Potential of fecal microbiota for early-stage detection of colorectal cancer

A reliable method for colorectal cancer prediction based on feature selection and support vector machine

Colorectal cancer (CRC) is a common cancer responsible for approximately 600,000 deaths per year worldwide. Thus, it is very important to find the related factors and detect the cancer accurately. However, timely and accurate prediction of the disease is challenging. In this study, we build an integrated model based on logistic regression (LR) and support vector machine (SVM) to classify the CRC into cancer and normal samples. From various factors, human location, age, gender, BMI, and cancer tumor type, tumor grade, and DNA, of the cancer, we select the most significant factors (p < 0.05) using logistic regression as main features, and with these features, a grid-search SVM model is designed using different kernel types (Linear, radial basis function (RBF), Sigmoid, and Polynomial). The result of the logistic regression indicates that the Firmicutes (AUC 0.918), Bacteroidetes (AUC 0.856), body mass index (BMI) (AUC 0.777), and age (AUC 0.710) and their combined factors (AUC 0.942) are effective for CRC detection. And the best kernel type is RBF, which achieves an accuracy of 90.1% when k = 5, and 91.2% when k = 10. This study provides a new method for colorectal cancer prediction based on independent risky factors. Graphical abstract Flow chart depicting the method adopted in the study. LR (logistic regression) and ROC curve are used to select independent features as input of SVM. SVM kernel selection aims to find the best kernel function for classification by comparing Linear, RBF, Sigmoid, and Polynomial kernel types of SVM, and the result shows the best kernel is RBF. Classification performance of LR + RF, LR + NB, LR + KNN, and LR + ANNs models are compared with LR + SVM. After these steps, the cancer and healthy individuals can be classified, and the best model is selected.

The prevalence and transcriptional activity of the mucosal microbiota of ulcerative colitis patients

Active microbes likely have larger impact on gut health status compared to inactive or dormant microbes. We investigate the composition of active and total mucosal microbiota of treatment-naïve ulcerative colitis (UC) patients to determine the microbial picture at the start-up phase of disease, using both a 16S rRNA transcript and gene amplicon sequencing. DNA and RNA were isolated from the same mucosal colonic biopsies. Our aim was to identify active microbial members of the microbiota in early stages of disease and reveal which members are present, but do not act as major players. We demonstrated differences in active and total microbiota of UC patients when comparing inflamed to non-inflamed tissue. Several taxa, among them the Proteobacteria phyla and families therein, revealed lower transcriptional activity despite a high presence. The Bifidobacteriaceae family of the Actinobacteria phylum showed lower abundance in the active microbiota, although no difference in presence was detected. The most abundant microbiota members of the inflamed tissue in UC patients were not the most active. Knowledge of active members of microbiota in UC patients could enhance our understanding of disease etiology. The active microbial community composition did not deviate from the total when comparing UC patients to non-IBD controls.

Diagnostic Potential and Interactive Dynamics of the Colorectal Cancer Virome

Colorectal cancer is a leading cause of cancer-related death in the United States and worldwide. Its risk and severity have been linked to colonic bacterial community composition. Although human-specific viruses have been linked to other cancers and diseases, little is known about colorectal cancer virus communities. We addressed this knowledge gap by identifying differences in colonic virus communities in the stool of colorectal cancer patients and how they compared to bacterial community differences. The results suggested an indirect role for the virome in impacting colorectal cancer by modulating the associated bacterial community. These findings both support the idea of a biological role for viruses in colorectal cancer and provide a new understanding of basic colorectal cancer etiology.

Human viruses (those that infect human cells) have been associated with many cancers, largely due to their mutagenic and functionally manipulative abilities. Despite this, cancer microbiome studies have focused almost exclusively on bacteria instead of viruses. We began evaluating the cancer virome by focusing on colorectal cancer, a primary cause of morbidity and mortality throughout the world and a cancer linked to altered colonic bacterial community compositions but with an unknown association with the gut virome. We used 16S rRNA gene, whole shotgun metagenomic, and purified virus metagenomic sequencing of stool to evaluate the differences in human colorectal cancer virus and bacterial community composition. Through random forest modeling, we identified differences in the healthy and colorectal cancer viromes. The cancer-associated virome consisted primarily of temperate bacteriophages that were also predicted to be bacterium-virus community network hubs. These results provide foundational evidence that bacteriophage communities are associated with colorectal cancer and potentially impact cancer progression by altering the bacterial host communities.

A Pilot Study: Changes of Gut Microbiota in Post-surgery Colorectal Cancer Patients

Colorectal cancer (CRC) is a growing health problem throughout the world. Strong evidences have supported that gut microbiota can influence tumorigenesis; however, little is known about what happens to gut microbiota following surgical resection. Here, we examined the changes of gut microbiota in CRC patients after the surgical resection. Using the PCoA analysis and dissimilarity tests, the microbial taxonomic compositions and diversities of gut microbiota in post-surgery CRC patients (A1) were significantly different from those in pre-surgery CRC patients (A0) and healthy individuals (H). Compared with A0 and H, the Shannon diversity and Simpson diversity were significantly decreased in A1 (P < 0.05). Based on the LEfSe analysis, the relative abundance of phylum Proteobacteria in A1 was significantly increased than that in A0 and H. The genus Klebsiella in A1 had higher proportions than that in A0 (P < 0.05). Individual variation was distinct; however, 90% of CRC patients in A1 had more abundances of Klebsiella than A0. The Klebsiella in A1 was significantly associated with infectious diseases (P < 0.05), revealed by the correlation analysis between differentiated genera and metabolic pathway. The Klebsiella (Proteobacteria, Gammaproteobacteria, Enterobacteriales, Enterobacteriaceae) in A1 was significantly linked with lymphatic invasion (P < 0.05). Furthermore, the PCA of KEGG pathways indicated that gut microbiota with a more scattered distribution in A1 was noticeably different from that in A0 and H. The nodes, the links, and the kinds of phylum in each module in A1 were less than those in A0 and H, indicating that gut microbiota in A1 had a relatively looser ecologcial interaction network. To sum up, this pilot study identified the changes of gut microbiota in post-surgery CRC patients, and highlights future avenues in which the gut microbiota is likely to be of increasing importance in the care of surgical patients.

Applying simple linear combination, multiple logistic and factor analysis methods for candidate fecal bacteria as novel biomarkers for early detection of adenomatous polyps and colon cancer

BACKGROUND

Colorectal cancer (CRC) is the third leading cause of cancer, and presents a considerable disease burden, worldwide. Recently, the gut microbiota has been proposed as a potential risk factor for CRC, and even adenomatous polyps (AP). Here, the aim of this study was to investigate the role of selected gut bacteria as fecal bacterial biomarkers, in early detection of CRC and AP.

MATERIAL AND METHODS

Fecal samples (n = 93) were collected from Taleghani Hospital, Tehran, Iran, between 2015 and 2017, from normal controls (NC), AP cases and CRC stage I patients, who were undergoing screening for colonoscopy. Absolute quantitative real time PCR (qPCR) assays were established for the quantification of bacterial marker candidates, in all cases and control groups. In order to evaluate the diagnostic value of bacterial candidates in distinguishing CRC from a polyp, receiver operating characteristic curve (ROC) was performed. Multiple logistic regressions were used to find the best combinations of the bacterial candidates, then, combinations were analyzed based on three methods, including linear combination, multiple logistic and factor analysis models.

RESULTS

According to the logistic model, combination of Fusobacterium nucleatum, Enterococcus feacalis, Streptococcus bovis, Enterotoxigenic Bacteroides fragilis (ETBF) and Porphyromonas spp. showed improved diagnostic performance, compared to each bacterium alone, as area under the receiver operating characteristic (AUROC) increases to 0.97, with 95% confidence interval. It was found that a simple linear combination was an appropriate model for discriminating AP and CRC cases, compared to the NC, with a sensitivity of 91.4% and specificity of 93.5%.

CONCLUSION

Our results indicated that based on fecal bacterial candidates, statistical simple linear combination model and ROC curve analysis, early detection of AP and CRC might be possible.

