Sergey Kryazhimskiy
University of California-San Diego, CA·Ecology & Evolution
If the history of life were replayed, would evolution end in the same place? The outcome is neither fully random nor fully fixed.
- Fields
Ecology & Evolution
Genetics
Microbiology & Immunology
- Topics
experimental evolution
fitness landscapes
adaptive mutations
- Grants
- 2 known grants, through Jul 2030
What they work on
- Develop mathematical theory for how the biochemical architecture of cells, starting with complex metabolic networks, constrains the shape of fitness landscapes and how mutations move organisms across them.
- Measure how mutations change cellular traits such as the transcriptome (which genes are switched on) in yeast Saccharomyces cerevisiae and Escherichia coli, across genetic backgrounds and environments, to find general patterns.
- Use the resulting patterns to work toward predicting the evolution of collateral antibiotic resistance, where adapting to one drug changes a microbe's response to others.
- Observe evolutionary dynamics in a two-species microbial community and a semi-natural marine microbial system using whole-genome time-course sequencing.
- Compare the genomic and ecological repeatability of evolution in a yeast–Chlamydomonas reinhardtii mutualism grown where the yeast either can or cannot survive without the alga.
- Measure the range of adaptive mutations available to each partner, and test whether yeast and alga repeatably evolve specializations to one another, within an undergraduate research-teaching module.
More about the research
It depends on which new mutations arise, what effects they have, and how a species interacts with its neighbors. Being able to predict evolution matters because new mutations drive antibiotic resistance in bacteria, drug resistance in cancers, and the spread of viruses to new hosts. Both of the lab's projects use fast-evolving microbes to ask what makes evolution predictable. One builds a general theory of how mutations affect fitness. The other tests how partnerships between species change how repeatable evolution is.
Why it matters
Drug-resistant bacteria, treatment-resistant cancers and viruses that jump to new hosts all evolve through new mutations, but these changes are hard to predict today. A theory of how mutations affect microbial traits could help forecast this kind of harmful evolution, including collateral antibiotic resistance. The mutualism experiments add basic understanding of how interactions between species shape evolution.
Known grants
From NIH and NSF research grants. Labs often have other funding we can't see.
Closest labs
Michael Manhart
Rutgers University-New Brunswick, NJ·Ecology & Evolution
Test whether cross-feeding different nutrient types (amino acids, vitamins, carbon intermediates) changes the fitness effects of mutations differently, using engineered E. coli auxotroph partnerships and DNA-barcoded mutant libraries.
Kerry Geiler-Samerotte
Arizona State University Campus Immersion, AZ·Ecology & Evolution·Early-career
Evolve thousands of DNA-barcoded yeast lineages across subtly different temperatures to measure how the genetic basis of adaptation and the distribution of fitness effects (DFE) shift along the gradient.
William Harcombe
University of Minnesota, MN·Ecology & Evolution
Test whether mutualism changes the combined effect of antibiotic pairs by running over 3,900 growth experiments comparing Escherichia coli and Salmonella enterica in monoculture versus obligate cross-feeding co-culture.
The school
University of California-San Diego: 84 labs on PI Pages, $1.9B a year on research, 637 research doctorates a year.
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