Colorectal Cancer and the Human Gut Microbiome: Reproducibility with Whole-Genome Shotgun Sequencing

The Limits and Avoidance of Biases in Metagenomic Analyses of Human Fecal Microbiota

An increasing body of evidence highlights the role of fecal microbiota in various human diseases. However, more than two-thirds of fecal bacteria cannot be cultivated by routine laboratory techniques. Thus, physicians and scientists use DNA sequencing and statistical tools to identify associations between bacterial subgroup abundances and disease. However, discrepancies between studies weaken these results. In the present study, we focus on biases that might account for these discrepancies. First, three different DNA extraction methods (G’NOME, QIAGEN, and PROMEGA) were compared with regard to their efficiency, i.e., the quality and quantity of DNA recovered from feces of 10 healthy volunteers. Then, the impact of the DNA extraction method on the bacteria identification and quantification was evaluated using our published cohort of sample subjected to both 16S rRNA sequencing and whole metagenome sequencing (WMS). WMS taxonomical assignation employed the universal marker genes profiler mOTU-v2, which is considered the gold standard. The three standard pipelines for 16S RNA analysis (MALT and MEGAN6, QIIME1, and DADA2) were applied for comparison. Taken together, our results indicate that the G’NOME-based method was optimal in terms of quantity and quality of DNA extracts. 16S rRNA sequence-based identification of abundant bacteria genera showed acceptable congruence with WMS sequencing, with the DADA2 pipeline yielding the highest congruent levels. However, for low abundance genera (<0.5% of the total abundance) two pipelines and/or validation by quantitative polymerase chain reaction (qPCR) or WMS are required. Hence, 16S rRNA sequencing for bacteria identification and quantification in clinical and translational studies should be limited to diagnostic purposes in well-characterized and abundant genera. Additional techniques are warranted for low abundant genera, such as WMS, qPCR, or the use of two bio-informatics pipelines.

Human Gut Microbiome-Based Knowledgebase as a Biomarker Screening Tool to Improve the Predicted Probability for Colorectal Cancer

Colorectal cancer (CRC) is a common clinical malignancy globally ranked as the fourth leading cause of cancer mortality. Some microbes are known to contribute to adenoma-carcinoma transition and possess diagnostic potential. Advances in high-throughput sequencing technology and functional studies have provided significant insights into the landscape of the gut microbiome and the fundamental roles of its components in carcinogenesis. Integration of scattered knowledge is highly beneficial for future progress. In this study, literature review and information extraction were performed, with the aim of integrating the available data resources and facilitating comparative research. A knowledgebase of the human CRC microbiome was compiled to facilitate understanding of diagnosis, and the global signatures of CRC microbes, sample types, algorithms, differential microorganisms and various panels of markers plus their diagnostic performance were evaluated based on statistical and phylogenetic analyses. Additionally, prospects about current changelings and solution strategies were outlined for identifying future research directions. This type of data integration strategy presents an effective platform for inquiry and comparison of relevant information, providing a tool for further study about CRC-related microbes and exploration of factors promoting clinical transformation (available at: http://gsbios.com/index/experimental/dts_ mben?id=1).

Southern Chinese populations harbour non-nucleatum Fusobacteria possessing homologues of the colorectal cancer-associated FadA virulence factor

OBJECTIVE

Fusobacteria are not common nor relatively abundant in non-colorectal cancer (CRC) populations, however, we identified multiple Fusobacterium taxa nearly absent in western and rural populations to be comparatively more prevalent and relatively abundant in southern Chinese populations. We investigated whether these represented known or novel lineages in the Fusobacterium genus, and assessed their genomes for features implicated in development of cancer.

METHODS

Prevalence and relative abundances of fusobacterial species were calculated from 3157 CRC and non-CRC gut metagenomes representing 16 populations from various biogeographies. Microbial genomes were assembled and compared with existing reference genomes to assess novel fusobacterial diversity. Phylogenetic distribution of virulence genes implicated in CRC was investigated.

RESULTS

Irrespective of CRC disease status, southern Chinese populations harboured increased prevalence (maximum 39% vs 7%) and relative abundances (average 0.4% vs 0.04% of gut community) of multiple recognised and novel fusobacterial taxa phylogenetically distinct from Fusobacterium nucleatum. Genomes assembled from southern Chinese gut metagenomes increased existing fusobacterial diversity by 14.3%. Homologues of the FadA adhesin linked to CRC were consistently detected in several monophyletic lineages sister to and inclusive of F. varium and F. ulcerans, but not F. mortiferum. We also detected increased prevalence and relative abundances of F. varium in CRC compared with non-CRC cohorts, which together with distribution of FadA homologues supports a possible association with gut disease.

CONCLUSION

The proportion of fusobacteria in guts of southern Chinese populations are higher compared with several western and rural populations in line with the notion of environment/biogeography driving human gut microbiome composition. Several non-nucleatum taxa possess FadA homologues and were enriched in CRC cohorts; whether this imposes a risk in developing CRC and other gut diseases deserves further investigation.

Gut microbiome profiling of a rural and urban South African cohort reveals biomarkers of a population in lifestyle transition

BACKGROUND

Comparisons of traditional hunter-gatherers and pre-agricultural communities in Africa with urban and suburban Western North American and European cohorts have clearly shown that diet, lifestyle and environment are associated with gut microbiome composition. Yet, little is known about the gut microbiome composition of most communities in the very diverse African continent. South Africa comprises a richly diverse ethnolinguistic population that is experiencing an ongoing epidemiological transition and concurrent spike in the prevalence of obesity, largely attributed to a shift towards more Westernized diets and increasingly inactive lifestyle practices. To characterize the microbiome of African adults living in more mainstream lifestyle settings and investigate associations between the microbiome and obesity, we conducted a pilot study, designed collaboratively with community leaders, in two South African cohorts representative of urban and transitioning rural populations. As the rate of overweight and obesity is particularly high in women, we collected single time-point stool samples from 170 HIV-negative women (51 at Soweto; 119 at Bushbuckridge), performed 16S rRNA gene sequencing on these samples and compared the data to concurrently collected anthropometric data.

RESULTS

We found the overall gut microbiome of our cohorts to be reflective of their ongoing epidemiological transition. Specifically, we find that geographical location was more important for sample clustering than lean/obese status and observed a relatively higher abundance of the Melainabacteria, Vampirovibrio, a predatory bacterium, in Bushbuckridge. Also, Prevotella, despite its generally high prevalence in the cohorts, showed an association with obesity. In comparisons with benchmarked datasets representative of non-Western populations, relatively higher abundance values were observed in our dataset for Barnesiella (log2fold change (FC) = 4.5), Alistipes (log2FC = 3.9), Bacteroides (log2FC = 4.2), Parabacteroides (log2FC = 3.1) and Treponema (log2FC = 1.6), with the exception of Prevotella (log2FC = - 4.7).

CONCLUSIONS

Altogether, this work identifies putative microbial features associated with host health in a historically understudied community undergoing an epidemiological transition. Furthermore, we note the crucial role of community engagement to the success of a study in an African setting, the importance of more population-specific studies to inform targeted interventions as well as present a basic foundation for future research.

Omics technologies for improved diagnosis and treatment of colorectal cancer: Technical advancement and major perspectives

Colorectal cancer (CRC) ranks third among the most commonly occurring cancers worldwide, and it causes half a million deaths annually. Alongside mechanistic study for CRC detection and treatment by conventional techniques, new technologies have been developed to study CRC. These technologies include genomics, transcriptomics, proteomics, and metabolomics which elucidate DNA markers, RNA transcripts, protein and, metabolites produced inside the colon and rectum part of the gut. All these approaches form the omics arena, which presents a remarkable opportunity for the discovery of novel prognostic, diagnostic and therapeutic biomarkers and also delineate the underlying mechanism of CRC causation, which may further help in devising treatment strategies. This review also mentions the latest developments in metagenomics and culturomics as emerging evidence suggests that metagenomics of gut microbiota has profound implications in the causation, prognosis, and treatment of CRC. A majority of bacteria cannot be studied as they remain unculturable, so culturomics has also been strengthened to develop culture conditions suitable for the growth of unculturable bacteria and identify unknown bacteria. The overall purpose of this review is to succinctly evaluate the application of omics technologies in colorectal cancer research for improving the diagnosis and treatment strategies.

