Dataset Information

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

ABSTRACT: 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.

SUBMITTER: Tarallo S

PROVIDER: S-EPMC6749105 | biostudies-literature | 2019 Sep

REPOSITORIES: biostudies-literature

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

Tarallo Sonia S Ferrero Giulio G Gallo Gaetano G Francavilla Antonio A Clerico Giuseppe G Realis Luc Alberto A Manghi Paolo P Thomas Andrew Maltez AM Vineis Paolo P Segata Nicola N Pardini Barbara B Naccarati Alessio A Cordero Francesca F

mSystems 20190917 5

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 fro ...[more]

PMID: 31530647

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Project description:AimThe goal of this study is to compare microbiome composition in three different sample types in women, namely stool brought from home vs. solid stool samples obtained at the time of an unprepped sigmoidoscopy vs. biopsies of the colonic mucosa at the time of an unprepped sigmoidoscopy, using alpha- and beta-diversity metrics following bacterial 16S rRNA sequencing. The findings may have relevance to health and disease states in which bacterial metabolism has a significant impact on molecules/metabolites that are recirculated between the gut lumen and mucosa and systemic circulation, such as estrogens (as in breast cancer) or bile acids.MethodsConcomitant at-home-collected stool, endoscopically-collected stool, and colonic biopsy samples were collected from 48 subjects (24 breast cancer, 24 control.) After 16S rRNA sequencing, an amplicon sequence variant (ASV) based approach was used to analyze the data. Alpha diversity metrics (Chao1, Pielou's Evenness, Faith PD, Shannon, and Simpson) and beta diversity metrics (Bray-Curtis, Weighted and Unweighted Unifrac) were calculated. LEfSe was used to analyze differences in the abundance of various taxa between sample types.ResultsAlpha and beta diversity metrics were significantly different between the three sample types. Biopsy samples were different than stool samples in all metrics. The highest variation in microbiome diversity was noted in the colonic biopsy samples. At-home and endoscopically-collected stool showed more similarities in count-based and weighted beta diversity metrics. There were significant differences in rare taxa and phylogenetically-diverse taxa between the two types of stool samples. Generally, there were higher levels of Proteobacteria in biopsy samples, with significantly more Actinobacteria and Firmicutes in stool (all p < 0.001, q-value < 0.05). Overall, there was a significantly higher relative abundance of Lachnospiraceae and Ruminococcaceae in stool samples (at-home collected and endoscopically-collected) and higher abundances of Tisserellaceae in biopsy samples (all p < 0.001, q-value < 0.05).ConclusionOur data shows that different sampling methods can impact results when looking at the composition of the gut microbiome using ASV-based approaches.

Project description:In ruminants, the digestion and utilization of dietary proteins are closely linked to the bacterial populations that are present in the gastrointestinal tract. In the present study, 16S rDNA sequencing, together with a metagenomic strategy was used to characterize the fecal bacteria of ewes in the early lactation stage after feeding with three levels of dietary proteins 8.58%, 10.34%, and 13.93%, in three different groups (H_1), (H_m) and (H_h), respectively. A total of 376,278,516 clean data-points were obtained by metagenomic sequencing. Firmicutes and Bacteroidetes were the dominant phyla, regardless of the dietary protein levels. In the H_h group, the phyla Proteobacteria, Caldiserica, and Candidatus_Cryosericota were less abundant than those in the H_I group. In contrast, Lentisphaerae, Chlamydiae, and Planctomycetes were significantly more abundant in the H_h group. Some genera, such as Prevotella, Roseburia, and Firmicutes_unclassified, were less abundant in the H_h group than those in the H_I group. In contrast, Ruminococcus, Ruminococcaceae_noname, Anaerotruncus, Thermotalae, Lentisphaerae_noname, and Paraprevotella were enriched in the H_h group. The acquired microbial genes were mainly clustered into biological processes; molecular functions; cytosol; cellular components; cytoplasm; structural constituents of ribosomes; plasma membranes; translation; and catalytic activities. 205987 genes were significantly enriched in the H_h group. In contrast, 108129 genes were more abundant in the H_I group. Our findings reveal that dynamic changes in fecal bacteria and their genes are strongly influenced by the levels of dietary proteins. We discovered that differentially expressed genes mainly regulate metabolic activity and KEGG demonstrated the primary involvement of these genes in the metabolism of carbohydrates, amino acids, nucleotides, and vitamins. Additionally, genes responsible for metabolism were more abundant in the H_h group. Investigating fecal bacterial characteristics may help researchers develop a dietary formula for lactating ewes to optimize the growth and health of ewes and lambs.

Dataset Information

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

Publications

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

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