About

Elizabeth Jerison is an Assistant Professor of Physics at the University of Chicago, affiliated with the Committee on Immunology and the UChicago Biosciences. Her research focuses on tumor-immune interactions, particularly in melanoma, and their response to checkpoint blockade therapies. Her work involves studying the surface features of melanoma and how they facilitate interactions with the immune system, contributing to understanding the pathological responses in humans. Her scientific contributions extend to evolutionary biology and microbial evolution, with investigations into phenotypic and molecular evolution over thousands of generations in laboratory yeast populations, as well as the dynamics of genetic variation, adaptation, and epistasis. Her research employs a range of experimental and theoretical approaches to explore evolutionary processes, mutation effects, and the physical interactions at biological interfaces. Elizabeth Jerison's work aims to deepen understanding of immune responses in cancer and the fundamental mechanisms of evolution and adaptation in biological systems.

Research topics

• Genetics
• Biology
• Evolutionary biology
• Engineering
• Computational biology
• Biochemical engineering
• Cell biology
• Neuroscience

Selected publications

• Cytokine Dynamics Following a Point Source Perturbation

  Knowledge@UChicago (University of Chicago) · 2026-01-01

  otherOpen accessSenior author

  The immune system consists of a complex network of white blood cells, signaling molecules, and receptors that serve the vital purpose of identifying and defending against a variety of threats. The detection of harmful pathogens causes an inflammatory response, which is intended to be a short term deviation from homeostasis. However, in certain cases the inflammatory response can spiral out of control rather than attenuate to baseline, as occurs with chronic inflammation. While there is a wealth of biological knowledge on the signaling pathways involved in inflammatory responses, the spatiotemporal dynamics of these responses in tissues are poorly understood. The development of a model that characterizes these dynamics would provide considerable insight into the trajectory of the inflammatory response and under what circumstances it will return to homeostasis or enter another regime, which would have valuable applications to the field of medicine. To study the transport of cytokines, as well as the responses in tissue that occur when cells detect these signaling molecules, the lab is establishing techniques for generating controlled local sources of cytokines within larval zebrafish. This simulates a single white blood cell detecting and responding to a pathogen. There are two methods currently in development to generate local cytokine sources. The first method uses a transgenic zebrafish line that produces the cytokine Tumor Necrosis Factor-alpha (TNF⍺) in response to heat shock. In the second method, the zebrafish is bathed in a caged toll-like receptor (TLR) agonist, which–when activated–binds to a nearby TLR and initiates the inflammatory response, including the production of cytokines. When employed in conjunction with staining and imaging techniques, these methods provide valuable insight into cytokine behavior.

  PublisherOA PDFDOI

• Spatially structured inflammatory response in the presence of a uniform stimulus

  Proceedings of the National Academy of Sciences · 2026-03-20 · 1 citations

  articleOpen access1st authorCorresponding

  Inflammatory responses occur within the complex spatial context of tissues and organs, and many questions remain about how tissue structure and cellular communication shape their spatiotemporal dynamics. Here, we use a multiplexed RNA in situ hybridization approach, together with analytical tools, to study inflammatory gene expression in the larval zebrafish tailfin in response to a bath of lipopolysaccharide. We use this model system to address whether spatial structure emerges in the tissue response even absent the spatial variation introduced by a pathogen. We find that epithelial cells in the tailfin express several proinflammatory genes, and that across these genes, the uniform stimulus triggers a spatially nonuniform response. We use a graph-based spectral decomposition method to analyze its structure, and find that it is consistent with a diffusion-consumption model of secondary signaling. Overall, long-wavelength modes dominate the signal, creating zones of activation which account for a majority of the variation in gene expression. Our results show that epithelial cells are important producers of proinflammatory effector molecules in this system, and that tissue induces spatial correlations even absent a structured input.

