The mucosal microbiome of inflammatory bowel diseases

The human microbiome is the diverse community of micro-organisms that live with humans. The gut microbiome contains the densest collection of microbial cells in the body and has been described as functioning as an organ. Alterations in these microbial communities are associated with disease. This work provides a new methodology for the taxonomic assignment of 16S rRNA gene sequencing data, then utilises this and other cutting edge techniques to elucidate the mucosal associated microbiome in Inflammatory Bowel Disease and finally examines the viability of using mucosal samples for shotgun metagenomics or metatranscriptomics. Taxonomic classification is a corner stone for the characterisation of microbial communities, but currently many studies are limited to genus level classification. Thus, we developed SPINGO, a flexible and stand-alone software dedicated to species level assignment of 16S rRNA gene sequences. SPINGO outperforms other methods in terms of classification accuracy, and is as fast or faster than those that have higher error rates. Crohn’s Disease (CD) and Ulcerative Colitis (UC) are Inflammatory Bowel Diseases (IBD) which cause inflammation along the gastrointestinal tract of millions of people worldwide. By collecting paired colonic pinch biopsies from inflamed and noninflamed tissue from IBD patients and paired healthy biopsies from healthy individuals we reveal a gradient between IBD and healthy controls that is associated with inflammation. Differential abundance analysis reveals a total of 89 taxa in this cohort to be different between CD and UC when compared to healthy controls. Clustering of these samples reveals discrete groups which may provide a frame-work for sub-typing IBD based on the microbiota. Microbiome scientists frequently rely on faecal samples as a proxy for the colonic environment despite numerous studies finding that it is not completely representative. Here we assess the potential of using colonic pinch biopsies for profiling the metagenome and metatranscriptome of the mucosal associated microbiota. We find that current methodologies are not capable of adequately separating microbial and human DNA or RNA resulting in as few as 1 – 2% of microbial reads after sequencing.

Grantor dc:publisher

University College Cork

Year dc:date.issued

2016

Author dc:creator

• Ryan, Feargal J.

Advisor dc:contributor.advisor

• Claesson, Marcus

• Microbiome
• Bioinformatics
• Metagenomics
• Inflammatory bowel disease

Statement dc:rights

• © 2016, Feargal Ryan.

Licence dc:rights.uri

• http://creativecommons.org/licenses/by-nc-nd/3.0/

Language dc:language.iso

en

Handle dc:identifier.uri

https://hdl.handle.net/10468/3566

OAI identifier oai:identifier

oai:cora.ucc.ie:10468/3566