Longitudinal Multi-omics Reveals Subset-Specific Mechanisms Underlying Irritable Bowel Syndrome.

The gut microbiome has been implicated in multiple human chronic gastrointestinal (GI) disorders. Determining its mechanistic role in disease has been difficult due to apparent disconnects between animal and human studies and lack of an integrated multi-omics view of disease-specific physiological changes. We integrated longitudinal multi-omics data from the gut microbiome, metabolome, host epigenome, and transcriptome in the context of irritable bowel syndrome (IBS) host physiology. We identified IBS subtype-specific and symptom-related variation in microbial composition and function. A subset of identified changes in microbial metabolites correspond to host physiological mechanisms that are relevant to IBS. By integrating multiple data layers, we identified purine metabolism as a novel host-microbial metabolic pathway in IBS with translational potential. Our study highlights the importance of longitudinal sampling and integrating complementary multi-omics data to identify functional mechanisms that can serve as therapeutic targets in a comprehensive treatment strategy for chronic GI diseases. VIDEO ABSTRACT.

Multi-Omics Analyses Show Disease, Diet, and Transcriptome Interactions With the Virome.

BACKGROUND & AIMS: The gut virome includes eukaryotic viruses and bacteriophages that can shape the gut bacterial community and elicit host responses. The virome can be implicated in diseases, such as irritable bowel syndrome (IBS), where gut bacteria play an important role in pathogenesis. We provide a comprehensive and longitudinal characterization of the virome, including DNA and RNA viruses and paired multi-omics data in a cohort of healthy subjects and patients with IBS. METHODS: We selected 2 consecutive stool samples per subject from a longitudinal study cohort and performed metagenomic sequencing on DNA and RNA viruses after enriching for viral-like particles. Viral sequence abundance was evaluated over time, as well as in the context of diet, bacterial composition and function, metabolite levels, colonic gene expression, host genetics, and IBS subsets. RESULTS: We found that the gut virome was temporally stable and correlated with the colonic transcriptome. We identified IBS-subset-specific changes in phage populations; Microviridae, Myoviridae, and Podoviridae species were elevated in diarrhea-predominant IBS, and other Microviridae and Myoviridae species were elevated in constipation-predominant IBS compared to healthy controls. We identified correlations between subsets of the virome and bacterial composition (unclassifiable "dark matter" and phages) and diet (eukaryotic viruses). CONCLUSIONS: We found that the gut virome is stable over time but varies among subsets of patients with IBS. It can be affected by diet and potentially influences host function via interactions with gut bacteria and/or altering host gene expression.

Gut microbiota diversity across ethnicities in the United States.

Composed of hundreds of microbial species, the composition of the human gut microbiota can vary with chronic diseases underlying health disparities that disproportionally affect ethnic minorities. However, the influence of ethnicity on the gut microbiota remains largely unexplored and lacks reproducible generalizations across studies. By distilling associations between ethnicity and differences in two US-based 16S gut microbiota data sets including 1,673 individuals, we report 12 microbial genera and families that reproducibly vary by ethnicity. Interestingly, a majority of these microbial taxa, including the most heritable bacterial family, Christensenellaceae, overlap with genetically associated taxa and form co-occurring clusters linked by similar fermentative and methanogenic metabolic processes. These results demonstrate recurrent associations between specific taxa in the gut microbiota and ethnicity, providing hypotheses for examining specific members of the gut microbiota as mediators of health disparities.

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.

Identification of shared and disease-specific host gene-microbiome associations across human diseases using multi-omic integration.

While gut microbiome and host gene regulation independently contribute to gastrointestinal disorders, it is unclear how the two may interact to influence host pathophysiology. Here we developed a machine learning-based framework to jointly analyse paired host transcriptomic (n = 208) and gut microbiome (n = 208) profiles from colonic mucosal samples of patients with colorectal cancer, inflammatory bowel disease and irritable bowel syndrome. We identified associations between gut microbes and host genes that depict shared as well as disease-specific patterns. We found that a common set of host genes and pathways implicated in gastrointestinal inflammation, gut barrier protection and energy metabolism are associated with disease-specific gut microbes. Additionally, we also found that mucosal gut microbes that have been implicated in all three diseases, such as Streptococcus, are associated with different host pathways in each disease, suggesting that similar microbes can affect host pathophysiology in a disease-specific manner through regulation of different host genes. Our framework can be applied to other diseases for the identification of host gene-microbiome associations that may influence disease outcomes.