Re-purposing 16S rRNA gene sequence data from within case paired tumor biopsy and tumor-adjacent biopsy or fecal samples to identify microbial markers for colorectal cancer

Microbes colonizing colorectal cancer (CRC) tumors have the potential to affect disease, and vice-versa. The manner in which they differ from microbes in physically adjacent tissue or stool within the case in terms of both, taxonomy and biological activity remains unclear. In this study, we systematically analyzed previously published 16S rRNA sequence data from CRC patients with matched tumor:tumor-adjacent biopsies (n = 294 pairs, n = 588 biospecimens) and matched tumor biopsy:fecal pairs (n = 42 pairs, n = 84 biospecimens). Procrustes analyses, random effects regression, random forest (RF) modeling, and inferred functional pathway analyses were conducted to assess community similarity and microbial diversity across heterogeneous patient groups and studies. Our results corroborate previously reported association of increased Fusobacterium with tumor biopsies. Parvimonas and Streptococcus abundances were also elevated while Faecalibacterium and Ruminococcaceae abundances decreased in tumors relative to tumor-adjacent biopsies and stool samples from the same case. With the exception of these limited taxa, the majority of findings from individual studies were not confirmed by other 16S rRNA gene-based datasets. RF models comparing tumor and tumor-adjacent specimens yielded an area under curve (AUC) of 64.3%, and models of tumor biopsies versus fecal specimens exhibited an AUC of 82.5%. Although some taxa were shared between fecal and tumor samples, their relative abundances varied substantially. Inferred functional analysis identified potential differences in branched amino acid and lipid metabolism. Microbial markers that reliably occur in tumor tissue can have implications for microbiome based and microbiome targeting therapeutics for CRC.

Evaluating gut microbiota profiles from archived fecal samples

BACKGROUND

Associations between colorectal cancer and microbiota have been identified. Archived fecal samples might be valuable sample sources for investigating causality in carcinogenesis and biomarkers discovery due to the potential of performing longitudinal studies. However, the quality, quantity and stability of the gut microbiota in these fecal samples must be assessed prior to such studies. We evaluated i) cross-contamination during analysis for fecal blood and ii) evaporation in stored perforated fecal immunochemical tests (iFOBT) samples, iii) temperature stability as well as iv) comparison of the gut microbiota diversity and composition in archived, iFOBT and fresh fecal samples in order to assess feasibility of large scale microbiota studies.

METHODS

The microbiota profiles were obtained by sequencing the V3-V4 region of 16S rDNA gene.

RESULTS

The iFOBT does not introduce any cross-sample contamination detectable by qPCR. Neither could we detect evaporation during freeze-thaw cycle of perforated iFOBT samples. Our results confirm room temperature stability of the gut microbiome. Diverse microbial profiles were achieved in 100% of fresh, 81% of long-term archived and 96% of iFOBT samples. Microbial diversity and composition were comparable between fresh and iFOBT samples, however, diversity differed significantly between long-term archived, fresh and iFOBT samples.

CONCLUSION

Our data showed that it is feasible to exploit archived fecal sample sets originally collected for testing of fecal blood. The advantages of using these sample sets for microbial biomarker discovery and longitudinal observational studies are the availability of high-quality diagnostic and follow-up data. However, care must be taken when microbiota are profiled in long-term archived fecal samples.

Knomics-Biota - a system for exploratory analysis of human gut microbiota data

Background

Metagenomic surveys of human microbiota are becoming increasingly widespread in academic research as well as in food and pharmaceutical industries and clinical context. Intuitive tools for investigating experimental data are of high interest to researchers.

Results

Knomics-Biota is a web-based resource for exploratory analysis of human gut metagenomes. Users can generate and share analytical reports corresponding to common experimental schemes (like case-control study or paired comparison). Interactive visualizations and statistical analysis are provided in association with the external factors and in the context of thousands of publicly available datasets arranged into thematic collections. The web-service is available at https://biota.knomics.ru.

Conclusions

Knomics-Biota web service is a comprehensive tool for interactive metagenomic data analysis.

Electronic supplementary material

The online version of this article (10.1186/s13040-018-0187-3) contains supplementary material, which is available to authorized users.

Activated ATF6 Induces Intestinal Dysbiosis and Innate Immune Response to Promote Colorectal Tumorigenesis

BACKGROUND & AIMS

Activating transcription factor 6 (ATF6) regulates endoplasmic reticulum stress. We studied whether ATF6 contributes to the development of colorectal cancer (CRC) using tissue from patients and transgenic mice.

METHODS

We analyzed data from 541 patients with CRC in The Cancer Genome Atlas database for genetic variants and aberrant expression levels of unfolded protein response genes. Findings were validated in a cohort of 83 patients with CRC in Germany. We generated mice with intestinal epithelial cell-specific expression of the active form of Atf6 (nATF6IEC) from 2 alleles (homozygous), mice with expression of nATF6IEC from 1 allele (heterozygous), and nATF6IECfl/fl mice (controls). All nATF6IEC mice were housed under either specific-pathogen-free or germ-free conditions. Cecal microbiota from homozygous nATF6IEC mice or control mice was transferred into homozygous nATF6IEC mice or control mice. nATF6IEC mice were crossed with mice with disruptions in the myeloid differentiation primary response gene 88 and toll-like receptor adaptor molecule 1 gene (Myd88/Trif-knockout mice). Intestinal tissues were collected from mice and analyzed by histology, immunohistochemistry, immunoblots, gene expression profiling of unfolded protein response and inflammatory genes, array-based comparative genome hybridization, and 16S ribosomal RNA gene sequencing.

RESULTS

Increased expression of ATF6 was associated with reduced disease-free survival times of patients with CRC. Homozygous nATF6IEC mice developed spontaneous colon adenomas at 12 weeks of age. Compared with controls, homozygous nATF6IEC mice had changes in the profile of their cecal microbiota, increased proliferation of intestinal epithelial cells, and loss of the mucus barrier-all preceding tumor formation. These mice had increased penetration of bacteria into the inner mucus layer and activation of signal transducer and activator of transcription 3, yet inflammation was not observed at the pretumor or tumor stages. Administration of antibiotics to homozygous nATF6IEC mice greatly reduced tumor incidence, and germ-free housing completely prevented tumorigenesis. Analysis of nATF6IEC MyD88/TRIF-knockout mice showed that tumor initiation and growth required MyD88/TRIF-dependent activation of signal transducer and activator of transcription 3. Transplantation of cecal microbiota from nATF6IEC mice and control mice, collected before tumor formation, caused tumor formation in ex-germ-free nATF6IEC mice.

CONCLUSIONS

In patients with CRC, ATF6 was associated with reduced time of disease-free survival. In studies of nATF6IEC mice, we found sustained intestinal activation of ATF6 in the colon to promote dysbiosis and microbiota-dependent tumorigenesis.

Ecologically informed microbial biomarkers and accurate classification of mixed and unmixed samples in an extensive cross-study of human body sites

BACKGROUND

The identification of body site-specific microbial biomarkers and their use for classification tasks have promising applications in medicine, microbial ecology, and forensics. Previous studies have characterized site-specific microbiota and shown that sample origin can be accurately predicted by microbial content. However, these studies were usually restricted to single datasets with consistent experimental methods and conditions, as well as comparatively small sample numbers. The effects of study-specific biases and statistical power on classification performance and biomarker identification thus remain poorly understood. Furthermore, reliable detection in mixtures of different body sites or with noise from environmental contamination has rarely been investigated thus far. Finally, the impact of ecological associations between microbes on biomarker discovery was usually not considered in previous work.

RESULTS

Here we present the analysis of one of the largest cross-study sequencing datasets of microbial communities from human body sites (15,082 samples from 57 publicly available studies). We show that training a Random Forest Classifier on this aggregated dataset increases prediction performance for body sites by 35% compared to a single-study classifier. Using simulated datasets, we further demonstrate that the source of different microbial contributions in mixtures of different body sites or with soil can be detected starting at 1% of the total microbial community. We apply a biomarker selection method that excludes indirect environmental associations driven by microbe-microbe associations, yielding a parsimonious set of highly predictive taxa including novel biomarkers and excluding many previously reported taxa. We find a considerable fraction of unclassified biomarkers ("microbial dark matter") and observe that negatively associated taxa have a surprisingly high impact on classification performance. We further detect a significant enrichment of rod-shaped, motile, and sporulating taxa for feces biomarkers, consistent with a highly competitive environment.

CONCLUSIONS

Our machine learning model shows strong body site classification performance, both in single-source samples and mixtures, making it promising for tasks requiring high accuracy, such as forensic applications. We report a core set of ecologically informed biomarkers, inferred across a wide range of experimental protocols and conditions, providing the most concise, general, and least biased overview of body site-associated microbes to date.

Pathogenic functions of host microbiota

BACKGROUND

It is becoming evident that certain features of human microbiota, encoded by distinct autochthonous taxa, promote disease. As a result, borders between the so-called opportunistic pathogens, pathobionts, and commensals are increasingly blurred, and specific targets for manipulating microbiota to improve host health are becoming elusive.

