Realizing the potential of the microbiome: Q&A with Alex Mitchell

Alex Mitchell
Alex recently joined Eagle Genomics as Senior Bioinformatician. In this article he talks to us about how he came to specialize in the microbiome and makes some predictions about its potential impact.


Q: What is your role at Eagle Genomics?

I am a Senior Bioinformatician in the BioData Innovation team, which means I am involved in a wide range of activities. One day I might be advising on which components should be put together to create an analysis pipeline for microbiome data. The next, I might be working on an update to our data model, to ensure it can handle all of the different types of information that we want to bring together. My overall role is really to make sure Eagle’s e[datascientist] software platform evolves in such a way that it meets (or, better yet, surpasses) our customers’ needs.

Q: What is your professional background and how did it lead you to this role?

My doctorate was in pharmacology, putting in long hours in the laboratory running assays. As my career progressed, I found myself using a lot of different bioinformatics tools for data analysis and getting more and more interested in that field. As a result, you could say I fell down the bioinformatics rabbit hole. I ended up working on a range of different projects, from text mining the biomedical literature, to protein function prediction, which in turn led to me taking up a position at the European Bioinformatics Institute (EMBL-EBI). There, I started applying my function prediction expertise to microbiome research. With new sequencing technologies granting us access to genomes that we have never seen before, the big questions are: what are these organisms, what are they doing and how are they doing it? Looking at the proteins they express and trying to understand their functions goes some way towards answering those questions. During my time at EMBL-EBI, I helped build one of the world’s largest resources of analysed microbiome data to try to address this.

Q: Where do you see discoveries in microbiome having the most impact?

It might be quicker to list the areas where microbiome discoveries won’t have an impact! The potential is vast. Looking at the human microbiome alone, that represents an entire second genome that we all carry around with us, which is much more diverse (and open to manipulation) than our own. A better understanding of it could help with everything from personalised diet (working out what to eat and when, for optimal health), to better skin care and hair care benefits, and improved oral health. Then there is the diagnosis of particular conditions or diseases through the identification of biomarkers. And potential treatments, possibly in the form of microbial cocktails or precision editing of microbial genomes - medicine in the age of the microbiome could look quite different to the way it looks now.

Outside of human health, microbiome discoveries could impact agriculture and animal welfare, through improved crop yields, superior drought and disease resistance, and production of better animal feeds. Then there are the wider environmental impacts, with the potential to monitor, or even clean up, pollution. There is some really interesting work currently going on in this field in terms of plastics in the world’s oceans and whether the microbiome of the ‘plastisphere’ could help digest it. On a related note, there is huge potential for microbiome research in energy production, through the conversion of biomass into liquid fuels, hydrogen, methane or even electricity. In essence, wherever microbes are involved, there is potential for microbiome research to have an impact. And microbes are involved in almost everything!

Q: How can we harness the potential of growing volumes of microbiome data?

Data integration is really one of the key things here. Bringing data sets together and combining them with other types of information gives us the bigger picture. For example, combining human gut microbiome data with information on individual subjects in terms of their diet, clinical observations and metabolite data could give us really deep insights into what is going on in diseases such as diabetes, helping us design better treatments. However, one of the issues is that as we add in more and more information, the picture gets too big for us to understand everything that is going on. This is why we need technologies such as AI to guide us. Integrating, visualising and exploring such data are some of the areas where the e[datascientist] platform can help.

Q: What’s the most exciting thing about working for Eagle Genomics?

For me, it is the chance to work on projects and build products that have real effects out in the world, whether that is improving the diagnosis of a disease, or helping design a more effective toothpaste. It is a really great feeling to be able to point at something tangible and think ‘I contributed to that’, even if it was only in a small way. At Eagle Genomics, we have the range of subject matter experts, software developers, statisticians and AI professionals to make that possible.

Q: Tell us one thing we couldn’t find out about you on Google.

I may not have worked in a lab for quite some time, but I still put my skills to use making home brew beer. My set up is fairly small scale at present, but the end product is pretty decent.