid. The individual impact of these components on gut microbiota is well known; however, the combinatorial effects are less clear. In this investigation, we fractionated Jerusalem artichokes into three parts (water-soluble extract, insoluble extract, and organic extract) and powdered them. Mice were fed a high-fat diet that included one or more of these extracts for 10 days, and then their cecal pH, cecal short-chain fatty acids (SCFAs), and fecal microbiota were evaluated. The combination of the water-soluble and organic extract decreased cecal pH and increased the concentration of SCFAs and led to dynamic changes in the composition of the gut microbiota. These results demonstrate that both the water-soluble and organic extracts in Jerusalem artichokes are bioactive substances that are capable of changing SCFA production and the composition of gut microbiota. Powdered Jerusalem artichokes, rather than inulin supplements, may be superior for promoting a healthy gut.

Mice Microbiota Composition Changes by Inulin Feeding with a Long Fasting Period under a Two-Meals-Per-Day Schedule

Water-soluble dietary fiber is known to modulate fecal microbiota. Although there are a few reports investigating the effects of fiber intake timing on metabolism, there are none on the effect of intake timing on microbiota. Therefore, in this study, we examined the timing effects of inulin-containing food on fecal microbiota. Mice were housed under conditions with a two-meals-per-day schedule, with a long fasting period in the morning and a short fasting period in the evening. Then, 10-14 days after inulin intake, cecal content and feces were collected, and cecal pH and short-chain fatty acids (SCFAs) were measured. The microbiome was determined using 16S rDNA sequencing. Inulin feeding in the morning rather than the evening decreased the cecal pH, increased SCFAs, and changed the microbiome composition. These data suggest that inulin is more easily digested by fecal microbiota during the active period than the inactive period. Furthermore, to confirm the effect of fasting length, mice were housed under a one-meal-per-day schedule. When the duration of fasting was equal, the difference between morning and evening nearly disappeared. Thus, our study demonstrates that consuming inulin at breakfast, which is generally after a longer fasting period, has a greater effect on the microbiota.

Primate microbiomes over time: Longitudinal answers to standing questions in microbiome research

To date, most insights into the processes shaping vertebrate gut microbiomes have emerged from studies with cross-sectional designs. While this approach has been valuable, emerging time series analyses on vertebrate gut microbiomes show that gut microbial composition can change rapidly from 1 day to the next, with consequences for host physical functioning, health, and fitness. Hence, the next frontier of microbiome research will require longitudinal perspectives. Here we argue that primatologists, with their traditional focus on tracking the lives of individual animals and familiarity with longitudinal fecal sampling, are well positioned to conduct research at the forefront of gut microbiome dynamics. We begin by reviewing some of the most important ecological processes governing microbiome change over time, and briefly summarizing statistical challenges and approaches to microbiome time series analysis. We then introduce five questions of general interest to microbiome science where we think field-based primate studies are especially well positioned to fill major gaps: (a) Do early life events shape gut microbiome composition in adulthood? (b) Do shifting social landscapes cause gut microbial change? (c) Are gut microbiome phenotypes heritable across variable environments? (d) Does the gut microbiome show signs of host aging? And (e) do gut microbiome composition and dynamics predict host health and fitness? For all of these questions, we highlight areas where primatologists are uniquely positioned to make substantial contributions. We review preliminary evidence, discuss possible study designs, and suggest future directions.

Prospective evaluation of antibody response to Streptococcus gallolyticus and risk of colorectal cancer

The gut microbiome is increasingly implicated in colorectal cancer (CRC) development. A subgroup of patients diagnosed with CRC show high antibody responses to Streptococcus gallolyticus subspecies gallolyticus (SGG). However, it is unclear whether the association is also present pre-diagnostically. We assessed the association of antibody responses to SGG proteins in pre-diagnostic serum samples with CRC risk in a case-control study nested within a prospective cohort. Pre-diagnostic serum samples from 485 first incident CRC cases (mean time between blood draw and diagnosis 3.4 years) and 485 matched controls in the European Prospective Investigation into Nutrition and Cancer (EPIC) study were analyzed for antibody responses to 11 SGG proteins using multiplex serology. Odds ratios (OR) and 95% confidence intervals (CI) were estimated using multivariable conditional logistic regression models. Antibody positivity for any of the 11 SGG proteins was significantly associated with CRC risk with 56% positive controls compared to 63% positive cases (OR: 1.36, 95% CI: 1.04-1.77). Positivity for two or more proteins of a previously identified SGG 6-marker panel with greater CRC-specificity was also observed among 9% of controls compared to 17% of CRC cases, corresponding to a significantly increased CRC risk (OR: 2.17, 95% CI: 1.44-3.27). In this prospective nested case-control study, we observed a positive association between antibody responses to SGG and CRC development in serum samples taken before evident disease onset. Further work is required to establish the possibly etiological significance of these observations and whether SGG serology may be applicable for CRC risk stratification.