RESULTS

In this study, we focus on the functions of host bacterial communities that have the potential to cause disease, proposing the term "pathogenic function (pathofunction)". The concept is presented via three distinct examples, namely, the formation of (i) trimethylamine, (ii) secondary bile acids, and (iii) hydrogen sulfide, which represent metabolites of the gut microbiota linked to the development of non-communicable diseases. Using publicly available metagenomic and metatranscriptomic data (n = 2975), we quantified those pathofunctions in health and disease and exposed the key players. Pathofunctions were ubiquitously present with increased abundances in patient groups. Overall, the three pathofunctions were detected at low mean concentrations (< 1% of total bacteria carried respective genes) and encompassed various taxa, including uncultured members.

CONCLUSIONS

We outline how this function-centric approach, where all members of a community exhibiting a particular pathofunction are redundant, can contribute to risk assessment and the development of precision treatment directing gut microbiota to increase host health.

Intestinal microorganisms involved in colorectal cancer complicated with dyslipidosis

BACKGROUND

Abnormal lipid metabolism is considered to be one of main promoters of colorectal cancer (CRC), and intestinal microorganisms may be involved in CRC in patients with abnormal lipid metabolism.

OBJECTIVE

To investigate lipid metabolism in CRC patients and explore the role of intestinal microorganisms in CRC complicated with abnormal lipid metabolism.

METHODS

Overall, 150 CRC patients in Huzhou Central Hospital from January 2016 to September 2017 were recruited in the present study. Basic patient information and clinical serological indicators were investigated and analyzed. Twenty-one stool samples were collected from patients after receiving informed consent. Next-generation sequencing technology was used to sequence bacterial 16S ribosomal RNA. Bioinformatics analysis was used to profile the microbial composition and screen distinctive bacteria in patients with CRC complicated with abnormal lipid metabolism.

RESULTS

Apo B and FFA levels were higher in patients with stage I disease than in patients with other stages. HDL, LDL, Apo B and FFA levels were higher in female patients than in male patients. FFA level was higher in rectal cancer patients than in colon cancer patients. These differences were statistically significant (p < 0.05). The proportion of Escherichia/Shigella was increased in CRC patients with hyperlipoidaemia and hypercholesteremia; the abundance of Streptococcus was increased in CRC patients with hyperlipoidaemia; the abundance of Clostridium XIVa was reduced in CRC patients with hyperlipoidaemia and hypercholesteremia; and the abundance of Ruminococcaceae was reduced in CRC patients with hypercholesteremia. Bilophila and Butyricicoccus were closely related to CRC patients without hyperlipoidaemia or hypercholesteremia, and Selenomonas, Clostridium, Bacteroidetes Slackia, Burkholderiales and Veillonellaceae were closely related to CRC patients with hyperlipoidaemia. Some pathways, including secretion system, chaperones and folding catalysts, amino sugar and nucleotide sugar metabolism, arginine and proline metabolism, glycine, serine and threonine metabolism, histidine metabolism, pores and ion channels, nitrogen metabolism and sporulation, may be involved in lipid metabolism abnormality in CRC patients.

CONCLUSIONS

Many CRC patients have abnormal lipid metabolism, and the intestinal microbiota is altered in these CRC patients.

Grow With the Challenge - Microbial Effects on Epithelial Proliferation, Carcinogenesis, and Cancer Therapy

The eukaryotic host is in close contact to myriads of resident and transient microbes, which influence the crucial physiological pathways. Emerging evidence points to their role of host-microbe interactions for controlling tissue homeostasis, cell fate decisions, and regenerative capacity in epithelial barrier organs including the skin, lung, and gut. In humans and mice, it has been shown that the malignant tumors of these organs harbor an altered microbiota. Mechanistic studies have shown that the altered metabolic properties and secreted factors contribute to epithelial carcinogenesis and tumor progression. Exciting recent work points toward a crucial influence of the associated microbial communities on the response to chemotherapy and immune-check point inhibitors during cancer treatment, which suggests that the modulation of the microbiota might be a powerful tool for personalized oncology. In this article, we provide an overview of how the bacterial signals and signatures may influence epithelial homeostasis across taxa from cnidarians to vertebrates and delineate mechanisms, which might be potential targets for therapy of human diseases by either harnessing barrier integrity (infection and inflammation) or restoring uncontrolled proliferation (cancer).

Metabolite quantification of faecal extracts from colorectal cancer patients and healthy controls

Colorectal cancer (CRC), a primary cause of morbidity and mortality worldwide is expected to rise in the coming years. A better understanding of the metabolic changes taking place during the disease progression is needed for effective improvements of screening strategies and treatments. In the present study, Nuclear Magnetic Resonance (NMR) metabolomics was used to quantify the absolute concentrations of metabolites in faecal extracts from two cohorts of CRC patients and healthy controls. The quantification of over 80 compounds revealed that patients with CRC had increased faecal concentrations of branched chain fatty acids (BCFA), isovalerate and isobutyrate plus valerate and phenylacetate but diminished concentrations of amino acids, sugars, methanol and bile acids (deoxycholate, lithodeoxycholate and cholate). These results suggest that alterations in microbial activity and composition could have triggered an increase in utilisation of host intestinal slough cells and mucins and led to an increase in BCFA, valerate and phenylacetate. Concurrently, a general reduction in the microbial metabolic function may have led to reduced levels of other components (amino acids, sugars and bile acids) normally produced under healthy conditions. This study provides a thorough listing of the most abundant compounds found in human faecal waters and presents a template for absolute quantification of metabolites. The production of BCFA and phenylacetate in colonic carcinogenesis warrants further investigations.

The implementation of omics technologies in cancer microbiome research

Whilst the interplay between host genetics and the environment plays a pivotal role in the aetiopathogenesis of cancer, there are other key contributors of importance as well. One such factor of central and growing interest is the contribution of the microbiota to cancer. Even though the field is only a few years old, investigation of the 'cancer microbiome' has already led to major advances in knowledge of the basic biology of cancer risk and progression, opened novel avenues for biomarkers and diagnostics, and given a better understanding of mechanisms underlying response to therapy. Recent developments in microbial DNA sequencing techniques (and the bioinformatics required for analysis of these datasets) have allowed much more in-depth profiling of the structure of microbial communities than was previously possible. However, for more complete assessment of the functional implications of microbial changes, there is a growing recognition of the importance of the integration of microbial profiling with other omics modalities, with metabonomics (metabolite profiling) and proteomics (protein profiling) both gaining particular recent attention. In this review, we give an overview of some of the key scientific techniques being used to unravel the role of the cancer microbiome. We have aimed to highlight practical aspects related to sample collection and preparation, choice of the modality of analysis, and examples of where different omics technologies have been complementary to each other to highlight the significance of the cancer microbiome.

Microbes involving in carcinogenesis; growing state of the art

Lateral gene transfer (LGT) has been demonstrated as a transfer process of novel genes between different species. LGT proceedings are occurring between microbes and plants, as well as between microbes and animals. New evidence demonstrates that bacterial insertional mutagenesis may occur in cancer cells. Due to the important role of genetic changes in the increase of cell proliferation and cancer development, we reviewed the effects of microbial-animal LGT in human oncogenesis. In addition, viral DNA can induce cancer development by random insertion into cancer-related genes or by inducing translocations. In conclusion, growing evidence shows the contribution of the microbial genome in cancer and autoimmune disease.

Changes in gut microbiota and plasma inflammatory factors across the stages of colorectal tumorigenesis: a case-control study

Background

Colorectal cancer (CRC) is a common malignant gastrointestinal tumor. In China, CRC is the 5th most commonly diagnosed cancer. The vast majority of CRC cases are sporadic and evolve with the adenoma-carcinoma sequence. There is mounting evidence indicating that gut microbiota and inflammation play important roles in the development of CRC although study results are not entirely consistent. In the current study, we investigated the changes in the CRC-associated bacteria and plasma inflammatory factors and their relationships based on data from a case-control study of Han Chinese. We included 130 initially diagnosed CRC patients, 88 advanced colorectal adenoma patients (A-CRA), 62 patients with benign intestinal polyps and 130 controls.

Results

Fecal microbiota composition was obtained using 16S ribosomal DNA (16S rDNA) sequencing. PCOA analysis showed structural differences in microbiota among the four study groups (P = 0.001, Unweighted Unifrac). Twenty-four CRC-associated bacteria were selected by a two-step statistical method and significant correlations were observed within these microbes. CRC-associated bacteria were found to change with the degree of malignancy. Plasma C-reactive protein (CRP) and soluble tumor necrosis factor II (sTNFR-II) displayed significant differences among the four study groups and increased with adenoma-carcinoma sequence. The correlations of CRP and sTNFR-II with several CRC-associated microbes were also explored.

