Fusobacterium nucleatum(Fn) is a common bacterial member of the human oral microbiome—and it is an opportunist. When Fn is found elsewhere in the human body, the microbe is typically associated with disease, and colorectal cancer (CRC) is one such disease. In fact, the presence of Fn in the tissues can often predict a poor outcome. Unfortunately, we don’t know much about how Fn causes disease, and whether all of the other microbes present in the colon, the colonic ‘microbiota’, influence this process. To make a start in understanding disease processes, scientists often use animal or tissue culture models, such as mice. In the case of mice, we don’t yet understand whether Fn affects these animals in the same way it does humans. To address this, the first part of my research is aimed at understanding how well the mouse model of Fn disease matches what happens in human disease, at a molecular level. To do this, I will use cultured mouse cells and the equivalent human cells and infect them with Fn, then track the effects of infection at a molecular level using microscopy, to visualize the cells, and a technique called ‘RNA-seq’, which allows us to see how the cells are behaving.
The next part of my project is to understand how Fn might be influenced in its ability to cause disease by determining whether the colonic microbiota plays a role in infection. Members of the microbiota may be neutral bystanders to the process of Fn infection, but alternatively they may influence Fn by either helping or hindering the pathogenic process. I will carry out infection experiments in the presence of absence of selected microbes from the colon, and from this I should be able to see if there are certain microbes that, when present, may alter the course of Fn mediated disease.
Finally, since it is known that microbes communicate with each other using a chemical language, I am interested to find out whether Fn can respond to the language of the gut microbiota alone, and whether this is enough to alter the cause of infection. I will culture whole microbial ecosystems from the colons of both diseased and healthy people using a customized apparatus called a ‘Robogut’. The Robogut mimics the human colonic environment, allowing us to grow most of the microbes present in a human colon, using, for example, poop as a starting point. Once the ecosystems are growing well, I will harvest some of this material and extract the molecules from the sample, without the microbes, and use this to see whether Fn can respond to this chemical language alone. If it does, there is great value in understanding which molecules Fn responds to in particular. This, and the outcomes of my other work will help in the development of novel therapies, diagnostic techniques or prevention strategies for CRC.