Comparison of Collection Methods for Fecal Samples for Discovery Metabolomics in Epidemiologic Studies

BACKGROUND

The gut metabolome may be associated with the incidence and progression of numerous diseases. The composition of the gut metabolome can be captured by measuring metabolite levels in the feces. However, there are little data describing the effect of fecal sample collection methods on metabolomic measures.

METHODS

We collected fecal samples from 18 volunteers using four methods: no solution, 95% ethanol, fecal occult blood test (FOBT) cards, and fecal immunochemical test (FIT). One set of samples was frozen after collection (day 0), and for 95% ethanol, FOBT, and FIT, a second set was frozen after 96 hours at room temperature. We evaluated (i) technical reproducibility within sample replicates, (ii) stability after 96 hours at room temperature for 95% ethanol, FOBT, and FIT, and (iii) concordance of metabolite measures with the putative "gold standard," day 0 samples without solution.

RESULTS

Intraclass correlation coefficients (ICC) estimating technical reproducibility were high for replicate samples for each collection method. ICCs estimating stability at room temperature were high for 95% ethanol and FOBT (median ICC > 0.87) but not FIT (median ICC = 0.52). Similarly, Spearman correlation coefficients (rs) estimating metabolite concordance with the "gold standard" were higher for 95% ethanol (median rs = 0.82) and FOBT (median rs = 0.70) than for FIT (median rs = 0.40).

CONCLUSIONS

Metabolomic measurements appear reproducible and stable in fecal samples collected with 95% ethanol or FOBT. Concordance with the "gold standard" is highest with 95% ethanol and acceptable with FOBT.

IMPACT

Future epidemiologic studies should collect feces using 95% ethanol or FOBT if interested in studying fecal metabolomics. Cancer Epidemiol Biomarkers Prev; 25(11); 1483-90. ©2016 AACR.

Fecal Microbiota, Fecal Metabolome, and Colorectal Cancer Interrelations

Background and Aims

Investigation of microbe-metabolite relationships in the gut is needed to understand and potentially reduce colorectal cancer (CRC) risk.

Methods

Microbiota and metabolomics profiling were performed on lyophilized feces from 42 CRC cases and 89 matched controls. Multivariable logistic regression was used to identify statistically independent associations with CRC. First principal coordinate-component pair (PCo1-PC1) and false discovery rate (0.05)-corrected P-values were calculated for 116,000 Pearson correlations between 530 metabolites and 220 microbes in a sex*case/control meta-analysis.

Results

Overall microbe-metabolite PCo1-PC1 was more strongly correlated in cases than in controls (Rho 0.606 vs 0.201, P = 0.01). CRC was independently associated with lower levels of Clostridia, Lachnospiraceae, p-aminobenzoate and conjugated linoleate, and with higher levels of Fusobacterium, Porphyromonas, p-hydroxy-benzaldehyde, and palmitoyl-sphingomyelin. Through postulated effects on cell shedding (palmitoyl-sphingomyelin), inflammation (conjugated linoleate), and innate immunity (p-aminobenzoate), metabolites mediated the CRC association with Fusobacterium and Porphyromonas by 29% and 34%, respectively. Overall, palmitoyl-sphingomyelin correlated directly with abundances of Enterobacteriaceae (Gammaproteobacteria), three Actinobacteria and five Firmicutes. Only Parabacteroides correlated inversely with palmitoyl-sphingomyelin. Other lipids correlated inversely with Alcaligenaceae (Betaproteobacteria). Six Bonferroni-significant correlations were found, including low indolepropionate and threnoylvaline with Actinobacteria and high erythronate and an uncharacterized metabolite with Enterobacteriaceae.

Conclusions

Feces from CRC cases had very strong microbe-metabolite correlations that were predominated by Enterobacteriaceae and Actinobacteria. Metabolites mediated a direct CRC association with Fusobacterium and Porphyromonas, but not an inverse association with Clostridia and Lachnospiraceae. This study identifies complex microbe-metabolite networks that may provide insights on neoplasia and targets for intervention.