The gut microbiome in konzo.

Konzo, a distinct upper motor neuron disease associated with a cyanogenic diet and chronic malnutrition, predominately affects children and women of childbearing age in sub-Saharan Africa. While the exact biological mechanisms that cause this disease have largely remained elusive, host-genetics and environmental components such as the gut microbiome have been implicated. Using a large study population of 180 individuals from the Democratic Republic of the Congo, where konzo is most frequent, we investigate how the structure of the gut microbiome varied across geographical contexts, as well as provide the first insight into the gut flora of children affected with this debilitating disease using shotgun metagenomic sequencing. Our findings indicate that the gut microbiome structure is highly variable depending on region of sampling, but most interestingly, we identify unique enrichments of bacterial species and functional pathways that potentially modulate the susceptibility of konzo in prone regions of the Congo.

Interactions between the gut microbiome and host gene regulation in cystic fibrosis.

BACKGROUND: Cystic fibrosis is the most common autosomal recessive genetic disease in Caucasians. It is caused by mutations in the CFTR gene, leading to poor hydration of mucus and impairment of the respiratory, digestive, and reproductive organ functions. Advancements in medical care have led to markedly increased longevity of patients with cystic fibrosis, but new complications have emerged, such as early onset of colorectal cancer. Although the pathogenesis of colorectal cancer in cystic fibrosis remains unclear, altered host-microbe interactions might play a critical role. To investigate this, we characterized changes in the microbiome and host gene expression in the colonic mucosa of cystic fibrosis patients relative to healthy controls, and identified host gene-microbiome interactions in the colon of cystic fibrosis patients. METHODS: We performed RNA-seq on colonic mucosa samples from cystic fibrosis patients and healthy controls to determine differentially expressed host genes. We also performed 16S rRNA sequencing to characterize the colonic mucosal microbiome and identify gut microbes that are differentially abundant between patients and healthy controls. Lastly, we modeled associations between relative abundances of specific bacterial taxa in the gut mucosa and host gene expression. RESULTS: We find that 1543 genes, including CFTR, show differential expression in the colon of cystic fibrosis patients compared to healthy controls. These genes are enriched with functions related to gastrointestinal and colorectal cancer, such as metastasis of colorectal cancer, tumor suppression, p53, and mTOR signaling pathways. In addition, patients with cystic fibrosis show decreased gut microbial diversity, decreased abundance of butyrate producing bacteria, such as Ruminococcaceae and Butyricimonas, and increased abundance of other taxa, such as Actinobacteria and Clostridium. An integrative analysis identified colorectal cancer-related genes, including LCN2 and DUOX2, for which gene expression is correlated with the abundance of colorectal cancer-associated bacteria, such as Ruminococcaceae and Veillonella. CONCLUSIONS: In addition to characterizing host gene expression and mucosal microbiome in cystic fibrosis patients, our study explored the potential role of host-microbe interactions in the etiology of colorectal cancer in cystic fibrosis. Our results provide biomarkers that may potentially serve as targets for stratifying risk of colorectal cancer in patients with cystic fibrosis.

Population dynamics of the human gut microbiome: change is the only constant.

Characterization of the temporal dynamics of the human gut microbiome is crucial for understanding its role in modulating host health. Two recent studies explored the genetic diversity of gut microbes and unraveled extensive longitudinal dynamics within the host that is driven by natural selection.

Transposon mutagenesis screen in mice identifies TM9SF2 as a novel colorectal cancer oncogene.

New therapeutic targets for advanced colorectal cancer (CRC) are critically needed. Our laboratory recently performed an insertional mutagenesis screen in mice to identify novel CRC driver genes and, thus, potential drug targets. Here, we define Transmembrane 9 Superfamily 2 (TM9SF2) as a novel CRC oncogene. TM9SF2 is an understudied protein, belonging to a well conserved protein family characterized by their nine putative transmembrane domains. Based on our transposon screen we found that TM9SF2 is a candidate progression driver in digestive tract tumors. Analysis of The Cancer Genome Atlas (TCGA) data revealed that approximately 35% of CRC patients have elevated levels of TM9SF2 mRNA, data we validated using an independent set of CRC samples. RNAi silencing of TM9SF2 reduced CRC cell growth in an anchorage-independent manner, a hallmark of cancer. Furthermore, CRISPR/Cas9 knockout of TM9SF2 substantially diminished CRC tumor fitness in vitro and in vivo. Transcriptome analysis of TM9SF2 knockout cells revealed a potential role for TM9SF2 in cell cycle progression, oxidative phosphorylation, and ceramide signaling. Lastly, we report that increased TM9SF2 expression correlates with disease stage and low TM9SF2 expression correlate with a more favorable relapse-free survival. Taken together, this study provides evidence that TM9SF2 is a novel CRC oncogene.