The Human Microbiome in Relation to Cancer Risk: A Systematic Review of Epidemiologic Studies

The microbiome has been hypothesized to play a role in cancer development. Because of the diversity of published data, an overview of available epidemiologic evidence linking the microbiome with cancer is now needed. We conducted a systematic review using a tailored search strategy in Medline and EMBASE databases to identify and summarize the current epidemiologic literature on the relationship between the microbiome and different cancer outcomes published until December 2019. We identified 124 eligible articles. The large diversity of parameters used to describe microbial composition made it impossible to harmonize the different studies in a way that would allow meta-analysis, therefore only a qualitative description of results could be performed. Fifty studies reported differences in the gut microbiome between patients with colorectal cancer and various control groups. The most consistent findings were for Fusobacterium, Porphyromonas, and Peptostreptococcus being significantly enriched in fecal and mucosal samples from patients with colorectal cancer. For the oral microbiome, significantly increased and decreased abundance was reported for Fusobacterium and Streptococcus, respectively, in patients with oral cancer compared with controls. Overall, although there was a large amount of evidence for some of these alterations, most require validation in high-quality, preferably prospective, epidemiologic studies.

The Clinical Versatility of Next-Generation Sequencing in Colorectal Cancer

Next-Generation Sequencing is an evolving technology employed in the field of cancer biology. This mini review is intended as a brief overview of NGS for the clinical utility in colorectal cancer. The pathogenesis and treatment of colorectal cancer will continue to evolve as NGS is applied to more patient samples, correlating tumor biology and outcomes.

Compositional and functional differences of the mucosal microbiota along the intestine of healthy individuals

Gut mucosal microbes evolved closest to the host, developing specialized local communities. There is, however, insufficient knowledge of these communities as most studies have employed sequencing technologies to investigate faecal microbiota only. This work used shotgun metagenomics of mucosal biopsies to explore the microbial communities' compositions of terminal ileum and large intestine in 5 healthy individuals. Functional annotations and genome-scale metabolic modelling of selected species were then employed to identify local functional enrichments. While faecal metagenomics provided a good approximation of the average gut mucosal microbiome composition, mucosal biopsies allowed detecting the subtle variations of local microbial communities. Given their significant enrichment in the mucosal microbiota, we highlight the roles of Bacteroides species and describe the antimicrobial resistance biogeography along the intestine. We also detail which species, at which locations, are involved with the tryptophan/indole pathway, whose malfunctioning has been linked to pathologies including inflammatory bowel disease. Our study thus provides invaluable resources for investigating mechanisms connecting gut microbiota and host pathophysiology.

Microbes and complex diseases: from experimental results to computational models

Studies have shown that the number of microbes in humans is almost 10 times that of cells. These microbes have been proven to play an important role in a variety of physiological processes, such as enhancing immunity, improving the digestion of gastrointestinal tract and strengthening metabolic function. In addition, in recent years, more and more research results have indicated that there are close relationships between the emergence of the human noncommunicable diseases and microbes, which provides a novel insight for us to further understand the pathogenesis of the diseases. An in-depth study about the relationships between diseases and microbes will not only contribute to exploring new strategies for the diagnosis and treatment of diseases but also significantly heighten the efficiency of new drugs development. However, applying the methods of biological experimentation to reveal the microbe-disease associations is costly and inefficient. In recent years, more and more researchers have constructed multiple computational models to predict microbes that are potentially associated with diseases. Here, we start with a brief introduction of microbes and databases as well as web servers related to them. Then, we mainly introduce four kinds of computational models, including score function-based models, network algorithm-based models, machine learning-based models and experimental analysis-based models. Finally, we summarize the advantages as well as disadvantages of them and set the direction for the future work of revealing microbe-disease associations based on computational models. We firmly believe that computational models are expected to be important tools in large-scale predictions of disease-related microbes.

Evolving Technologies in Gastrointestinal Microbiome Era and Their Potential Clinical Applications

The human gastrointestinal microbiota (GIM) is a complex and diverse ecosystem that consists of community of fungi, viruses, protists and majorly bacteria. The association of several human illnesses, such as inflammatory bowel disease, allergy, metabolic syndrome and cancers, have been linked directly or indirectly to compromise in the integrity of the GIM, for which some medical interventions have been proposed or attempted. This review highlights and gives update on various technologies, including microfluidics, high-through-put sequencing, metabolomics, metatranscriptomics and culture in GIM research and their applications in gastrointestinal microbiota therapy, with a view to raise interest in the evaluation, validation and eventual use of these technologies in diagnosis and the incorporation of therapies in routine clinical practice.

Establishing high-accuracy biomarkers for colorectal cancer by comparing fecal microbiomes in patients with healthy families

Colorectal cancer (CRC) causes high morbidity and mortality worldwide, and noninvasive gut microbiome (GM) biomarkers are promising for early CRC diagnosis. However, the GM varies significantly based on ethnicity, diet and living environment, suggesting varied GM biomarker performance in different regions. We performed a metagenomic association analysis on stools from 52 patients and 55 corresponding healthy family members who lived together to identify GM biomarkers for CRC in Chongqing, China. The GM of patients differed significantly from that of healthy controls. A total of 22 microbial genes were included as screening biomarkers with high accuracy in additional 46 cases and 40 randomly selected healthy adults in Chongqing (area under the receive-operation curve (AUC) = 0.905, 95% CI 0.832-0.977). The classifier based on the identified 22 biomarkers also performed well in the cohort from Hong Kong (AUC = 0.811, 95% CI 0.715-0.907) and French (AUC = 0.859, 95% CI 0.773-0.944) populations. Quantitative PCR was applied for measuring three selected biomarkers in the classification of CRC patients in independent Chongqing population containing 30 cases and 30 controls and the best biomarker from Coprobacillus performed well with high AUC (0.930, 95% CI 0.904-0.955). This study revealed increased sensitivity and applicability of our GM biomarkers compared with previous biomarkers significantly promoting the early diagnosis of CRC.

Porphyromonas: A neglected potential key genus in human microbiomes

Anaerobes form a large part of microbial communities, and have begun to be specifically studied in both healthy and pathologic contexts. Porphyromonas is one of the top ten anaerobic taxa in the microbiome (anaerobiome) in healthy subjects. However, to date, most studies focused on the deleterious role of P. gingivalis, the most widely described species. Interestingly, targeted metagenomics reveals Porphyromonas other than gingivalis (POTG), highlighting other species such as P. catoniae or P. pasteri as potential biomarkers in disease progression or pathogen colonization susceptibility. From the sparse data, it appears that the Porphyromonas genus may also be a relevant target of investigation in several pulmonary diseases. Moreover, deciphering cutaneous, gastric and oral microbiomes hint that Porphyromonas may be a genus of interest in non-pulmonary diseases. This review aims to summarize the major data on POTG and to report their impact on the various human microbiomes in different clinical states.

Effects of postoperative adjuvant chemotherapy and palliative chemotherapy on the gut microbiome in colorectal cancer

BACKGROUND

The gut microbiome changes are related to the colorectal cancer (CRC). Chemotherapy is one of the main treatment methods for CRC.

PURPOSE

To explore the effect of chemotherapy on the gut bacteria and fungi in CRC.

METHODS

Total of 11 advanced CRC patients treated with the FOLFIRI regimen, 15 postoperative CRC patients treated with the XELOX regimen, and corresponding CRC patients without surgery and chemotherapy were recruited. The 16S ribosomal RNA and ITS sequences were sequenced, and bioinformatics analysis was executed to screen for the distinctive gut microbiome.