Conclusions

CRC-associated species and plasma inflammatory factors tended to change along the adenoma-carcinoma sequence. Several CRC-associated bacteria were correlated with CRP and sTNFR-II. It is likely that gut microbiome and inflammation gradually form a microenvironment that is associated with CRC development.

Electronic supplementary material

The online version of this article (10.1186/s12866-018-1232-6) contains supplementary material, which is available to authorized users.

Breast cancer in postmenopausal women is associated with an altered gut metagenome

BACKGROUND

Increasing evidence suggests that gut microbiota play a role in the pathogenesis of breast cancer. The composition and functional capacity of gut microbiota associated with breast cancer have not been studied systematically.

METHODS

We performed a comprehensive shotgun metagenomic analysis of 18 premenopausal breast cancer patients, 25 premenopausal healthy controls, 44 postmenopausal breast cancer patients, and 46 postmenopausal healthy controls.

RESULTS

Microbial diversity was higher in breast cancer patients than in controls. Relative species abundance in gut microbiota did not differ significantly between premenopausal breast cancer patients and premenopausal controls. In contrast, relative abundance of 45 species differed significantly between postmenopausal patients and postmenopausal controls: 38 species were enriched in postmenopausal patients, including Escherichia coli, Klebsiella sp_1_1_55, Prevotella amnii, Enterococcus gallinarum, Actinomyces sp. HPA0247, Shewanella putrefaciens, and Erwinia amylovora, and 7 species were less abundant in postmenopausal patients, including Eubacterium eligens and Lactobacillus vaginalis. Acinetobacter radioresistens and Enterococcus gallinarum were positively but weakly associated with expression of high-sensitivity C-reactive protein; Shewanella putrefaciens and Erwinia amylovora were positively but weakly associated with estradiol levels. Actinomyces sp. HPA0247 negatively but weakly correlated with CD3⁺CD8⁺ T cell numbers. Further characterization of metagenome functional capacity indicated that the gut metagenomes of postmenopausal breast cancer patients were enriched in genes encoding lipopolysaccharide biosynthesis, iron complex transport system, PTS system, secretion system, and beta-oxidation.

CONCLUSION

The composition and functions of the gut microbial community differ between postmenopausal breast cancer patients and healthy controls. The gut microbiota may regulate or respond to host immunity and metabolic balance. Thus, while cause and effect cannot be determined, there is a reproducible change in the microbiota of treatment-naive patients relative to matched controls.

Alterations in Enteric Virome Are Associated With Colorectal Cancer and Survival Outcomes

BACKGROUND & AIMS

Patients with colorectal cancer (CRC) have a different gut microbiome signature than individuals without CRC. Little is known about the viral component of CRC-associated microbiome. We aimed to identify and validate viral taxonomic markers of CRC that might be used in detection of the disease or predicting outcome.

METHODS

We performed shotgun metagenomic analyses of viromes of fecal samples from 74 patients with CRC (cases) and 92 individuals without CRC (controls) in Hong Kong (discovery cohort). Viral sequences were classified by taxonomic alignment against an integrated microbial reference genome database. Viral markers associated with CRC were validated using fecal samples from 3 separate cohorts: 111 patients with CRC and 112 controls in Hong Kong, 46 patients with CRC and 63 controls in Austria, and 91 patients with CRC and 66 controls in France and Germany. Using abundance profiles of CRC-associated virome genera, we constructed random survival forest models to identify those associated with patient survival times.

RESULTS

The diversity of the gut bacteriophage community was significantly increased in patients with CRC compared with controls. Twenty-two viral taxa discriminated cases from controls with an area under the receiver operating characteristic curve of 0.802 in the discovery cohort. The viral markers were validated in 3 cohorts, with area under the receiver operating characteristic curves of 0.763, 0.736, and 0.715, respectively. Clinical subgroup analysis showed that dysbiosis of the gut virome was associated with early- and late-stage CRC. A combination of 4 taxonomic markers associated with reduced survival of patients with CRC (log-rank test, P = 8.1 × 10^-6) independently of tumor stage, lymph node metastases, or clinical parameters. We found altered interactions between bacteriophages and oral bacterial commensals in fecal samples from patients with CRC compared with controls.

CONCLUSIONS

In a metagenomic analysis of fecal samples from patients and controls, we identified virome signatures associated with CRC. These data might be used to develop tools to identify individuals with CRC or predict outcomes.

The oral microbiota in colorectal cancer is distinctive and predictive

BACKGROUND AND AIMS

Microbiota alterations are linked with colorectal cancer (CRC) and notably higher abundance of putative oral bacteria on colonic tumours. However, it is not known if colonic mucosa-associated taxa are indeed orally derived, if such cases are a distinct subset of patients or if the oral microbiome is generally suitable for screening for CRC.

METHODS

We profiled the microbiota in oral swabs, colonic mucosae and stool from individuals with CRC (99 subjects), colorectal polyps (32) or controls (103).

RESULTS

Several oral taxa were differentially abundant in CRC compared with controls, for example, Streptococcus and Prevotellas pp. A classification model of oral swab microbiota distinguished individuals with CRC or polyps from controls (sensitivity: 53% (CRC)/67% (polyps); specificity: 96%). Combining the data from faecal microbiota and oral swab microbiota increased the sensitivity of this model to 76% (CRC)/88% (polyps). We detected similar bacterial networks in colonic microbiota and oral microbiota datasets comprising putative oral biofilm forming bacteria. While these taxa were more abundant in CRC, core networks between pathogenic, CRC-associated oral bacteria such as Peptostreptococcus, Parvimonas and Fusobacterium were also detected in healthy controls. High abundance of Lachnospiraceae was negatively associated with the colonisation of colonic tissue with oral-like bacterial networks suggesting a protective role for certain microbiota types against CRC, possibly by conferring colonisation resistance to CRC-associated oral taxa and possibly mediated through habitual diet.

CONCLUSION

The heterogeneity of CRC may relate to microbiota types that either predispose or provide resistance to the disease, and profiling the oral microbiome may offer an alternative screen for detecting CRC.

Association Between Bacteremia From Specific Microbes and Subsequent Diagnosis of Colorectal Cancer

BACKGROUND & AIMS

Colorectal cancer (CRC) development has been associated with increased proportions of Bacteroides fragilis and certain Streptococcus, Fusobacterium, and Peptostreptococcus species in the intestinal microbiota. We investigated associations between bacteremia from specific intestinal microbes and occurrence of CRC.

METHODS

We performed a retrospective study after collecting data on 13,096 adult patients (exposed group) in Hong Kong hospitalized with bacteremia (identified by blood culture test) without a previous diagnosis of cancer from January 1, 2006 through December 31, 2015. We collected data on intestinal microbes previously associated with CRC (genera Bacteroides, Clostridium, Filifactor, Fusobacterium, Gemella, Granulicatella, Parvimonas, Peptostreptococcus, Prevotella, Solobacterium, and Streptococcus). Clinical information, including patient demographics, comorbid medical conditions, date of bacteremia, and bacterial species identified, were collected. The incidence of biopsy-proved CRC was compared between the exposed and unexposed (patients without bacteremia matched for age, sex, and comorbidities) groups.

RESULTS

The risk of CRC was increased in patients with bacteremia from B fragilis (hazard ratio [HR] = 3.85, 95% CI = 2.62-5.64, P = 5.5 × 10^-12) or Streptococcus gallolyticus (HR = 5.73, 95% CI = 2.18-15.1, P = 4.1 × 10^-4) compared with the unexposed group. In addition, the risk of CRC was increased in patients with bacteremia from Fusobacterium nucleatum (HR = 6.89, 95% CI = 1.70-27.9, P = .007), Peptostreptococcus species (HR = 3.06, 95% CI = 1.47-6.35, P = .003), Clostridium septicum (HR = 17.1, 95% CI = 1.82-160, P = .013), Clostridium perfringens (HR = 2.29, 95% CI = 1.16-4.52, P = .017), or Gemella morbillorum (HR = 15.2, 95% CI = 1.54-150, P = .020). We observed no increased risk in patients with bacteremia caused by microbes not previously associated with colorectal neoplasms.

