RESEARCH
Badlands Nat'l Park
In my research, I aim to understand how bacteria interact with their environments, pursuing a molecular explanation for the phenomena that define these relationships.
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We use both computational ("dry") and experimental ("wet") methods to tackle these questions, and my lab space reflects this by featuring dedicated, but adjacent, spaces for both pursuits. Our tools therefore range from Python and R to pipettes and mass spectrometers.
Go to Publications
CURRENT PROJECTS
Computational profiling of secondary metabolites in complex bacterial communities
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Next-generation DNA sequencing has given us unprecedented access to microbial diversity at a genomic level. A major challenge in the field is interpreting these data to learn how microbes are behaving and effecting change (or, if they are just signals/markers of some other biological process). We are developing open source tools that will enable researchers to identify biosynthetic pathways associated with phenotypes of interest. In some cases, these pathways have known products; in other cases, the products are completely unknown!
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We have used these techniques to show differences in metabolic product potential several human diseases, with more on the way. Three examples (see Publications for citations):
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Putative biosynthetic profiles distinguish protective from disease-associated Enterococcus species, as observed in hematopoietic stem cell transplant patients.
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Multiple secondary metabolite pathways are enriched in mice treated with antibiotics in a type I diabetes susceptibility study.
Data Visualization
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Something that's always percolating in the background is how to improve data visualization in "big data" studies like microbiome research. How do we communicate the data truthfully, clearly, and efficiently? Put another way, how to bring some Edward Tufte to microbiome analysis. In our work, most of this is performed in R. For example, I recently came up with a way to summarize the difficult-to-interpret Procrustes rotation analysis that is used not infrequently in microbiome studies. Check it out on GitHub here, and see it applied in Vangay et al. (2018) Cell.
Primate microbial biodiversity
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With my collaborator Jonathan Clayton, DVM PhD (UNebraska-Omaha), we are studying several aspects of non-human primate microbial communities. These projects include both wild and zoo-resident primates, and include fascinating hypotheses and explorations into the dynamics of microbial uptake and transfer and unexplored magnitudes of biodiversity, among others; the findings may have implications in conservation, evolutionary biology, human and non-human primate health, biochemistry and metabolism, biotechnology, and beyond. We have some very cool work in the pipeline!
Collaborative microbiome analyses
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One of the great parts of working in microbiome data analysis is the opportunity to collaborate on awesomely broad topics and constantly learn about fascinating new biology related to microorganisms. A few projects that we are working on:
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Chemotherapy and dysbiosis in HCT patients​
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Small intestine microbial communities​
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Gastrointestinal disease in captive primates
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Microbiome biogeography of non-human primates
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Disease vector microbiomes in ticks from rural Uganda​​
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Parasite detection and profiling in humans and wild primates
New directions
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Always spinning up new ideas, often with undergraduate researchers and collaborators both within Macalester and outside. Who knows what's next?
COLLABORATORS
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Science would be nothing without teamwork and collaboration. I'm lucky to have great collaborators on recent and current projects, including:
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Dan Knights (UMN)
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Jonathan Clayton (University of Nebraska)
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Lisa Corewyn, Kari Brossard Stoos (Ithaca College), and Mary Kelaita (St. Phillips College)
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Como Zoo primates team
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Shernan Holtan, Armin Rashidi, and Najla El Jurdi (UMN Medicine, Hematology)
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Devavani Chatterjea (Macalester)
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Purna Kashyap (Mayo Clinic)
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Michael Mahero (UMN)
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Martin Blaser (NYU Medicine)