RESULTS

The abundances of Veillonella, Humicola, Tremellomycetes and Malassezia were increased in postoperative CRC patients treated with the XELOX regimen. The abundances of Faecalibacterium, Clostridiales, phascolarctobacterium, Humicola and Rhodotorula were decreased, and the abundances of Candida, Magnusiomyces, Tremellomycetes, Dipodascaceae, Saccharomycetales, Malassezia and Lentinula were increased in advanced CRC patients treated with the FOLFIRI regimen. The abundances of Humicola, Rhodotorula, and Magnusiomyces were decreased, and the abundances of Candida, Tremellomycetes, Dipodascaceae, Saccharomycetales, Malassezia and Lentinula were increased in advanced CRC patients treated with the FOLFIRI regimen combined with cetuximab compared with those treated with the FOLFIRI regimen alone.

CONCLUSIONS

The community structure of gut bacteria and fungi changes in chemotherapy on CRCs.

LINC01123 Promotes Progression of Colorectal Cancer via miR-625-5p/LASP1 Axis

Background: Evidence from previous investigations points to a rising trend in the incidence of colorectal cancer (CRC) worldwide. The mortality resulting from this cancer is high. Unlike nonsmall cell lung cancer for which LINC01123 has been investigated, there are few reports on how this long noncoding RNA (lncRNA) regulates CRC. Materials and Methods: The authors evaluated the expression of LINC01123 in CRC tissues by quantitative real-time polymerase chain reaction. Its impact on cancer cell behavior was analyzed with cell counting kit-8 (CCK-8), colony formation, and Transwell invasion assays. To establish the mechanisms of LINC01123 in CRC they carried out RIP and luciferase reporter assays. Results: The results show that LINC01123 expression is abnormally elevated in CRC tissues and cell lines. High LINC01123 expression closely correlates with poor prognosis, advanced TNM stage, and lymph-node metastasis. The authors also show that knockdown of LINC01123 inhibits proliferation and invasion in CRC cells. In mechanism, it is revealed that LINC01123 may function as competitive endogenous RNA (ceRNA) against miR-625-5p to promote LIM and SH3 protein 1 (LASP1) expression. Conclusions: The data indicate that high LINC01123 exerts its oncogenic roles by regulating the miR-625-5p/LASP1 axis in CRC progression.

Host DNA contents in fecal metagenomics as a biomarker for intestinal diseases and effective treatment

Background

Compromised intestinal barrier (CIB) has been associated with many enteropathies, including colorectal cancer (CRC) and inflammatory bowel disease (IBD). We hypothesized that CIB could lead to increased host-derived contents including epithelial cells into the gut, change its physio-metabolic properties, and globally alter microbial community and metabolic capacities.

Results

Consistently, we found host DNA contents (HDCs), calculated as the percentage of metagenomic sequencing reads mapped to the host genome, were significantly elevated in patients of CRC and Crohn’s disease (CD). Consistent with our hypothesis, we found that HDC correlated with microbial- and metabolic-biomarkers of these diseases, contributed significantly to machine-learning models for patient stratification and was consequently ranked as a top contributor. CD patients with treatment could partially reverse the changes of many CD-signature species over time, with reduced HDC and fecal calprotectin (FCP) levels. Strikingly, HDC showed stronger correlations with the reversing changes of the CD-related species than FCP, and contributed greatly in classifying treatment responses, suggesting that it was also a biomarker for effective treatment.

Conclusions

Together, we revealed that association between HDCs and gut dysbiosis, and identified HDC as a novel biomarker from fecal metagenomics for diagnosis and effective treatment of intestinal diseases; our results also suggested that host-derived contents may have greater impact on gut microbiota than previously anticipated.

Integrative Analysis of Fecal Metagenomics and Metabolomics in Colorectal Cancer

Although colorectal cancer (CRC) is the second leading cause of death in developed countries, current diagnostic tests for early disease stages are suboptimal. We have performed a combination of UHPLC-MS metabolomics and 16S microbiome analyses on 224 feces samples in order to identify early biomarkers for both advanced adenomas (AD) and CRC. We report differences in fecal levels of cholesteryl esters and sphingolipids in CRC. We identified Fusobacterium, Parvimonas and Staphylococcus to be increased in CRC patients and Lachnospiraceae family to be reduced. We finally described Adlercreutzia to be more abundant in AD patients' feces. Integration of metabolomics and microbiome data revealed tight interactions between bacteria and host and performed better than FOB test for CRC diagnosis. This study identifies potential early biomarkers that outperform current diagnostic tools and frame them into the stablished gut microbiota role in CRC pathogenesis.

Clinical results and microbiota changes after faecal microbiota transplantation for chronic pouchitis: a pilot study

Objectives: Research evidence suggests that chronic pouchitis is associated with intestinal dysbiosis. Faecal microbiota transplantation (FMT) has been proposed as a possible treatment. We performed a 6-month prospective, open-label, single-centre cohort pilot-study (NCT03538366) to investigate if FMT could improve clinical outcome and alter gut microbiota in patients with chronic pouchitis.Materials and methods: Nine adult patients with chronic pouchitis were included and allocated to 14 days FMT by enemas from five faecal donors, with a 6-month follow-up. Pouchitis severity was assessed using pouchitis disease activity index (PDAI) before and after FMT. Changes in gut microbiota, and engraftment of donor's microbiota were assessed in faecal samples.Results: All patients were treated with FMT for 14 continuous days. Overall, four of nine patients receiving FMT were in clinical remission at 30-day follow-up, and three patients remained in remission until 6-month follow-up. Clinical symptoms of pouchitis improved significantly between inclusion and 14-day follow-up (p = .02), but there was no improvement in PDAI between inclusion (mean 8.6) and 30-day follow-up (mean 5.2). Treatment with FMT caused a substantial shift in microbiota and increased microbial diversity in six patients, resembling that of the donors, with a high engraftment of specific donor microbiota.Conclusions: Symptomatic benefit in FMT treatment was found for four of nine patients with chronic pouchitis with increased microbial diversity and high engraftment of donor's microbiota. A larger, randomised controlled study is required to fully evaluate the potential role of FMT in treating chronic pouchitis.

Adjusting for age improves identification of gut microbiome alterations in multiple diseases

Interaction between disease-microbiome associations and ageing has not been explored in detail. Here, using age/region-matched sub-sets, we analysed the gut microbiome differences across five major diseases in a multi-cohort dataset constituting more than 2500 individuals from 20 to 89 years old. We show that disease-microbiome associations display specific age-centric trends. Ageing-associated microbiome alterations towards a disease-like configuration occur in colorectal cancer patients, thereby masking disease signatures. We identified a microbiome disease response shared across multiple diseases in elderly subjects that is distinct from that in young/middle-aged individuals, but also a novel set of taxa consistently gained in disease across all age groups. A subset of these taxa was associated with increased frailty in subjects from the ELDERMET cohort. The relevant taxa differentially encode specific functions that are known to have disease associations.

Detection of Colorectal Carcinoma Based on Microbiota Analysis Using Generalized Regression Neural Networks and Nonlinear Feature Selection

To obtain a screening tool for colorectal cancer (CRC) based on gut microbiota, we seek here to identify an optimal classifier for CRC detection as well as a novel nonlinear feature selection method for determining the most discriminative microbial species. In this study, the intestinal microflora in feces of 141 patients were modeled using general regression neural networks (GRNNs) combined with the proposed feature selection method. The proposed model led to slightly higher accuracy (AUC = 0.911) than previous studies . The results show that the Clostridium scindens and Bifidobacterium angulatum are indicators of healthy gut flora and CRC happens to reduce these bacterial species. In addition, Fusobacterium gonidiaformans was found to be closely correlated with the CRC. The occurrence of colorectal adenoma was not sufficiently discriminatory based on fecal microbiota implicating that the change of colonic flora happens in the advanced phase of CRC development rather than initial adenoma. Integrating the proposed model with fecal occult blood test (FOBT), the CRC detection accuracy remained nearly unchanged (AUC = 0.915). The performance of the proposed method is validated using independent cohorts from America and Austria. Our results suggest that the proposed feature selection method combined with GRNN is potentially an accurate method for CRC detection.

Identifying viruses from metagenomic data using deep learning

BACKGROUND

The recent development of metagenomic sequencing makes it possible to massively sequence microbial genomes including viral genomes without the need for laboratory culture. Existing reference-based and gene homology-based methods are not efficient in identifying unknown viruses or short viral sequences from metagenomic data.