CONCLUSIONS

In a retrospective analysis of patients hospitalized for bacteremia, we associated later diagnosis of CRC with B fragilis and S gallolyticus and other intestinal microbes. These bacteria might have entered the bloodstream from intestinal dysbiosis and perturbed barrier function. These findings support a model in which specific members of the intestinal microbiota promote colorectal carcinogenesis. Clinicians should evaluate patients with bacteremia from these species for neoplastic lesions in the colorectum.

Metagenomic analysis of gut microbial communities from a Central Asian population

OBJECTIVE

Changes in the gut microbiota are increasingly recognised to be involved in many diseases. This ecosystem is known to be shaped by many factors, including climate, geography, host nutrition, lifestyle and medication. Thus, knowledge of varying populations with different habits is important for a better understanding of the microbiome.

DESIGN

We therefore conducted a metagenomic analysis of intestinal microbiota from Kazakh donors, recruiting 84 subjects, including male and female healthy subjects and metabolic syndrome (MetS) patients aged 25-75 years, from the Kazakh administrative centre, Astana. We characterise and describe these microbiomes, the first deep-sequencing cohort from Central Asia, in comparison with a global dataset (832 individuals from five countries on three continents), and explore correlations between microbiota, clinical and laboratory parameters as well as with nutritional data from Food Frequency Questionnaires.

RESULTS

We observe that Kazakh microbiomes are relatively different from both European and East Asian counterparts, though similar to other Central Asian microbiomes, with the most striking difference being significantly more samples falling within the Prevotella-rich enterotype, potentially reflecting regional diet and lifestyle. We show that this enterotype designation remains stable within an individual over time in 82% of cases. We further observe gut microbiome features that distinguish MetS patients from controls (eg, significantly reduced Firmicutes to Bacteroidetes ratio, Bifidobacteria and Subdoligranulum, alongside increased Prevotella), though these overlap little with previously published reports and thus may reflect idiosyncrasies of the present cohort.

CONCLUSION

Taken together, this exploratory study describes gut microbiome data from an understudied population, providing a starting point for further comparative work on biogeography and research on widespread diseases.

TRIAL REGISTRATION NUMBER

ISRCTN37346212; Post-results.

Intestinal microbiota, chronic inflammation, and colorectal cancer

In addition to genetic and epigenetic factors, various environmental factors, including diet, play important roles in the development of colorectal cancer (CRC). Recently, there is increasing interest in the intestinal microbiota as an environmental risk factor for CRC, because diet also influences the composition of the intestinal microbiota. The human intestinal microbiota comprises about 100 trillion microbes. This microbiome thrives on undigested dietary residues in the intestinal lumen and produces various metabolites. It is well known that the dietary risk factors for CRC are mediated by dysbiosis of the intestinal microbiota and their metabolites. In this review, we describe the bacterial taxa associated with CRC, including Fusobacterium nucleatum, enterotoxigenic Bacteroides fragilis, Escherichia coli, and butyrate-producing bacteria. We also discuss the host-diet interaction in colorectal carcinogenesis.

Mother-to-Infant Microbial Transmission from Different Body Sites Shapes the Developing Infant Gut Microbiome

The acquisition and development of the infant microbiome are key to establishing a healthy host-microbiome symbiosis. The maternal microbial reservoir is thought to play a crucial role in this process. However, the source and transmission routes of the infant pioneering microbes are poorly understood. To address this, we longitudinally sampled the microbiome of 25 mother-infant pairs across multiple body sites from birth up to 4 months postpartum. Strain-level metagenomic profiling showed a rapid influx of microbes at birth followed by strong selection during the first few days of life. Maternal skin and vaginal strains colonize only transiently, and the infant continues to acquire microbes from distinct maternal sources after birth. Maternal gut strains proved more persistent in the infant gut and ecologically better adapted than those acquired from other sources. Together, these data describe the mother-to-infant microbiome transmission routes that are integral in the development of the infant microbiome.

Thermal proteome profiling in bacteria: probing protein state in vivo

Increasing antibiotic resistance urges for new technologies for studying microbes and antimicrobial mechanism of action. We adapted thermal proteome profiling (TPP) to probe the thermostability of Escherichia coli proteins in vivoE. coli had a more thermostable proteome than human cells, with protein thermostability depending on subcellular location-forming a high-to-low gradient from the cell surface to the cytoplasm. While subunits of protein complexes residing in one compartment melted similarly, protein complexes spanning compartments often had their subunits melting in a location-wise manner. Monitoring the E. coli meltome and proteome at different growth phases captured changes in metabolism. Cells lacking TolC, a component of multiple efflux pumps, exhibited major physiological changes, including differential thermostability and levels of its interaction partners, signaling cascades, and periplasmic quality control. Finally, we combined in vitro and in vivo TPP to identify targets of known antimicrobial drugs and to map their downstream effects. In conclusion, we demonstrate that TPP can be used in bacteria to probe protein complex architecture, metabolic pathways, and intracellular drug target engagement.

Fecal fusobacterium nucleatum for detecting colorectal cancer: a systematic review and meta-analysis

OBJECTIVE

The purpose of this systematic review and meta-analysis was to evaluate the efficacy of fecal Fusobacterium nucleatum ( Fn) for detecting colorectal cancer. It is the first systematic review and meta-analysis to focus exclusively on fecal Fn for colorectal cancer.

MATERIALS AND METHODS

Comprehensive searches of several databases before January 2018 were conducted. Fecal Fn for detecting colorectal cancer was evaluated via pooled sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, diagnostic odds ratio, and area under the curve. Heterogeneity was explored using meta-regression and subgroup analyses. The publication bias and the overall quality of evidence were also analyzed.

RESULTS

Our analysis included six papers containing seven case-control studies in the systematic review and meta-analysis. Overall sensitivity and specificity were 0.68 (95% confidence interval (CI) 0.64, 0.72) and 0.78 (95% CI 0.75, 0.81), respectively. The positive likelihood ratio and negative likelihood ratio in detecting colorectal cancer were 2.87 (95% CI 1.62, 5.10) and 0.40 (95% CI 0.30, 0.54) respectively. The diagnostic odds ratio (OR) was 8.75 (95% CI 4.86, 15.78) and the area under the curve was 0.80. A subgroup analysis showed that in Asia, the colorectal cancer sample size ⩾50 had higher specificity (specificity 0.85, 95% CI 0.80, 0.88). No publication bias existed. The GRADEpro showed a moderate level of the available evidence.

CONCLUSIONS

Compared to other examinations, the fecal Fn test seems a good choice for detecting colorectal cancer. It also has better diagnostic performance in Asians. However, more clinical trials with large sample sizes and strict randomization are needed to further verify the evidence.

Microbiota, Epithelium, Inflammation, and TGF-β Signaling: An Intricate Interaction in Oncogenesis

Microbiota has been widely considered to play a critical role in human carcinogenesis. Recent evidence demonstrated that microbiota, epithelial barrier and inflammation has made up a tightly interdependent triangle during the process of carcinogenesis. Hence, we discussed the triangle relationship of microbiota dysbiosis, epithelial barrier dysfunction and dysregulated immune responses to elucidate the mechanisms by which microbiota induces carcinogenesis, especially highlighting the reciprocal crosstalk between transforming growth factor-β signaling and every side of the tumorigenic triangle. This sophisticated interaction will provide insight into the basic mechanisms of carcinogenesis and may bring new hope to cancer prevention and therapeutic intervention.

Cholecystectomy Damages Aging-Associated Intestinal Microbiota Construction

The intestinal microbiome is essential in humans to maintain physiological balance and nutrition metabolism. Laparoscopic cholecystectomy due to gallstone disease and cholecystitis can cause intestinal microbial dysbiosis, and following bile acid metabolism dysfunction, positions the patient at high risk of colorectal cancer. However, little is known regarding intestinal microbiota characteristics in post-cholecystectomy patients. Here, we compared the microbial composition of cholecystectomy patients with that of a healthy population. We determined that cholecystectomy eliminated aging-associated fecal commensal microbiota and further identified several bile acid metabolism-related bacteria as contributors of colorectal cancer incidence via elevation of secondary bile acids.

Colorectal cancer mutational profiles correlate with defined microbial communities in the tumor microenvironment

Variation in the gut microbiome has been linked to colorectal cancer (CRC), as well as to host genetic variation. However, we do not know whether, in addition to baseline host genetics, somatic mutational profiles in CRC tumors interact with the surrounding tumor microbiome, and if so, whether these changes can be used to understand microbe-host interactions with potential functional biological relevance. Here, we characterized the association between CRC microbial communities and tumor mutations using microbiome profiling and whole-exome sequencing in 44 pairs of tumors and matched normal tissues. We found statistically significant associations between loss-of-function mutations in tumor genes and shifts in the abundances of specific sets of bacterial taxa, suggestive of potential functional interaction. This correlation allows us to statistically predict interactions between loss-of-function tumor mutations in cancer-related genes and pathways, including MAPK and Wnt signaling, solely based on the composition of the microbiome. In conclusion, our study shows that CRC microbiomes are correlated with tumor mutational profiles, pointing towards possible mechanisms of molecular interaction.