Distinct microbes, metabolites, and ecologies define the microbiome in deficient and proficient mismatch repair colorectal cancers.

BACKGROUND: Links between colorectal cancer (CRC) and the gut microbiome have been established, but the specific microbial species and their role in carcinogenesis remain an active area of inquiry. Our understanding would be enhanced by better accounting for tumor subtype, microbial community interactions, metabolism, and ecology. METHODS: We collected paired colon tumor and normal-adjacent tissue and mucosa samples from 83 individuals who underwent partial or total colectomies for CRC. Mismatch repair (MMR) status was determined in each tumor sample and classified as either deficient MMR (dMMR) or proficient MMR (pMMR) tumor subtypes. Samples underwent 16S rRNA gene sequencing and a subset of samples from 50 individuals were submitted for targeted metabolomic analysis to quantify amino acids and short-chain fatty acids. A PERMANOVA was used to identify the biological variables that explained variance within the microbial communities. dMMR and pMMR microbial communities were then analyzed separately using a generalized linear mixed effects model that accounted for MMR status, sample location, intra-subject variability, and read depth. Genome-scale metabolic models were then used to generate microbial interaction networks for dMMR and pMMR microbial communities. We assessed global network properties as well as the metabolic influence of each microbe within the dMMR and pMMR networks. RESULTS: We demonstrate distinct roles for microbes in dMMR and pMMR CRC. Bacteroides fragilis and sulfidogenic Fusobacterium nucleatum were significantly enriched in dMMR CRC, but not pMMR CRC. These findings were further supported by metabolic modeling and metabolomics indicating suppression of B. fragilis in pMMR CRC and increased production of amino acid proxies for hydrogen sulfide in dMMR CRC. CONCLUSIONS: Integrating tumor biology and microbial ecology highlighted distinct microbial, metabolic, and ecological properties unique to dMMR and pMMR CRC. This approach could critically improve our ability to define, predict, prevent, and treat colorectal cancers.

HOMINID: a framework for identifying associations between host genetic variation and microbiome composition.

Recent studies have uncovered a strong effect of host genetic variation on the composition of host-associated microbiota. Here, we present HOMINID, a computational approach based on Lasso linear regression, that given host genetic variation and microbiome taxonomic composition data, identifies host single nucleotide polymorphisms (SNPs) that are correlated with microbial taxa abundances. Using simulated data, we show that HOMINID has accuracy in identifying associated SNPs and performs better compared with existing methods. We also show that HOMINID can accurately identify the microbial taxa that are correlated with associated SNPs. Lastly, by using HOMINID on real data of human genetic variation and microbiome composition, we identified 13 human SNPs in which genetic variation is correlated with microbiome taxonomic composition across body sites. In conclusion, HOMINID is a powerful method to detect host genetic variants linked to microbiome composition and can facilitate discovery of mechanisms controlling host-microbiome interactions.

A Semantic Web-based System for Mining Genetic Mutations in Cancer Clinical Trials.

Textual eligibility criteria in clinical trial protocols contain important information about potential clinically relevant pharmacogenomic events. Manual curation for harvesting this evidence is intractable as it is error prone and time consuming. In this paper, we develop and evaluate a Semantic Web-based system that captures and manages mutation evidences and related contextual information from cancer clinical trials. The system has 2 main components: an NLP-based annotator and a Semantic Web ontology-based annotation manager. We evaluated the performance of the annotator in terms of precision and recall. We demonstrated the usefulness of the system by conducting case studies in retrieving relevant clinical trials using a collection of mutations identified from TCGA Leukemia patients and Atlas of Genetics and Cytogenetics in Oncology and Haematology. In conclusion, our system using Semantic Web technologies provides an effective framework for extraction, annotation, standardization and management of genetic mutations in cancer clinical trials.