Freddy Bunbury
University of Chicago, IL·Microbiology & Immunology
Phytoplankton are tiny photosynthetic organisms at the base of food webs in lakes, rivers and oceans, and some cause harmful algal blooms. Scientists cannot yet predict how they will fare as water warms, because it is not known how they adapt to heat.
- Fields
Microbiology & Immunology
Ecology & Evolution
Genetics
- Topics
cyanobacteria
phytoplankton
thermotolerance
- Grants
- 1 known grant, through Aug 2028
What they work on
- Identify genome features, such as amino acid frequencies and gene content, that predict the optimal growth temperature of cyanobacteria, using thermophilic hot-spring strains.
- Apply these temperature models to moderate-temperature cyanobacteria and to freshwater metagenomic data, including NEON samples, to find species poorly adapted to warming.
- Distinguish helpful from harmful heat-stress responses by comparing transcriptomic and metabolomic profiles of isolates with different heat survival, linked using sparse canonical correlation analysis.
- Test whether horizontal gene transfer speeds heat-tolerance evolution by adding DNA from heat-tolerant donors to sensitive strains in lab selection experiments, then compare with natural populations.
More about the research
This project studies cyanobacteria, a type of phytoplankton, that thrive in hot springs near the upper temperature limit for oxygen-producing photosynthesis. Their genomes likely carry strong signs of heat adaptation.
Why it matters
Genome-based predictions of heat tolerance could help forecast which phytoplankton are most vulnerable to warming and anticipate harmful algal blooms in U.S. freshwaters. The findings could also guide efforts to engineer heat-resilient cyanobacteria for producing supplements, biofuels and other bioproducts, including through gene transfer–driven artificial evolution.
Known grants
From NIH and NSF research grants. Labs often have other funding we can't see.
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Todd Treangen
Rice University, TX·Computer Science·Early-career
Identify yet-unseen pathogens by linking taxonomy-based classification of sequences with genes whose functions are of concern, so that novel threats can be recognized in sequencing data.
The school
University of Chicago: 39 labs on PI Pages, $681M a year on research, 457 research doctorates a year.
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