Michael Baym
Harvard University, MA·Microbiology & Immunology
Bacteria evolve fast, and two linked questions drive the work here: why antibiotic resistance spreads the way it does, and how to watch evolution happen cell by cell. Resistance is a near-ideal system for studying evolution because fitness can be measured, selection pressure can be dialed up or down, and new traits arrive either by mutation or by being handed between cells.
- Fields
Microbiology & Immunology
Ecology & Evolution
Biology
- Topics
antibiotic resistance
evolutionary tradeoffs
plasmids
- Grants
- 3 known grants, through Dec 2029
What they work on
- Test whether the standard model of resistance evolution is incomplete by measuring the direct and indirect fitness costs of resistance and of specialization in evolving bacterial populations under tunable antibiotic selection.
- Characterize how plasmids and other mobile genetic elements compete within single bacteria and across populations, and how they interact with resistance genes and with bacteriophage, the viruses that infect bacteria.
- Survey environmental bacteria for previously undescribed mobile genetic elements and the cargo genes they carry, and reconstruct how antibiotic resistance has shifted over roughly eighty years of clinical use using computational analysis of sequence data.
- Build synthetic plasmid systems that allow intracellular plasmid competition to be measured directly, quantifying the tradeoff between gene expression level and plasmid fitness with microfluidics, fluorescence imaging and sequencing.
- Construct Self-EvolvR, an engineered Cas9 that continually mutates its own barcode sequence, and validate it for lineage tracing in living bacterial and eukaryotic cells.
- Raise the Self-EvolvR mutation rate by directed evolution until lineages separated by only a few cell divisions can be distinguished, while keeping toxicity to the host cell low.
More about the research
The projects combine laboratory evolution of bacteria, synthetic biology, sequence analysis and mathematical modeling, with one project building a DNA-based tool for tracking lineages that the other projects need.
Why it matters
Antibiotic resistance is a public health crisis, and understanding what suppresses resistance as well as what spreads it could suggest new approaches: treatment plans for long-term infections that anticipate or exploit a pathogen's evolutionary options, and population-level policies aimed at the dynamics that actually matter for containment. The barcoding tool could help any field that needs to follow replicating cells, from bacterial growth to tissue development, immune responses and cancer.
Known grants
From NIH and NSF research grants. Labs often have other funding we can't see.
Closest labs
Amy Mathers
University of Virginia, VA·Microbiology & Immunology
Determine which transposons, DNA segments that jump between locations, dominate movement of a carbapenemase resistance gene inside bacterial cells, by combining whole-genome sequencing of patient and environmental isolates with new mathematical analyses.
Emile Gluck-Thaler
University of Wisconsin-Madison, WI·Genetics
Determine how rates of horizontal Starship transfer between fungi change in response to different environmental cues, using a newly developed laboratory transfer assay.
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.
The school
Harvard University: 42 labs on PI Pages, $1.5B a year on research, 712 research doctorates a year.
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