Taxonomy-aware feature engineering for microbiome classification

Background

What is a healthy microbiome? The pursuit of this and many related questions, especially in light of the recently recognized microbial component in a wide range of diseases has sparked a surge in metagenomic studies. They are often not simply attributable to a single pathogen but rather are the result of complex ecological processes. Relatedly, the increasing DNA sequencing depth and number of samples in metagenomic case-control studies enabled the applicability of powerful statistical methods, e.g. Machine Learning approaches. For the latter, the feature space is typically shaped by the relative abundances of operational taxonomic units, as determined by cost-effective phylogenetic marker gene profiles. While a substantial body of microbiome/microbiota research involves unsupervised and supervised Machine Learning, very little attention has been put on feature selection and engineering.

Results

We here propose the first algorithm to exploit phylogenetic hierarchy (i.e. an all-encompassing taxonomy) in feature engineering for microbiota classification. The rationale is to exploit the often mono- or oligophyletic distribution of relevant (but hidden) traits by virtue of taxonomic abstraction. The algorithm is embedded in a comprehensive microbiota classification pipeline, which we applied to a diverse range of datasets, distinguishing healthy from diseased microbiota samples.

Conclusion

We demonstrate substantial improvements over the state-of-the-art microbiota classification tools in terms of classification accuracy, regardless of the actual Machine Learning technique while using drastically reduced feature spaces. Moreover, generalized features bear great explanatory value: they provide a concise description of conditions and thus help to provide pathophysiological insights. Indeed, the automatically and reproducibly derived features are consistent with previously published domain expert analyses.

Electronic supplementary material

The online version of this article (10.1186/s12859-018-2205-3) contains supplementary material, which is available to authorized users.

Microbial markers in colorectal cancer detection and/or prognosis

Colorectal cancer (CRC) is the second leading cause of cancer worldwide. CRC is still associated with a poor prognosis among patients with advanced disease. On the contrary, due to its slow progression from detectable precancerous lesions, the prognosis for patients with early stages of CRC is encouraging. While most robust methods are invasive and costly, actual patient-friendly screening methods for CRC suffer of lack of sensitivity and specificity. Therefore, the development of sensitive, non-invasive and cost-effective methods for CRC detection and prognosis are necessary for increasing the chances of a cure. Beyond its beneficial functions for the host, increasing evidence suggests that the intestinal microbiota is a key factor associated with carcinogenesis. Many clinical studies have reported a disruption in the gut microbiota balance and an alteration in the faecal metabolome of CRC patients, suggesting the potential use of a microbial-based test as a non-invasive diagnostic and/or prognostic tool for CRC screening. This review aims to discuss the microbial signatures associated with CRC known to date, including dysbiosis and faecal metabolome alterations, and the potential use of microbial variation markers for non-invasive early diagnosis and/or prognostic assessment of CRC and advanced adenomas. We will finally discuss the possible use of these markers as predicators for treatment response and their limitations.

Leveraging Existing 16S rRNA Gene Surveys To Identify Reproducible Biomarkers in Individuals with Colorectal Tumors

An increasing body of literature suggests that both individual and collections of bacteria are associated with the progression of colorectal cancer. As the number of studies investigating these associations increases and the number of subjects in each study increases, a meta-analysis to identify the associations that are the most predictive of disease progression is warranted. We analyzed previously published 16S rRNA gene sequencing data collected from feces and colon tissue. We quantified the odds ratios (ORs) for individual bacterial taxa that were associated with an individual having tumors relative to a normal colon. Among the fecal samples, there were no taxa that had significant ORs associated with adenoma and there were 8 taxa with significant ORs associated with carcinoma. Similarly, among the tissue samples, there were no taxa that had a significant OR associated with adenoma and there were 3 taxa with significant ORs associated with carcinoma. Among the significant ORs, the association between individual taxa and tumor diagnosis was equal to or below 7.11. Because individual taxa had limited association with tumor diagnosis, we trained Random Forest classification models using only the taxa that had significant ORs, using the entire collection of taxa found in each study, and using operational taxonomic units defined based on a 97% similarity threshold. All training approaches yielded similar classification success as measured using the area under the curve. The ability to correctly classify individuals with adenomas was poor, and the ability to classify individuals with carcinomas was considerably better using sequences from feces or tissue.IMPORTANCE Colorectal cancer is a significant and growing health problem in which animal models and epidemiological data suggest that the colonic microbiota have a role in tumorigenesis. These observations indicate that the colonic microbiota is a reservoir of biomarkers that may improve our ability to detect colonic tumors using noninvasive approaches. This meta-analysis identifies and validates a set of 8 bacterial taxa that can be used within a Random Forest modeling framework to differentiate individuals as having normal colons or carcinomas. When models trained using one data set were tested on other data sets, the models performed well. These results lend support to the use of fecal biomarkers for the detection of tumors. Furthermore, these biomarkers are plausible candidates for further mechanistic studies into the role of the gut microbiota in tumorigenesis.

Green Tea Liquid Consumption Alters the Human Intestinal and Oral Microbiome

SCOPE

GTPs (green tea polyphenols) exert anti-CRC (colorectal cancer) activity. The intestinal microbiota and intestinal colonization by bacteria of oral origin has been implicated in colorectal carcinogenesis. GT modulates the composition of mouse gut microbiota harmonious with anticancer activity. Therefore, the effect of green tea liquid (GTL) consumption on the gut and oral microbiome is investigated in healthy volunteers (n = 12).

METHODS AND RESULTS

16S sequencing and phylogenetic investigation of communities by reconstruction of unobserved states (PICRUSt) analysis of both fecal and saliva samples (collected before intervention, after 2 weeks of GTL (400 mL per day) and after a washout period of one week) in healthy volunteers show changes in microbial diversity and core microbiota and difference in clear classification (partial least squares-discriminant analysis [PLS-DA]). An irreversible, increased FIR:BAC (Firmicutes to Bacteroidetes ratio), elevated SCFA producing genera, and reduction of bacterial LPS synthesis in feces are discovered in response to GTL. GTL alters the salivary microbiota and reduces the functional pathways abundance relevance to carcinogenesis. Similar bacterial networks in fecal and salivary microbiota datasets comprising putative oral bacteria are found and GTL reduces the fecal levels of Fusobacterium. Interestingly, both Lachnospiraceae and B/E (Bifidobacterium to Enterobacteriacea ratio-markers of colonization resistance [CR]) are negatively associated with the presence of oral-like bacterial networks in the feces.

CONCLUSION

These results suggest that GTL consumption causes both oral and gut microbiome alterations.

Characterization of the fecal and mucosa-associated microbiota in dogs with colorectal epithelial tumors

Colorectal epithelial tumors occur spontaneously in dogs, and the pathogenesis seems to parallel that of humans. The development of human colorectal tumorigenesis has been linked to alterations in the composition of the intestinal microbiota. This study characterized the fecal- and mucosa-associated microbiota in dogs with colorectal epithelial tumors (n = 10). The fecal microbiota was characterized by 16S rDNA analysis and compared with that of control dogs (n = 13). We also determined the mucosa-associated microbiota composition in colonic tumor tissue (n = 8) and in adjacent non-tumor tissue (n = 5) by 16S rDNA- and rRNA profiling. The fecal microbial community structure in dogs with tumors was different from that of control samples and was distinguished by oligotypes affiliated with Enterobacteriaceae, Bacteroides, Helicobacter, Porphyromonas, Peptostreptococcus and Streptococcus, and lower abundance of Ruminococcaceae, Slackia, Clostridium XI and Faecalibacterium. The overall community structure and populations of mucosal bacteria were not different based on either the 16S rDNA or the 16S rRNA profile in tumor tissue vs. adjacent non-tumor tissue. However, the proportion of live, potentially active bacteria appeared to be higher in non-tumor tissue compared with tumor tissue and included Slackia, Roseburia, unclass. Ruminococcaeceae, unclass. Lachnospiraceae and Oscillibacter. Colorectal tumors are rarely diagnosed in dogs, but despite this limitation, we were able to show that dogs with colorectal tumors have distinct fecal microbiota profiles. These initial results support the need for future case-control studies that are adequately powered, as well as age-matched and breed-matched, in order to evaluate the influence of bacteria on colorectal cancer etiopathogenesis and to determine whether the bacteria may have potential as biomarkers in clinical settings.

