Understanding the role of Fusobacterium nucleatum metabolism in colon cancer initiation and progression

Poster (2020, February 22)

Accumulating evidence suggests that dysbiosis, a state of pathological imbalance in the human gut microbiome, is present in patients suffering from colorectal cancer (CRC). 16S rRNA gene sequencing, as ... [more ▼]

Accumulating evidence suggests that dysbiosis, a state of pathological imbalance in the human gut microbiome, is present in patients suffering from colorectal cancer (CRC). 16S rRNA gene sequencing, as well as metagenomic and metatranscriptomic analyses, identified specific bacteria being associated with CRC. Among others, Fusobacterium ssp. have been found to directly interact with cancer or immune cells of their host. However, only a limited number of CRC-associated microbes have been examined for host-microbial interactions and, as such, the role of bacteria in the etiology of the disease remains largely elusive. Our aim is the development of predictive and experimental models that allow to not only study the host-microbiota interactions but are also amenable to high-throughput experimentation and large-scale omics-data integration. Ultimately, such models should help to get from meta-omics to cellular mechanism and, moreover, serve as tools for reproducible analyses of host-microbial interaction mechanisms of on a transcriptomic, proteomic, and metabolomic level. Our research proposes an integrative study approach allowing us to bridge meta-omics with functional mechanisms by focusing on the interaction taking place between F. nucleatum and patient-derived CRC cells. [less ▲]

Microbiome-derived Multi-omicBiomarkers for Early-stage Detection and Stratification of Parkinson's Disease

Poster (2018, October)

Birth mode is associated with earliest strain-conferred gut microbiome functions and immunostimulatory potential

in Nature Communications (2018)

A comprehensive metatranscriptome analysis pipeline and its validation using human small intestine microbiota datasets

in BMC genomics (2013), 14(1), 530

Background Next generation sequencing (NGS) technologies can be applied in complex microbial ecosystems for metatranscriptome analysis by employing direct cDNA sequencing, which is known as RNA sequencing ... [more ▼]

Background Next generation sequencing (NGS) technologies can be applied in complex microbial ecosystems for metatranscriptome analysis by employing direct cDNA sequencing, which is known as RNA sequencing (RNA-seq). RNA-seq generates large datasets of great complexity, the comprehensive interpretation of which requires a reliable bioinformatic pipeline. In this study, we focus on the development of such a metatranscriptome pipeline, which we validate using Illumina RNA-seq datasets derived from the small intestine microbiota of two individuals with an ileostomy. Results The metatranscriptome pipeline developed here enabled effective removal of rRNA derived sequences, followed by confident assignment of the predicted function and taxonomic origin of the mRNA reads. Phylogenetic analysis of the small intestine metatranscriptome datasets revealed a strong similarity with the community composition profiles obtained from 16S rDNA and rRNA pyrosequencing, indicating considerable congruency between community composition (rDNA), and the taxonomic distribution of overall (rRNA) and specific (mRNA) activity among its microbial members. Reproducibility of the metatranscriptome sequencing approach was established by independent duplicate experiments. In addition, comparison of metatranscriptome analysis employing single- or paired-end sequencing methods indicated that the latter approach does not provide improved functional or phylogenetic insights. Metatranscriptome functional-mapping allowed the analysis of global, and genus specific activity of the microbiota, and illustrated the potential of these approaches to unravel syntrophic interactions in microbial ecosystems. Conclusions A reliable pipeline for metatransciptome data analysis was developed and evaluated using RNA-seq datasets obtained for the human small intestine microbiota. The set-up of the pipeline is very generic and can be applied for (bacterial) metatranscriptome analysis in any chosen niche. [less ▲]