Studies of the microbiome—the array of bacteria, fungi, viruses, and other microorganisms living in or on a given individual or environment—generate a lot of data. An investigation of the skin microbiome of people with eczema, for example, would include not only the identities of the microbes present, but also a vast amount of metadata, or data about the data, such as the sex, age, weight, and disease status of the individuals under study. Analysis tools that integrate metadata have the potential to reveal connections between the microbiome and clinical outcomes.
The School of Veterinary Medicine’s Center for Host-Microbial Interactions (CHMI) has now launched a powerful new online resource to help researchers and clinicians navigate these vast quantities of microbiome-related data, providing tools to help mine the data to identify associations that can then motivate hypothesis-driven research.
The microbiome is the array of bacteria, fungi, viruses, and other microorganisms living in or on a given individual or environment.
MicrobiomeDB launched this week, an effort spearheaded by Penn Vet’s Daniel Beiting, research assistant professor and technical director of CHMI. The idea for the database emerged from Beiting’s time as a postdoctoral researcher in the lab of David Roos, the E. Otis Kendall Professor of Biology in the School of Arts & Sciences, who directs the Eukaryotic Pathogens Database, a massive collection of genomic information about disease-causing microorganisms.
“In my first few years at Penn Vet, it hit me that a lot of the excellent tools that David and the entire EuPathDB group had developed could be applied to the kinds of questions that microbiome researchers would want to ask,” says Beiting. “Part of the success of EuPathDB stems from strong support from the end-users—the community of scientists that study pathogen genomics. If we can get the same type of ‘buy-in’ from the community of microbiome researchers, we could develop something truly transformative for the field.”
Thus began a collaboration. Beiting has been working closely with Roos and his team of developers to create a user-friendly website in the mold of EuPathDB that would be responsive and valuable to the needs of scientists interested in probing the microbiome.
What sets MicrobiomeDB apart from some other web-based applications, Beiting says, is that, beyond just offering a place to store data, it offers an analytical platform that enables users to mine their own data, as well as see how their data compares to that of other researchers who may be studying related microbes or diseases using a variety of visualization tools.
Already, the site has more than 14,000 samples loaded into the database, some from human studies, others from animal species or environmental studies, with thousands more set to be added soon. And it will continue to grow.
Sample queries on the site give researchers examples of the ways the database can be used. For example, “What is the influence of diet on the establishment of the infant gut microbiome?” and, “Does having a dog influence the microbial environment in the home?”
Beiting says his goal is to make it easier for busy clinicians and scientists to quickly parse microbiome data, generate worthwhile hypotheses, and share the results of their mining, all without having to get into the details of software programming.
“We look forward to people getting engaged and giving us feedback to make this the most useful resource possible for them,” he says.