METHODS

Here we developed a reference-free and alignment-free machine learning method, DeepVirFinder, for identifying viral sequences in metagenomic data using deep learning.

RESULTS

Trained based on sequences from viral RefSeq discovered before May 2015, and evaluated on those discovered after that date, DeepVirFinder outperformed the state-of-the-art method VirFinder at all contig lengths, achieving AUROC 0.93, 0.95, 0.97, and 0.98 for 300, 500, 1000, and 3000 bp sequences respectively. Enlarging the training data with additional millions of purified viral sequences from metavirome samples further improved the accuracy for identifying virus groups that are under-represented. Applying DeepVirFinder to real human gut metagenomic samples, we identified 51,138 viral sequences belonging to 175 bins in patients with colorectal carcinoma (CRC). Ten bins were found associated with the cancer status, suggesting viruses may play important roles in CRC.

CONCLUSIONS

Powered by deep learning and high throughput sequencing metagenomic data, DeepVirFinder significantly improved the accuracy of viral identification and will assist the study of viruses in the era of metagenomics.

Cervicovaginal microbiome and natural history of HPV in a longitudinal study

BACKGROUND

Human papillomavirus (HPV) infection is one of the most common sexually transmitted infections. However, only a small percentage of high-risk (HR) HPV infections progress to cervical precancer and cancer. In this study, we investigated the role of the cervicovaginal microbiome (CVM) in the natural history of HR-HPV.

METHODS

This study was nested within the placebo arm of the Costa Rica HPV Vaccine Trial that included women aged 18-25 years of age. Cervical samples from two visits of women with an incident HR-HPV infection (n = 273 women) were used to evaluate the prospective role of the CVM on the natural history of HR-HPV. We focus specifically on infection clearance, persistence, and progression to cervical intraepithelial neoplasia grade 2 and 3 (CIN2+). The CVM was characterized by amplification and sequencing the bacterial 16S V4 rRNA gene region and the fungal ITS1 region using an Illumina MiSeq platform. OTU clustering was performed using QIIME2. Functional groups were imputed using PICRUSt and statistical analyses were performed using R.

RESULTS

At Visit 1 (V1) abundance of Lactobacillus iners was associated with clearance of incident HR-HPV infections (Linear Discriminant Analysis (LDA)>4.0), whereas V1 Gardnerella was the dominant biomarker for HR-HPV progression (LDA>4.0). At visit 2 (V2), increased microbial Shannon diversity was significantly associated with progression to CIN2+ (p = 0.027). Multivariate mediation analysis revealed that the positive association of V1 Gardnerella with CIN2+ progression was due to the increased cervicovaginal diversity at V2 (p = 0.040). A full multivariate model of key components of the CVM showed significant protective effects via V1 genus Lactobacillus, OR = 0.41 (0.22-0.79), V1 fungal diversity, OR = 0.90 (0.82-1.00) and V1 functional Cell Motility pathway, OR = 0.75 (0.62-0.92), whereas V2 bacterial diversity, OR = 1.19 (1.03-1.38) was shown to be predictive of progression to CIN2+.

CONCLUSION

This study demonstrates that features of the cervicovaginal microbiome are associated with HR-HPV progression in a prospective longitudinal cohort. The analyses indicated that the association of Gardnerella and progression to CIN2+ may actually be mediated by subsequent elevation of microbial diversity. Identified features of the microbiome associated with HR-HPV progression may be targets for therapeutic manipulation to prevent CIN2+.

TRIAL REGISTRATION

ClinicalTrials.gov NCT00128661.

Comparison of Methods To Collect Fecal Samples for Microbiome Studies Using Whole-Genome Shotgun Metagenomic Sequencing

Few previous studies have assessed stability and "gold-standard" concordance of fecal sample collection methods for whole-genome shotgun metagenomic sequencing (WGSS), an increasingly popular method for studying the gut microbiome. We used WGSS data to investigate ambient temperature stability and putative gold-standard concordance of microbial profiles in fecal samples collected and stored using fecal occult blood test (FOBT) cards, fecal immunochemical test (FIT) tubes, 95% ethanol, or RNAlater. Among 15 Mayo Clinic employees, for each collection method, we calculated intraclass correlation coefficients (ICCs) to estimate stability of fecal microbial profiles after storage for 4 days at ambient temperature and concordance with immediately frozen, no-solution samples (i.e., the putative gold standard). ICCs were estimated for multiple metrics, including relative abundances of select phyla, species, KEGG k-genes (representing any coding sequence that had >70% identity and >70% query coverage with respect to a known KEGG ortholog), KEGG modules, and KEGG pathways; species and k-gene alpha diversity; and Bray-Curtis and Jaccard species beta diversity. ICCs for microbial profile stability were excellent (≥90%) for fecal samples collected via most of the collection methods, except those preserved in 95% ethanol. Concordance with the immediately frozen, no-solution samples varied for all collection methods, but the number of observed species and the beta diversity metrics tended to have higher concordance than other metrics. Our findings, taken together with previous studies and feasibility considerations, indicated that FOBT cards, FIT tubes, and RNAlater are acceptable choices for fecal sample collection methods in future WGSS studies.IMPORTANCE A major direction for future microbiome research is implementation of fecal sample collections in large-scale, prospective epidemiologic studies. Studying microbiome-disease associations likely requires microbial data to be pooled from multiple studies. Our findings suggest collection methods that are most optimal to be used standardly across future WGSS microbiome studies.

Role of meprin metalloproteases in metastasis and tumor microenvironment

A crucial step for tumor cell extravasation and metastasis is the migration through the extracellular matrix, which requires proteolytic activity. Hence, proteases, particularly matrix metalloproteases (MMPs), have been discussed as therapeutic targets and their inhibition should diminish tumor growth and metastasis. The metalloproteases meprin α and meprin β are highly abundant on intestinal enterocytes and their expression was associated with different stages of colorectal cancer. Due to their ability to cleave extracellular matrix (ECM) components, they were suggested as pro-tumorigenic enzymes. Additionally, both meprins were shown to have pro-inflammatory activity by cleaving cytokines and their receptors, which correlates with chronic intestinal inflammation and associated conditions. On the other hand, meprin β was identified as an essential enzyme for the detachment and renewal of the intestinal mucus, important to prevent bacterial overgrowth and infection. Considering this, it is hard to estimate whether high activity of meprins is generally detrimental or if these enzymes have also protective functions in certain cancer types. For instance, for colorectal cancer, patients with high meprin β expression in tumor tissue exhibit a better survival prognosis, which is completely different to prostate cancer. This demonstrates that the very same enzyme may have contrary effects on tumor initiation and growth, depending on its tissue and subcellular localization. Hence, precise knowledge about proteolytic enzymes is required to design the most efficient therapeutic options for cancer treatment. In this review, we summarize the current findings on meprins' functions, expression, and cancer-associated variants with possible implications for tumor progression and metastasis.

Microbiome in Colorectal Cancer: How to Get from Meta-omics to Mechanism?

Mounting evidence from metagenomic analyses suggests that a state of pathological microbial imbalance or dysbiosis is prevalent in the gut of patients with colorectal cancer. Several bacterial taxa have been identified of which representative isolate cultures interact with human cancer cells in vitro and trigger disease pathways in animal models. However, how the complex interrelationships in dysbiotic communities may be involved in cancer pathogenesis remains a crucial question. Here, we provide a survey of current knowledge of the gut microbiome in colorectal cancer. Moving beyond observational studies, we outline new experimental approaches for gaining ecosystem-level mechanistic understanding of the gut microbiome's role in cancer pathogenesis.

Metabolic models predict bacterial passengers in colorectal cancer

BACKGROUND

Colorectal cancer (CRC) is a complex multifactorial disease. Increasing evidence suggests that the microbiome is involved in different stages of CRC initiation and progression. Beyond specific pro-oncogenic mechanisms found in pathogens, metagenomic studies indicate the existence of a microbiome signature, where particular bacterial taxa are enriched in the metagenomes of CRC patients. Here, we investigate to what extent the abundance of bacterial taxa in CRC metagenomes can be explained by the growth advantage resulting from the presence of specific CRC metabolites in the tumor microenvironment.

