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Concepts of Graph Theory Applied to the Human Microbiome

Periodic Reporting for period 1 - GRAHAM (Concepts of Graph Theory Applied to the Human Microbiome)

Reporting period: 2018-11-01 to 2020-10-31

The human microbiota - the bacteria, fungi, parasites, and small eukaryotes that live on and in the human body - play important roles in our health. Changes (or disruptions) to these communities have been linked with diseases that include irritable bowel syndrome (IBS), inflammatory bowel disease (IBD), obesity, and certain cancers. However, with the software tools currently available to microbiome researchers, its hard to pinpoint the specific changes (i.e. to a particular species, strain, gene, or even a mutation within a gene) that occur in these communities when we compare samples from healthy and diseased states. It is the goal of this Fellowship to develop, test, and use software to better allow for the elucidation of the changes to the microbial communities that drive these disease states.

The goals of this Fellowship are important for society because they aim to directly affect human health in the longterm. By better understanding how human microbial communities are implicated in various disease states, we gain the potential to better treat these diseases. For example, if we better understand that a specific set of strains is missing from a microbial community, we could think about longterm strategies to replenish these strains using probiotics, dietary intervention, or pharmaceuticals.

The overall objective is to better understand how the microbes that live on and in us interplay with the human body to drive disease, or as a consequence of various disorders.
A manuscript which covers the aims of WP1 and WP2 was published in February 2020. This manuscript describes a piece of software, called Coinfinder, which identifies gene-gene relationships within microbial strains. The manuscript also describes the testing of this software on publicly-available microbial strains. The software is open-source and can be found on Github (

Ongoing research includes expanding this software to identify gene-strain relationships within microbial communities, and applying these software to publicly-available datasets including one of 215 Pseudomonas aeruginosa strains (manuscript currently in review and available as a pre-print on bioRxiv: and another of roughly 9,000 strains from all types of human-associated bacteria (manuscript in preparation).

These results were disseminated at 10 national/international conferences, 2 invited seminars at academic institutions, as well as to public and internal academic outreach events.
"The results of this project are ongoing; however, to-date they have been presented at at least 3 International conferences, and accepted for publication in 1 journal (manuscript being processed for publication). I have also written a perspective article on the subject of gene transfers in microbial strains with my colleagues (manuscript currently submitted for peer-review), and have been successful in being awarded future funding as part of an internal Fellowship to continue my scientific career following this specific project.

I have contributed to public outreach events throughout this Fellowship, including as a panel member at a local Festival of Science and Curiosity speaking as an expert on human microbiome research and answering questions on recent ""Science in the News"" stories. I have also particated in outreach events specifically focussed on current students and their interest in continuing their career in the field of bioinformatic research."
An example output from the software creates in WP1 and WP2, called coinfinder.