Clinical applications of gut microbiota in cancer biology

The involvement of microorganisms in cancer has been increasing recognized. Collectively, microorganisms have been estimated to account for ∼20% of all cancers worldwide. Recent advances in metagenomics and bioinformatics have provided new insights on the microbial ecology in different tumors, pinpointing the roles of microorganisms in cancer formation, development and response to treatments. Furthermore, studies have emphasized the importance of host-microbial and inter-microbial interactions in the cancer microbiota. These studies have not only revolutionized our understanding of cancer biology, but also opened up new opportunities for cancer prevention, diagnosis, prognostication and treatment. This review article aims to summarize the microbiota in various cancers and their treatments, and explore clinical applications for such relevance.

Systematic review: Gut microbiota in fecal samples and detection of colorectal neoplasms

Colorectal cancer (CRC) is a leading cause of cancer morbidity and mortality. Dysbiosis in the gut microbiota may be associated with CRC. This systematic review focuses on differences in gut microbial community between people diagnosed with CRC or adenoma and healthy individuals using fecal samples, emphasizing non-invasive fecal microbiome models for CRC early diagnosis. Nineteen studies were identified in a systematic literature search of Pubmed, Web of Science and ScienceDirect. Several bacteria were reported to differ in abundance between CRC and adenoma cases and healthy controls, with Fusobacterium the most common. Fecal multi-bacterial predictive models used to distinguish CRC patients from healthy controls had reported areas under the receiver operating curve (AUCs) in external validation populations of 0.68-0.77. Though advanced sequencing techniques could in the future complement current non-invasive methods for CRC early detection, more studies with high statistical power, comparable and reproducible methods and external validation of predictive models are needed.

ResistoMap-online visualization of human gut microbiota antibiotic resistome

Abstract

We created ResistoMap—a Web-based interactive visualization of the presence of genetic determinants conferring resistance to antibiotics, biocides and heavy metals in human gut microbiota. ResistoMap displays the data on more than 1500 published gut metagenomes of world populations including both healthy subjects and patients. Multiparameter display filters allow visual assessment of the associations between the meta-data and proportions of resistome. The geographic map navigation layer allows to state hypotheses regarding the global trends of antibiotic resistance and correlates the gut resistome variations with the national clinical guidelines on antibiotics application.

Availability and Implementation

ResistoMap was implemented using AngularJS, CoffeeScript, D3.js and TopoJSON. The tool is publicly available at http://resistomap.rcpcm.org.

Contact

yarygin@phystech.edu.

Supplementary information

Supplementary data are available at Bioinformatics online.

Both the intratumoral immune and microbial microenvironment are linked to recurrence in human colon cancer: results from a prospective, multicenter nodal ultrastaging trial

Colon cancer (CC) is the third most common cancer diagnosed in the United States and the incidence has been rising among young adults. We and others have shown a relationship between the immune infiltrate and prognosis, with improved disease-free survival (DFS) being associated with a higher expression of CD8⁺ T cells. We hypothesized that a microbial signature might be associated with intratumoral immune cells as well as DFS. We found that the relative abundance of one Operational Taxonomic Unit (OTU), OTU_104, was significantly associated with recurrence even after applying false discovery correction (HR 1.21, CI 1.08 to 1.36). The final multivariable model showed that DFS was influenced by three parameters: N-stage, CD8⁺ labeling, as well as this OTU_104 belonging to the order Clostridiales. Not only were CD8⁺ labeling and OTU_104 significant contributors in the final DFS model, but they were also inversely correlated to each other (p=0.022). Interestingly, CD8⁺ was also significantly associated with the microbiota composition in the tumor: CD8⁺ T cells was inversely correlated with alpha diversity (p=0.027) and significantly associated with the beta diversity. This study is the first to demonstrate an association among the intratumoral microbiome, CD8⁺ T cells, and recurrence in CC. An increased relative abundance of a specific OTU_104 was inversely associated with CD8⁺ T cells and directly associated with CC recurrence. The link between this microbe, CD8⁺ T cells, and DFS has not been previously shown.

Leveraging sequence-based faecal microbial community survey data to identify a composite biomarker for colorectal cancer

OBJECTIVE

Colorectal cancer (CRC) is the second leading cause of cancer-associated mortality in the USA. The faecal microbiome may provide non-invasive biomarkers of CRC and indicate transition in the adenoma-carcinoma sequence. Re-analysing raw sequence and metadata from several studies uniformly, we sought to identify a composite and generalisable microbial marker for CRC.

DESIGN

Raw 16S rRNA gene sequence data sets from nine studies were processed with two pipelines, (1) QIIME closed reference (QIIME-CR) or (2) a strain-specific method herein termed SS-UP (Strain Select, UPARSE bioinformatics pipeline). A total of 509 samples (79 colorectal adenoma, 195 CRC and 235 controls) were analysed. Differential abundance, meta-analysis random effects regression and machine learning analyses were carried out to determine the consistency and diagnostic capabilities of potential microbial biomarkers.

RESULTS

Definitive taxa, including Parvimonas micra ATCC 33270, Streptococcus anginosus and yet-to-be-cultured members of Proteobacteria, were frequently and significantly increased in stools from patients with CRC compared with controls across studies and had high discriminatory capacity in diagnostic classification. Microbiome-based CRC versus control classification produced an area under receiver operator characteristic (AUROC) curve of 76.6% in QIIME-CR and 80.3% in SS-UP. Combining clinical and microbiome markers gave a diagnostic AUROC of 83.3% for QIIME-CR and 91.3% for SS-UP.

CONCLUSIONS

Despite technological differences across studies and methods, key microbial markers emerged as important in classifying CRC cases and such could be used in a universal diagnostic for the disease. The choice of bioinformatics pipeline influenced accuracy of classification. Strain-resolved microbial markers might prove crucial in providing a microbial diagnostic for CRC.

The Role of the Gut Microbiome in Colorectal Cancer

There is increasing evidence that the gut microbiome, which consists of trillions of microbes representing over 1,000 species of bacteria with over 3 million genes, significantly impacts intestinal health and disease. The gut microbiota not only is capable of promoting intestinal homeostasis and antitumor responses but can also contribute to chronic dysregulated inflammation as well as have genotoxic effects that lead to carcinogenesis. Whether the gut microbiota maintains health or promotes colon cancer may ultimately depend on the composition of the gut microbiome and the balance within the microbial community of protective and detrimental bacterial populations. Disturbances in the normal balanced state of a healthful microbiome, known as dysbiosis, have been observed in patients with colorectal cancer (CRC); however, whether these alterations precede and cause CRC remains to be determined. Nonetheless, studies in mice strongly suggest that the gut microbiota can modulate susceptibility to CRC, and therefore may serve as both biomarkers and therapeutic targets.

16S rRNA Gene Sequencing for Deciphering the Colorectal Cancer Gut Microbiome: Current Protocols and Workflows

The human gut holds the densest microbiome ecosystem essential in maintaining a healthy host physiology, whereby disruption of this ecosystem has been linked to the development of colorectal cancer (CRC). The advent of next-generation sequencing technologies such as the 16S rRNA gene sequencing has enabled characterization of the CRC gut microbiome architecture in an affordable and culture-free approach. Nevertheless, the lack of standardization in handling and storage of biospecimens, nucleic acid extraction, 16S rRNA gene primer selection, length, and depth of sequencing and bioinformatics analyses have contributed to discrepancies found in various published studies of this field. Accurate characterization of the CRC microbiome found in different stages of CRC has the potential to be developed into a screening tool in the clinical setting. This mini review aims to concisely compile all available CRC microbiome studies performed till end of 2016 and to suggest standardized protocols that are crucial in developing a gut microbiome screening panel for CRC.

Correcting for batch effects in case-control microbiome studies

High-throughput data generation platforms, like mass-spectrometry, microarrays, and second-generation sequencing are susceptible to batch effects due to run-to-run variation in reagents, equipment, protocols, or personnel. Currently, batch correction methods are not commonly applied to microbiome sequencing datasets. In this paper, we compare different batch-correction methods applied to microbiome case-control studies. We introduce a model-free normalization procedure where features (i.e. bacterial taxa) in case samples are converted to percentiles of the equivalent features in control samples within a study prior to pooling data across studies. We look at how this percentile-normalization method compares to traditional meta-analysis methods for combining independent p-values and to limma and ComBat, widely used batch-correction models developed for RNA microarray data. Overall, we show that percentile-normalization is a simple, non-parametric approach for correcting batch effects and improving sensitivity in case-control meta-analyses.