METHODS

We composed lists of metabolites and bacteria that are enriched on CRC samples by reviewing metabolomics experimental literature and integrating data from metagenomic case-control studies. We computationally evaluated the growth effect of CRC enriched metabolites on over 1500 genome-based metabolic models of human microbiome bacteria. We integrated the metabolomics data and the mechanistic models by using scores that quantify the response of bacterial biomass production to CRC-enriched metabolites and used these scores to rank bacteria as potential CRC passengers.

RESULTS

We found that metabolic networks of bacteria that are significantly enriched in CRC metagenomic samples either depend on metabolites that are more abundant in CRC samples or specifically benefit from these metabolites for biomass production. This suggests that metabolic alterations in the cancer environment are a major component shaping the CRC microbiome.

CONCLUSION

Here, we show with in sillico models that supplementing the intestinal environment with CRC metabolites specifically predicts the outgrowth of CRC-associated bacteria. We thus mechanistically explain why a range of CRC passenger bacteria are associated with CRC, enhancing our understanding of this disease. Our methods are applicable to other microbial communities, since it allows the systematic investigation of how shifts in the microbiome can be explained from changes in the metabolome.

Beyond Taxonomic Analysis of Microbiomes: A Functional Approach for Revisiting Microbiome Changes in Colorectal Cancer

Colorectal cancer (CRC) is one of the most prevalent cancers in the world, especially in developed countries. In different studies, the association between CRC and dysbiosis of gut microbiome has been reported. However, most of these works focus on the taxonomic variation of the microbiome, which presents little, if any, functional insight about the reason behind and/or consequences of microbiome dysbiosis. In this study, we used a previously reported metagenome dataset which is obtained by sequencing 156 microbiome samples of healthy individuals as the control group (Co), as well as microbiome samples of patients with advanced colorectal adenoma (Ad) and colorectal carcinoma (Ca). Features of the microbiome samples have been analyzed at the level of species, as well as four functional levels, i.e., gene, KEGG orthology (KO) group, Enzyme Commission (EC) number, and reaction. It was shown that, at each of these levels, certain features exist which show significant changing trends during cancer progression. In the next step, a list of these features were extracted, which were shown to be able to predict the category of Co, Ad, and Ca samples with an accuracy of >85%. When only one group of features (species, gene, KO group, EC number, reaction) was used, KO-related features were found to be the most successful features for classifying the three categories of samples. Notably, species-related features showed the least success in sample classification. Furthermore, by applying an independent test set, we showed that these performance trends are not limited to our original dataset. We determined the most important classification features at each of the four functional levels. We propose that these features can be considered as biomarkers of CRC progression. Finally, we show that the intra-diversity of each sample at the levels of bacterial species and genes is much more than those of the KO groups, EC numbers, and reactions of that sample. Therefore, we conclude that the microbiome diversity at the species level, or gene level, is not necessarily associated with the diversity at the functional level, which again indicates the importance of KO-, EC-, and reaction-based features in metagenome analysis. The source code of proposed method is freely available from https://www.bioinformatics.org/mamed.

Comparison of Gut Microbiome in Human Colorectal Cancer in Paired Tumor and Adjacent Normal Tissues

Background

To understand the biological effect of gut microbiome on the progression of colorectal cancer (CRC), we sequenced the V3-V4 region of the 16S rRNA gene to illustrate the overall structure of microbiota in the CRC patients.

Methods

In this study, a total of 66 CRC patients were dichotomized into different groups based on the following characteristics: paired tumor and adjacent normal tissues, distal and proximal CRC segments, MMR (-) and MMR (+), different TNM staging and clinic tumor staging.

Results

By sequencing and comparing the microbial assemblages, our results indicated that 7 microbe genus (Fusobacterium, Faecalibacterium, Akkermansia, Ruminococcus2, Parabacteroides, Streptococcus, and f_Ruminococcaceae) were significantly different between tumor and adjacent normal tissues; and 5 microbe genus (Bacteroides, Fusobacterium, Faecalibacterium, Parabacteroides, and Ruminococcus2) were significantly different between distal and proximal CRC segments; only 2 microbe genus (f_Enterobacteriaceae and Granulicatella) were significantly different between MMR (-) and MMR (+); but there was no significant microbial difference were detected neither in the TNM staging nor in the clinic tumor staging.

Conclusion

All these findings implied a better understanding of the alteration in the gut microbiome, which may offer new insight into diagnosing and therapying for CRC patients.

Breath Volatile Organic Compound Profiling of Colorectal Cancer Using Selected Ion Flow-tube Mass Spectrometry

OBJECTIVE

BACKGROUND:: Breath VOCs have the potential to noninvasively diagnose cancer.

METHODS

Exhaled breath samples were collected using 2-L double-layered Nalophan bags, and were analyzed using selected-ion-flow-tube mass-spectrometry. Gold-standard test for comparison was endoscopy for luminal inspection and computed tomography (CT) to confirm cancer recurrence. Three studies were conducted: RESULTS:: CONCLUSION:: This study suggests the association of a single breath biomarker with the primary presence and recurrence of CRCa. Further multicenter validation studies are required to validate these findings.

Influence of the Gut Microbiome, Diet, and Environment on Risk of Colorectal Cancer

Researchers have discovered associations between elements of the intestinal microbiome (including specific microbes, signaling pathways, and microbiota-related metabolites) and risk of colorectal cancer (CRC). However, it is unclear whether changes in the intestinal microbiome contribute to the development of sporadic CRC or result from it. Changes in the intestinal microbiome can mediate or modify the effects of environmental factors on risk of CRC. Factors that affect risk of CRC also affect the intestinal microbiome, including overweight and obesity; physical activity; and dietary intake of fiber, whole grains, and red and processed meat. These factors alter microbiome structure and function, along with the metabolic and immune pathways that mediate CRC development. We review epidemiologic and laboratory evidence for the influence of the microbiome, diet, and environmental factors on CRC incidence and outcomes. Based on these data, features of the intestinal microbiome might be used for CRC screening and modified for chemoprevention and treatment. Integrated prospective studies are urgently needed to investigate these strategies.

Multiclass Disease Classification from Microbial Whole-Community Metagenomes

The microbiome, the community of microorganisms living within an individual, is a promising avenue for developing non-invasive methods for disease screening and diagnosis. Here, we utilize 5643 aggregated, annotated whole-community metagenomes to implement the first multiclass microbiome disease classifier of this scale, able to discriminate between 18 different diseases and healthy. We compared three different machine learning models: random forests, deep neural nets, and a novel graph convolutional architecture which exploits the graph structure of phylogenetic trees as its input. We show that the graph convolutional model outperforms deep neural nets in terms of accuracy (achieving 75% average test-set accuracy), receiver-operator-characteristics (92.1% average area-under-ROC (AUC)), and precision-recall (50% average area-under-precision-recall (AUPR)). Additionally, the convolutional net's performance complements that of the random forest, showing a lower propensity for Type-I errors (false-positives) while the random forest makes less Type-II errors (false-negatives). Lastly, we are able to achieve over 90% average top-3 accuracy across all of our models. Together, these results indicate that there are predictive, disease-specific signatures across microbiomes that can be used for diagnostic purposes.

Gene Expression Analysis of Human Papillomavirus-Associated Colorectal Carcinoma

PURPOSE

Human papillomavirus (HPV) antigens had been found in colorectal cancer (CRC) tissue, but little evidence demonstrates the association of HPV with oncogene mutations in CRC. We aim to elucidate the mutated genes that link HPV infection and CRC carcinogenesis.

METHODS

Cancerous and adjacent noncancerous tissues were obtained from CRC patients. HPV antigen was measured by using the immunohistochemical (IHC) technique. The differentially expressed genes (DEGs) in HPV-positive and HPV-negative tumor tissues were measured by using TaqMan Array Plates. The target genes were validated with the qPCR method.