  PublisherDOI

• Parallel but distinct adaptive routes in the budding and fission yeasts after 10,000 generations of experimental evolution

  Nature Ecology & Evolution · 2026-03-13

  articleOpen access

  Experimental evolution has been a useful tool for investigating long-term temporal evolutionary dynamics and molecular mechanisms underlying adaptation. However, extracting fundamental principles and predictive features of evolutionary outcomes from these datasets remains challenging. Here we sought to circumvent these challenges by comparing distant yeast species that share several evolutionary features but differ in evolutionary history and genome architecture, that is Saccharomyces cerevisiae and Schizosaccharomyces pombe. We evolved ten populations of the fission yeast for 10,000 generations in the same conditions as a pre-existing budding yeast dataset, allowing us to observe repeatable evolutionary outcomes within species but diverse molecular targets of adaptation across species. The most frequent route of adaptation was through changes in carbon flux metabolism, which was previously unseen in S. cerevisiae evolved populations, but similar evolutionary paths have been observed in wild populations. This suggests that parallelism is pervasive and that mechanisms of adaptation can be shared among closely related or distant species. Despite similar gene content and identical environments, recurrent adaptation across S. pombe populations involved different genes than in S. cerevisiae and was detectable mostly at the transcriptomic level. This indicates that trans-regulatory effects and contingency may contribute to differences in evolutionary outcomes between these species.

  PublisherOA PDFDOI

• Characterizing nonlinear dynamics by contrastive cartography

  ArXiv.org · 2025-01-30

  preprintOpen accessSenior author

  The qualitative study of dynamical systems using bifurcation theory is key to understanding systems from biological clocks and neurons to physical phase transitions. Data generated from such systems can feature complex transients, an unknown number of attractors, and stochasticity. Characterization of these often-complicated behaviors remains challenging. Making an analogy to bifurcation analysis, which specifies that useful dynamical features are often invariant to coordinate transforms, we leverage contrastive learning to devise a generic tool to discover dynamical classes from stochastic trajectory data. By providing a model-free trajectory analysis tool, this method automatically recovers the dynamical phase diagram of known models and provides a "map" of dynamical behaviors for a large ensemble of dynamical systems. The method thus provides a way to characterize and compare dynamical trajectories without governing equations or prior knowledge of target behavior. We additionally show that the same strategy can be used to characterize the stochastic motion of bacteria, establishing that this approach can be used as a standalone analysis tool or as a component of a broader data-driven analysis framework for dynamical data.

  PublisherOA PDFDOI

• Characterizing Nonlinear Dynamics by Contrastive Cartography

  PRX Life · 2025-09-11

  articleOpen accessSenior author

  The qualitative study of dynamical systems using bifurcation theory is key to understanding systems from biological clocks and neurons to physical phase transitions. Data generated from such systems can feature complex transients, an unknown number of attractors, and stochasticity. Characterization of these often-complicated behaviors remains challenging. Making an analogy to bifurcation analysis, which specifies that useful dynamical features are often invariant to coordinate transformations, we leverage contrastive learning to devise a generic tool to discover dynamical classes from stochastic trajectory data. By providing a model-free trajectory analysis tool, this method automatically recovers the dynamical phase diagram of known models and provides a “map” of dynamical behaviors for a large ensemble of dynamical systems. The method thus provides a way to characterize and compare dynamical trajectories without governing equations or prior knowledge of target behavior. We additionally show that the same strategy can be used to characterize the stochastic motion of bacteria, establishing that this approach can be used as a stand-alone analysis tool or as a component of a broader data-driven analysis framework for dynamical data.

  PublisherOA PDFDOI

• CRATER tumor niches facilitate CD8+ T cell engagement and correspond with immunotherapy success

  Cell · 2025-10-17 · 8 citations

  articleOpen access

  T cell accumulation and tumor killing. In humans, elevation in CRATER density in biopsies following immune checkpoint blockade (ICB) therapy correlated with a clinical response to therapy. CRATERs are structures that show active tumor killing and may be useful as a diagnostic indicator for immunotherapy success.