Batch effects are obstacles to comparing results across studies. Traditional meta-analysis techniques for combining p-values from independent studies, like Fisher’s method, are effective but statistically conservative. If batch-effects can be corrected, then statistical tests can be performed on data pooled across studies, increasing sensitivity to detect differences between treatment groups. Here, we show how a simple, model-free approach corrects for batch effects in case-control microbiome datasets.

Gut microbiome of Moroccan colorectal cancer patients

Although colorectal cancer is the third leading cause of death in Morocco, there are no studies of the microbiome changes associated with the disease in the Moroccan population. The aim of our study was to compare the stool microbiome of Moroccan cancer patients with healthy individuals. We analyzed the microbiome composition of samples from 11 CRC patients and 12 healthy individuals by 16S rRNA amplicon sequencing. Principal coordinate analysis of samples revealed defined cancer versus healthy clusters. Our findings showed that cancer samples had higher proportions of Firmicutes (T = 50.5%; N = 28.4%; p = 0.04), specifically of Clostridia (T = 48.3%; N = 19.0%; p = 0.002), and Fusobacteria (T = 0.1%; N = 0.0%; p = 0.02), especially of Fusobacteriia (T = 0.1%; N = 0.0%; p = 0.02), while Bacteroidetes were enriched in healthy samples (T = 35.1%; N = 62.8%; p = 0.06), particularly the class Bacteroidia (T = 35.1%; N = 62.6%; p = 0.06). Porphyromonas, Clostridium, Ruminococcus, Selenomonas, and Fusobacterium were significantly overrepresented in diseased patients, similarly to other studies. Predicted functional information showed that bacterial motility proteins, flagellar assembly, and fatty acid biosynthesis metabolism were significantly overrepresented in cancer patients, while amino acid metabolism and glycan biosynthesis were overrepresented in controls. This suggests that involvement of these functional metagenomes is similar and relevant in the carcinogenesis process, independent of the origin of the samples. Results from this study allowed identification of bacterial taxa relevant to the Moroccan population and encourages larger studies to facilitate population-directed therapeutic approaches.

Similarity of the dog and human gut microbiomes in gene content and response to diet

BACKGROUND

Gut microbes influence their hosts in many ways, in particular by modulating the impact of diet. These effects have been studied most extensively in humans and mice. In this work, we used whole genome metagenomics to investigate the relationship between the gut metagenomes of dogs, humans, mice, and pigs.

RESULTS

We present a dog gut microbiome gene catalog containing 1,247,405 genes (based on 129 metagenomes and a total of 1.9 terabasepairs of sequencing data). Based on this catalog and taxonomic abundance profiling, we show that the dog microbiome is closer to the human microbiome than the microbiome of either pigs or mice. To investigate this similarity in terms of response to dietary changes, we report on a randomized intervention with two diets (high-protein/low-carbohydrate vs. lower protein/higher carbohydrate). We show that diet has a large and reproducible effect on the dog microbiome, independent of breed or sex. Moreover, the responses were in agreement with those observed in previous human studies.

CONCLUSIONS

We conclude that findings in dogs may be predictive of human microbiome results. In particular, a novel finding is that overweight or obese dogs experience larger compositional shifts than lean dogs in response to a high-protein diet.

Crosstalk between gut microbiota and Sirtuin-3 in colonic inflammation and tumorigenesis

Colorectal cancer (CRC) is a disease involving a variety of genetic and environmental factors. Sirtuin-3 (Sirt3) is expressed at a low level in cancer tissues of CRC, but it is unclear how Sirt3 modulates colonic tumorigenesis. In this study, we found that gut microbiota play a central role in the resistance to CRC tumor formation in wild-type (WT) mice through APC (Adenomatous Polyposis Coli)-mutant mouse microbiota transfer via Wnt signaling. We also found that Sirt3-deficient mice were hypersusceptible to colonic inflammation and tumor development through altered intestinal integrity and p38 signaling, respectively. Furthermore, susceptibility to colorectal tumorigenesis was aggravated by initial commensal microbiota deletion via Wnt signaling. Mice with Sirt3-deficient microbiota transfer followed by chemically induced colon tumorigenesis had low Sirt3 expression compared to WT control microbiome transfer, mainly due to a decrease in Escherichia/Shigella, as well as an increase in Lactobacillus reuteri and Lactobacillus taiwanensis. Collectively, our data revealed that Sirt3 is an anti-inflammatory and tumor-suppressing gene that interacts with the gut microbiota during colon tumorigenesis.

Boosting specific beneficial bacteria in the gut may enhance expression levels of a tumor-suppressing gene in colorectal cancer (CRC). Both genetic factors and the bacteria present in the gut play vital roles in CRC development. However, it is unclear exactly how genes interact with the bacteria to affect tumor growth. Man-tian Mi and co-workers at the Third Military Medical University in Chongqing, China, examined the role of a gene called Sirt-3 in CRC development. Mice lacking the Sirt-3 gene suffered severe chronic inflammation and developed tumors due to altered signalling pathways and reduced intestinal integrity. Further, the guts of the mice harboured more pathogenic bacteria than wild-type mice. The team also found lower levels of two key types of beneficial bacteria that would ordinarily prevent reduced Sirt-3 expression.

Multi-cohort analysis of colorectal cancer metagenome identified altered bacteria across populations and universal bacterial markers

BACKGROUND

Alterations of gut microbiota are associated with colorectal cancer (CRC) in different populations and several bacterial species were found to contribute to the tumorigenesis. The potential use of gut microbes as markers for early diagnosis has also been reported. However, cohort specific noises may distort the structure of microbial dysbiosis in CRC and lead to inconsistent results among studies. In this regard, our study targeted at exploring changes in gut microbiota that are universal across populations at species level.

RESULTS

Based on the combined analysis of 526 metagenomic samples from Chinese, Austrian, American, and German and French cohorts, seven CRC-enriched bacteria (Bacteroides fragilis, Fusobacterium nucleatum, Porphyromonas asaccharolytica, Parvimonas micra, Prevotella intermedia, Alistipes finegoldii, and Thermanaerovibrio acidaminovorans) have been identified across populations. The seven enriched bacterial markers classified cases from controls with an area under the receiver-operating characteristics curve (AUC) of 0.80 across the different populations. Abundance correlation analysis demonstrated that CRC-enriched and CRC-depleted bacteria respectively formed their own mutualistic networks, in which the latter was disjointed in CRC. The CRC-enriched bacteria have been found to be correlated with lipopolysaccharide and energy biosynthetic pathways.

CONCLUSIONS

Our study identified potential diagnostic bacterial markers that are robust across populations, indicating their potential universal use for non-invasive CRC diagnosis. We also elucidated the ecological networks and functional capacities of CRC-associated microbiota.

Immunogenicity of a Fap2 peptide mimotope of Fusobacterium nucleatum and its potential use in the diagnosis of colorectal cancer

Background

The role of Fusobacterium nucleatum Fap2 protein in the development of colorectal cancer has recently been explained. Fap2, when bound to the human inhibitory receptor, TIGIT, inhibits the cytotoxic activity of natural killer (NK) cells against cancer cells, thus, allowing proliferation of the latter eventually leading to tumor growth. The aim of the study was to identify the immunogenicity of a peptide mimotope of the Fap2 protein and to determine the reactivity of colorectal cancer patients’ sera against the mimotope.

Methods

Immunogenic epitope of the Fap2 protein of F. nucleatum was selected using the B-cell epitope prediction of the Immune Epitope Database and Analysis Resource (IEDB). The immunogenicity of the synthetic peptide mimotope of the Fap2 protein was determined in animal models and reactivity of colorectal cancer patients’ sera against the mimotope was done by indirect ELISA.

Results

Results show that the selected peptide mimotope, with sequence TELAYKHYFGT, of the outer membrane protein Fap2 of F. nucleatum is immunogenic. Increase in the absorbance readings of peptide-immunized rabbit sera was observed starting Week 1 which was sustained up to Week 10 in the indirect ELISA performed. Colorectal cancer cases (n = 37) were all reactive in an ELISA-based analysis using the mimotope as the capture antigen.

Conclusions

In this study, we identified an immunogenic epitope of the Fap2 protein of the Fusobacterium nucleatum. We demonstrated the reactivity of serum of histopathologically confirmed CRC patients in a peptide-capture indirect ELISA which may serve as proof of concept for the development of CRC diagnostics.