RESULTS

15 (31.9%) cases of CRC patients were observed to be HPV positive, in which HPV antigen was expressed in most tumor tissues rather than in adjacent noncancerous tissues. With TaqMan Array Plates analyses, we found that 39 differentially expressed genes (DEGs) were upregulated, while 17 DEGs were downregulated in HPV-positive CRC tissues compared with HPV-negative tissues. Four DEGs (MMP-7, MYC, WNT-5A, and AXIN2) were upregulated in tumor vs. normal tissues, or adenoma vs. normal tissue in TCGA, which was overlapped with our data. In the confirmation test, MMP-7, MYC, WNT-5A, and AXIN2 were upregulated in cancerous tissue compared with adjacent noncancerous tissue. MYC, WNT-5A, and AXIN2 were shown to be upregulated in HPV-positive CRC tissues when compared to HPV-negative tissues.

CONCLUSION

HPV-encoding genome may integrate into the tumor genomes that involved in multiple signaling pathways. Further genomic and proteomic investigation is necessary for obtaining a more comprehensive knowledge of signaling pathways associated with the CRC carcinogenesis.

Changes in C-reactive protein, neopterin and lactoferrin differ after conservative and surgical weight loss in individuals with morbid obesity

C-reactive protein, neopterin and lactoferrin are biomarkers of atherosclerotic disease. We aimed to assess changes in these biomarkers after conservative and surgical weight loss interventions in individuals with morbid obesity, to evaluate associations between biomarker changes and changes in body mass index and HbA1c, and to study associations between changes in the biomarkers. C-reactive protein, neopterin and lactoferrin were measured before and after conservative weight loss intervention and bariatric surgery. Data were analysed with mixed models. 137 individuals (mean age 43 years) were included. Body mass index decreased from 42.1 kg/m² to 38.9 kg/m² after the conservative intervention, and further to 30.5 kg/m² after bariatric surgery. All biomarkers decreased after the conservative weight loss intervention. C-reactive protein and lactoferrin continued to decrease following bariatric surgery whereas neopterin remained stable. After adjustments for change in body mass index and HbA1c, all biomarkers decreased significantly after the conservative weight loss intervention, whereas none changed after bariatric surgery. There were no consistent correlations between changes in C-reactive protein, neopterin and lactoferrin. In conclusion, biomarkers of atherosclerosis decreased after weight loss interventions but had different trajectories. Neopterin, a marker related to atherosclerotic plaque stability, decreased after conservative weight loss but not following bariatric surgery.

Gut Bacteria and their Metabolites: Which One Is the Defendant for Colorectal Cancer?

Colorectal cancer (CRC) is a worldwide health concern which requires efficient therapeutic strategies. The mechanisms underlying CRC remain an essential subject of investigations in the cancer biology field. The evaluation of human microbiota can be critical in this regard, since the disruption of the normal community of gut bacteria is an important issue in the development of CRC. However, several studies have already evaluated the different aspects of the association between microbiota and CRC. The current study aimed at reviewing and summarizing most of the studies on the modifications of gut bacteria detected in stool and tissue samples of CRC cases. In addition, the importance of metabolites derived from gut bacteria, their relationship with the microbiota, and epigenetic modifications have been evaluated.

The Prevotella copri Complex Comprises Four Distinct Clades Underrepresented in Westernized Populations

Prevotella copri is a common human gut microbe that has been both positively and negatively associated with host health. In a cross-continent meta-analysis exploiting >6,500 metagenomes, we obtained >1,000 genomes and explored the genetic and population structure of P. copri. P. copri encompasses four distinct clades (>10% inter-clade genetic divergence) that we propose constitute the P. copri complex, and all clades were confirmed by isolate sequencing. These clades are nearly ubiquitous and co-present in non-Westernized populations. Genomic analysis showed substantial functional diversity in the complex with notable differences in carbohydrate metabolism, suggesting that multi-generational dietary modifications may be driving reduced prevalence in Westernized populations. Analysis of ancient metagenomes highlighted patterns of P. copri presence consistent with modern non-Westernized populations and a clade delineation time pre-dating human migratory waves out of Africa. These findings reveal that P. copri exhibits a high diversity that is underrepresented in Western-lifestyle populations.

Association of Flavonifractor plautii, a Flavonoid-Degrading Bacterium, with the Gut Microbiome of Colorectal Cancer Patients in India

This study provides novel insights on the CRC-associated microbiome of a unique cohort in India, reveals the potential role of a new bacterium in CRC, and identifies cohort-specific biomarkers, which can potentially be used in noninvasive diagnosis of CRC. The study gains additional significance, as India is among the countries with a very low incidence of CRC, and the diet and lifestyle in India have been associated with a distinct gut microbiome in healthy Indians compared to other global populations. Thus, in this study, we hypothesize a unique relationship between CRC and the gut microbiome in an Indian population.

Recently, dysbiosis in the human gut microbiome and shifts in the relative abundances of several bacterial species have been recognized as important factors in colorectal cancer (CRC). However, these studies have been carried out mainly in developed countries where CRC has a high incidence, and it is unclear whether the host-microbiome relationships deduced from these studies can be generalized to the global population. To test if the documented associations between the microbiome and CRC are conserved in a distinct context, we performed metagenomic and metabolomic association studies on fecal samples from 30 CRC patients and 30 healthy controls from two different locations in India, followed by a comparison of CRC data available from other populations. We confirmed the association of Bacteroides and other bacterial taxa with CRC that have been previously reported in other studies. However, the association of CRC with Flavonifractor plautii in Indian patients emerged as a novel finding. The plausible role of F. plautii appears to be linked with the degradation of beneficial anticarcinogenic flavonoids, which was also found to be significantly correlated with the enzymes and modules involved in flavonoid degradation within Indian CRC samples. Thus, we hypothesize that the degradation of beneficial flavonoids might be playing a role in cancer progression within this Indian cohort. We also identified 20 potential microbial taxonomic markers and 33 potential microbial gene markers that discriminate the Indian CRC from healthy microbiomes with high accuracy based on machine learning approaches.

IMPORTANCE This study provides novel insights on the CRC-associated microbiome of a unique cohort in India, reveals the potential role of a new bacterium in CRC, and identifies cohort-specific biomarkers, which can potentially be used in noninvasive diagnosis of CRC. The study gains additional significance, as India is among the countries with a very low incidence of CRC, and the diet and lifestyle in India have been associated with a distinct gut microbiome in healthy Indians compared to other global populations. Thus, in this study, we hypothesize a unique relationship between CRC and the gut microbiome in an Indian population.

Targeting Programmed Fusobacterium nucleatum Fap2 for Colorectal Cancer Therapy

Colorectal patients generally have the maximum counts of Fusobacterium nucleatum (F. nucleatum) in tumors and elevate colorectal adenomas and carcinomas, which show the lowest rate of human survival. Hence, F. nucleatum is a diagnostic marker of colorectal cancer (CRC). Studies demonstrated that targeting fusobacterial Fap2 or polysaccharide of the host epithelium may decrease fusobacteria count in the CRC. Attenuated F. nucleatum-Fap2 prevents transmembrane signals and inhibits tumorigenesis inducing mechanisms. Hence, in this review, we hypothesized that application of genetically programmed fusobacterium can be skillful and thus reduce fusobacterium in the CRC. Genetically programmed F. nucleatum is a promising antitumor strategy.

Altered Fecal Small RNA Profiles in Colorectal Cancer Reflect Gut Microbiome Composition in Stool Samples

The characteristics of microbial small RNA transcription are largely unknown, while it is of primary importance for a better identification of molecules with functional activities in the gut niche under both healthy and disease conditions. By performing combined analyses of metagenomic and small RNA sequencing (sRNA-Seq) data, we characterized both the human and microbial small RNA contents of stool samples from healthy individuals and from patients with colorectal carcinoma or adenoma. With the integrative analyses of metagenomic and sRNA-Seq data, we identified a human and microbial small RNA signature which can be used to improve diagnosis of the disease. Our analysis of human and gut microbiome small RNA expression is relevant to generation of the first hypotheses about the potential molecular interactions occurring in the gut of CRC patients, and it can be the basis for further mechanistic studies and clinical tests.

Dysbiotic configurations of the human gut microbiota have been linked to colorectal cancer (CRC). Human small noncoding RNAs are also implicated in CRC, and recent findings suggest that their release in the gut lumen contributes to shape the gut microbiota. Bacterial small RNAs (bsRNAs) may also play a role in carcinogenesis, but their role has been less extensively explored. Here, we performed small RNA and shotgun sequencing on 80 stool specimens from patients with CRC or with adenomas and from healthy subjects collected in a cross-sectional study to evaluate their combined use as a predictive tool for disease detection. We observed considerable overlap and a correlation between metagenomic and bsRNA quantitative taxonomic profiles obtained from the two approaches. We identified a combined predictive signature composed of 32 features from human and microbial small RNAs and DNA-based microbiome able to accurately classify CRC samples separately from healthy and adenoma samples (area under the curve [AUC] = 0.87). In the present study, we report evidence that host-microbiome dysbiosis in CRC can also be observed by examination of altered small RNA stool profiles. Integrated analyses of the microbiome and small RNAs in the human stool may provide insights for designing more-accurate tools for diagnostic purposes.

IMPORTANCE The characteristics of microbial small RNA transcription are largely unknown, while it is of primary importance for a better identification of molecules with functional activities in the gut niche under both healthy and disease conditions. By performing combined analyses of metagenomic and small RNA sequencing (sRNA-Seq) data, we characterized both the human and microbial small RNA contents of stool samples from healthy individuals and from patients with colorectal carcinoma or adenoma. With the integrative analyses of metagenomic and sRNA-Seq data, we identified a human and microbial small RNA signature which can be used to improve diagnosis of the disease. Our analysis of human and gut microbiome small RNA expression is relevant to generation of the first hypotheses about the potential molecular interactions occurring in the gut of CRC patients, and it can be the basis for further mechanistic studies and clinical tests.

Clustering co-abundant genes identifies components of the gut microbiome that are reproducibly associated with colorectal cancer and inflammatory bowel disease

BACKGROUND

Whole-genome "shotgun" (WGS) metagenomic sequencing is an increasingly widely used tool for analyzing the metagenomic content of microbiome samples. While WGS data contains gene-level information, it can be challenging to analyze the millions of microbial genes which are typically found in microbiome experiments. To mitigate the ultrahigh dimensionality challenge of gene-level metagenomics, it has been proposed to cluster genes by co-abundance to form Co-Abundant Gene groups (CAGs). However, exhaustive co-abundance clustering of millions of microbial genes across thousands of biological samples has previously been intractable purely due to the computational challenge of performing trillions of pairwise comparisons.

RESULTS

Here we present a novel computational approach to the analysis of WGS datasets in which microbial gene groups are the fundamental unit of analysis. We use the Approximate Nearest Neighbor heuristic for near-exhaustive average linkage clustering to group millions of genes by co-abundance. This results in thousands of high-quality CAGs representing complete and partial microbial genomes. We applied this method to publicly available WGS microbiome surveys and found that the resulting microbial CAGs associated with inflammatory bowel disease (IBD) and colorectal cancer (CRC) were highly reproducible and could be validated independently using multiple independent cohorts.

CONCLUSIONS

This powerful approach to gene-level metagenomics provides a powerful path forward for identifying the biological links between the microbiome and human health. By proposing a new computational approach for handling high dimensional metagenomics data, we identified specific microbial gene groups that are associated with disease that can be used to identify strains of interest for further preclinical and mechanistic experimentation.

Hotspots of Sequence Variability in Gut Microbial Genes Encoding Pro-Inflammatory Factors Revealed by Oligotyping

The gut microbiota has been implicated in a number of normal and disease biological processes. Recent studies have identified a subset of gut bacterial genes as potentially involved in inflammatory processes. In this work, we explore the sequence variability for some of these bacterial genes using a combination of deep sequencing and oligotyping, a data analysis application that identifies mutational hotspots in short stretches of DNA. The genes for pks island, tcpC and usp, all harbored by certain strains of E. coli and all implicated in inflammation, were amplified by PCR directly from stool samples and subjected to deep amplicon sequencing. For comparison, the same genes were amplified from individual bacterial clones. The amplicons for pks island and tcpC from stool samples showed minimal levels of heterogeneity comparable with the individual clones. The amplicons for usp from stool samples, by contrast, revealed the presence of five distinct oligotypes in two different regions. Of these, the oligotype GT was found to be present in the control uropathogenic clinical isolate and also detected in stool samples from individuals with colorectal cancer (CRC). Mutational hotspots were mapped onto the USP protein, revealing possible substitutions around Leu110, Glu114, and Arg115 in the middle of the pyocin domain (Gln110, Gln114, and Thr115 in most healthy samples), and also Arg218 in the middle of the nuclease domain (His218 in the uropathogenic strain). All of these results suggest that a level of variability within bacterial pro-inflammatory genes could explain differences in bacterial virulence and phenotype.

Colonic Mucosal Transcriptomic Changes in Patients with Long-Duration Ulcerative Colitis Revealed Colitis-Associated Cancer Pathways

BACKGROUND AND AIMS

Patients with ulcerative colitis [UC] with long disease duration have a higher risk of developing colitis-associated cancer [CAC] compared with patients with short-duration UC. The aim of this study was to identify transcriptomic differences associated with the duration of UC disease.

METHODS

We conducted transcriptome profiling on 32 colonic biopsies [11 long-duration UC, ≥20 years; and 21 short-duration UC, ≤5 years] using Affymetrix Human Transcriptome Array 2.0. Differentially expressed genes [fold change > 1.5, p < 0.05] and alternative splicing events [splicing index > 1.5, p < 0.05] were determined using the Transcriptome Analysis Console. KOBAS 3.0 and DAVID 6.8 were used for KEGG and GO analysis. Selected genes from microarray analysis were validated using qPCR.

RESULTS

There were 640 differentially expressed genes between both groups. The top ten upregulated genes were HMGCS2, UGT2A3 isoforms, B4GALNT2, MEP1B, GUCA2B, ADH1C, OTOP2, SLC9A3, and LYPD8; the top ten downregulated genes were PI3, DUOX2, VNN1, SLC6A14, GREM1, MMP1, CXCL1, TNIP3, TFF1, and LCN2. Among the 123 altered KEGG pathways, the most significant were metabolic pathways; fatty acid degradation; valine, leucine, and isoleucine degradation; the peroxisome proliferator-activated receptor signalling pathway; and bile secretion, which were previously linked with CAC. Analysis showed that 3560 genes exhibited differential alternative splicing between long- and short-duration UC. Among them, 374 were differentially expressed, underscoring the intrinsic relationship between altered gene expression and alternative splicing.

CONCLUSIONS

Long-duration UC patients have altered gene expressions, pathways, and alternative splicing events as compared with short-duration UC patients, and these could be further validated to improve our understanding of the pathogenesis of CAC.

Culture-independent studies on bacterial dysbiosis in oral and oropharyngeal squamous cell carcinoma: A systematic review

Imbalance within the resident bacterial community (dysbiosis), rather than the presence and activity of a single organism, has been proposed to be associated with, and to influence, the development and progression of various diseases; however, the existence and significance of dysbiosis in oral/oropharyngeal cancer is yet to be clearly established. A systematic search (conducted on 25/01/2018 and updated on 25/05/2018) was performed on three databases (Pubmed, Web of Science & Scopus) to identify studies employing culture-independent methods which investigated the bacterial community in oral/oropharyngeal cancer patients compared to control subjects. Of the 1546 texts screened, only fifteen publications met the pre-determined selection criteria. Data extracted from 731 cases and 809 controls overall, could not identify consistent enrichment of any particular taxon in oral/oropharyngeal cancers, although common taxa could be identified between studies. Six studies reported the enrichment of Fusobacteria in cancer at different taxonomic levels whereas four studies reported an increase in Parvimonas. Changes in microbial diversity remained inconclusive, with four studies showing a higher diversity in controls, three studies showing a higher diversity in tumors and three additional studies showing no difference between tumors and controls. Even though most studies identified a component of dysbiosis in oral/oropharyngeal cancer, methodological and analytical variations prevented a standardized summary, which highlights the necessity for studies of superior quality and magnitude employing standardized methodology and reporting. Indeed an holistic metagenomic approach is likely to be more meaningful, as is understanding of the overall metabolome, rather than a mere enumeration of the organisms present.

Metagenomic analysis of colorectal cancer datasets identifies cross-cohort microbial diagnostic signatures and a link with choline degradation

Several studies have investigated links between the gut microbiome and colorectal cancer (CRC), but questions remain about the replicability of biomarkers across cohorts and populations. We performed a meta-analysis of five publicly available datasets and two new cohorts and validated the findings on two additional cohorts, considering in total 969 fecal metagenomes. Unlike microbiome shifts associated with gastrointestinal syndromes, the gut microbiome in CRC showed reproducibly higher richness than controls (P < 0.01), partially due to expansions of species typically derived from the oral cavity. Meta-analysis of the microbiome functional potential identified gluconeogenesis and the putrefaction and fermentation pathways as being associated with CRC, whereas the stachyose and starch degradation pathways were associated with controls. Predictive microbiome signatures for CRC trained on multiple datasets showed consistently high accuracy in datasets not considered for model training and independent validation cohorts (average area under the curve, 0.84). Pooled analysis of raw metagenomes showed that the choline trimethylamine-lyase gene was overabundant in CRC (P = 0.001), identifying a relationship between microbiome choline metabolism and CRC. The combined analysis of heterogeneous CRC cohorts thus identified reproducible microbiome biomarkers and accurate disease-predictive models that can form the basis for clinical prognostic tests and hypothesis-driven mechanistic studies.

Meta-analysis of fecal metagenomes reveals global microbial signatures that are specific for colorectal cancer

Association studies have linked microbiome alterations with many human diseases. However, they have not always reported consistent results, thereby necessitating cross-study comparisons. Here, a meta-analysis of eight geographically and technically diverse fecal shotgun metagenomic studies of colorectal cancer (CRC, n = 768), which was controlled for several confounders, identified a core set of 29 species significantly enriched in CRC metagenomes (false discovery rate (FDR) < 1 × 10^-5). CRC signatures derived from single studies maintained their accuracy in other studies. By training on multiple studies, we improved detection accuracy and disease specificity for CRC. Functional analysis of CRC metagenomes revealed enriched protein and mucin catabolism genes and depleted carbohydrate degradation genes. Moreover, we inferred elevated production of secondary bile acids from CRC metagenomes, suggesting a metabolic link between cancer-associated gut microbes and a fat- and meat-rich diet. Through extensive validations, this meta-analysis firmly establishes globally generalizable, predictive taxonomic and functional microbiome CRC signatures as a basis for future diagnostics.

Diet-Related Metabolic Perturbations of Gut Microbial Shikimate Pathway-Tryptamine-tRNA Aminoacylation-Protein Synthesis in Human Health and Disease

Human gut bacterial Na(+)-transporting NADH:ubiquinone reductase (NQR) sequence is associated with Alzheimer disease (AD). Here, Alzheimer disease-associated sequence (ADAS) is further characterized in cultured spore-forming Clostridium sp. Tryptophan and NQR substrate ubiquinone have common precursor chorismate in microbial shikimate pathway. Tryptophan-derived tryptamine presents in human diet and gut microbiome. Tryptamine inhibits tryptophanyl-tRNA synthetase (TrpRS) with consequent neurodegeneration in cell and animal models. Tryptophanyl-tRNA synthetase inhibition causes protein biosynthesis impairment similar to that revealed in AD. Tryptamine-induced TrpRS gene-dose reduction is associated with TrpRS protein deficiency and cell death. In animals, tryptamine treatment results in toxicity, weight gain, and prediabetes-related hypoglycemia. Sequence analysis of gut microbiome database reveals 89% to 100% ADAS nucleotide identity in American Indian (Cheyenne and Arapaho [C&A]) Oklahomans, of which ~93% being overweight or obese and 50% self-reporting type 2 diabetes (T2D). Alzheimer disease-associated sequence occurs in 10.8% of C&A vs 1.3% of healthy American population. This observation is of considerable interest because T2D links to AD and obesity. Alzheimer disease-associated sequence prevails in gut microbiome of colorectal cancer, which linked to AD. Metabolomics revealed that tryptamine, chorismate precursor quinate, and chorismate product 4-hydroxybenzoate (ubiquinone precursor) are significantly higher, while tryptophan-containing dipeptides are lower due to tRNA aminoacylation deficiency in C&A compared with non-native Oklahoman who showed no ADAS. Thus, gut microbial tryptamine overproduction correlates with ADAS occurrence. Antibiotic and diet additives induce ADAS and tryptamine. Mitogenic/cytotoxic tryptamine cause microbial and human cell death, gut dysbiosis, and consequent disruption of host-microbe homeostasis. Present analysis of 1246 participants from 17 human gut metagenomics studies revealed ADAS in cell death diseases.

The profiles of dysbiotic microbial communities

Alterations in the human gut microbiota play an important role in disease pathogenesis. Although next-generation sequencing has provided observational evidence linking shifts in gut microbiota composition to alterations in the human host, underlying mechanisms remain elusive. Metabolites generated within complex microbial communities and at the crossroads with host cells may be able to explain the impact of the gut microbiome on human homeostasis. Emerging technologies including novel culturing protocols, microfluidic systems, engineered organoids, and single-cell imaging approaches are providing new perspectives from which the gut microbiome can be studied paving the way to new diagnostic markers and personalized therapeutic interventions.

Compositional and Functional Differences between Microbiota and Cervical Carcinogenesis as Identified by Shotgun Metagenomic Sequencing

Recent studies have reported the potential role of microbiomes in cervical disease. However, little is known about the microbiome composition and function in cervical carcinogenesis. We aimed to identify the compositional and functional alterations of cervical microbiomes in cases of cervical carcinogenesis of Korean women using shotgun metagenomic sequencing. In this study, using shotgun sequencing, we sequenced the cervical metagenomes of cervical intraneoplasia 2/3 (n = 17), cervical cancer (n = 12), and normal controls (n = 18) to identify the microbial abundances and enriched metabolic functions in cervical metagenomes. At the genus level, the microbiota of cervical cancer were differentially enriched with genera Alkaliphilus, Pseudothermotoga, and Wolbachia. Cervical intraepithelial neoplasia (CIN) 2/3 were enriched with Lactobacillus, Staphylococcus, and Candidatus Endolissoclinum. The normal group was enriched with Pseudoalteromonas and Psychrobacter. Further characterization of the functionalities of the metagenomes may suggest that six Kyoto Encyclopedia of Genes and Genomes (KEGG) orthologies (KOs) that are involved in 10 pathways are associated with an increased risk of CIN2/3 and cervical cancer. Specifically, cervical metagenomes were enriched in the course of peptidoglycan synthesis and depleted by dioxin degradation and 4-oxalocrotonate tautomerase. The Cluster of Orthologous Groups (COG) category ‘Defense mechanisms’ was depleted in cervical cancer patients. Our findings based on shotgun metagenomic sequencing suggest that cervical microbiome community compositions and their metagenomics profiles differed between cervical lesions and normal subjects. Future studies should have larger sample sizes and/or aggregate their results to have sufficient power to detect reproducible and significant associations.

Next steps in studying the human microbiome and health in prospective studies, Bethesda, MD, May 16-17, 2017

The National Cancer Institute (NCI) sponsored a 2-day workshop, "Next Steps in Studying the Human Microbiome and Health in Prospective Studies," in Bethesda, Maryland, May 16-17, 2017. The workshop brought together researchers in the field to discuss the challenges of conducting microbiome studies, including study design, collection and processing of samples, bioinformatics and statistical methods, publishing results, and ensuring reproducibility of published results. The presenters emphasized the great potential of microbiome research in understanding the etiology of cancer. This report summarizes the workshop and presents practical suggestions for conducting microbiome studies, from workshop presenters, moderators, and participants.

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.