  PublisherDOI

• Parallel but distinct adaptive routes in the budding and fission yeasts after 10,000 generations of experimental evolution

  bioRxiv (Cold Spring Harbor Laboratory) · 2025-09-12

  preprintOpen access

  ABSTRACT Quantitative genetics approaches designed to understand the evolution of traits have helped improve our understanding of the genetic basis of adaptation. However, they often overlook crucial aspects of adaptation, including the long-term temporal evolutionary dynamics, the predictability of evolutionary outcomes, the influence of past evolution on future evolutionary trajectories (contingency), and the diversity of molecular mechanisms underlying adaptation. Experimental evolution has been a useful tool for answering these questions, but extracting fundamental principles and predictive features of evolutionary outcomes from these datasets remains challenging due to the large number of covariates and confounding effects, such as differences in experimental setup, species lifestyle, gene content, and evolution rate. Here, we sought to circumvent these challenges by comparing distant yeast species that share several evolutionary features but differ mainly in evolutionary history and genome architecture, i.e. Saccharomyces cerevisiae and Schizosaccharomyces pombe . Thus, we evolved 10 populations of the fission yeast for 10,000 generations in the same conditions as a pre-existing budding yeast dataset (i.e. high-sugar media and hypoxic conditions), allowing us to observe repeatable evolutionary outcomes within species but diverse molecular mechanisms and targets of adaptation across species. The most frequent adapting route in these conditions involved upregulating fermentation genes and downregulating the glycolysis gene pyk1 , which has not previously been observed in S. cerevisiae evolved populations or in wild Kluyveromyces lactis, but similar evolutionary paths have been observed in Schizosaccharomyces japonicus and in clinically relevant populations, such as some cancer cells. This suggests that parallelism is pervasive in the tree of life and that mechanisms of adaptation can be shared among closely related or distant species. Despite similar gene content and identical environments, recurrent adaptation across S. pombe populations involved different genes than in S. cerevisiae and was mostly detectable at the transcriptomic level. This suggests that trans-regulatory effects may play an important role in adaptation on short evolutionary timescales and that differences in evolutionary outcomes between these species may be attributed to contingency.

  PublisherOA PDFDOI

• Spatially-structured inflammatory response in the presence of a uniform stimulus

  bioRxiv (Cold Spring Harbor Laboratory) · 2025-01-31 · 1 citations

  preprintOpen access1st author

  Abstract Inflammatory responses occur within the complex spatial context of tissues and organs, and many questions remain about how tissue structure and cellular communication shape their spatiotemporal dynamics. Here, we use a multiplexed RNA in situ hybridization approach, together with analytical tools, to study inflammatory gene expression in the larval zebrafish tailfin in response to a bath of lipopolysaccharide (LPS). We use this model system to address whether spatial structure emerges in the tissue response even absent the spatial variation introduced by a pathogen. We find that epithelial cells in the tailfin express several pro-inflammatory genes, and that across these genes, the uniform stimulus triggers a spatially non-uniform response. We use a graph-based spectral decomposition method to analyze its structure, and find that long modes dominate, creating zones of activation. Overall, these zones account for a majority of the variation in gene expression. Our results show that epithelial cells are important producers of pro-inflammatory effector molecules in this system, and that tissue induces spatial correlations even absent a structured input.

  PublisherDOI

• Craters on the melanoma surface facilitate tumor-immune interactions and demonstrate pathologic response to checkpoint blockade in humans

  bioRxiv (Cold Spring Harbor Laboratory) · 2024-09-19 · 1 citations

  preprintOpen access

  Summary Immunotherapy leads to cancer eradication despite the tumor’s immunosuppressive environment. Here, we used extended long-term in-vivo imaging and high-resolution spatial transcriptomics of endogenous melanoma in zebrafish, and multiplex imaging of human melanoma, to identify domains that facilitate immune response during immunotherapy. We identified crater-shaped pockets at the margins of zebrafish and human melanoma, rich with beta-2 microglobulin (B2M) and antigen recognition molecules. The craters harbor the highest density of CD8 + T cells in the tumor. In zebrafish, CD8 + T cells formed prolonged interactions with melanoma cells within craters, characteristic of antigen recognition. Following immunostimulatory treatment, the craters enlarged and became the major site of activated CD8 + T cell accumulation and tumor killing that was B2M dependent. In humans, craters predicted immune response to ICB therapy, showing response better than high T cell infiltration. This marks craters as potential new diagnostic tool for immunotherapy success and targets to enhance ICB response.

  PublisherOA PDFDOI

• Dynamical control of immunity and inflammation

  Biophysical Journal · 2024-02-01 · 3 citations

  articleOpen access1st authorCorresponding
  PublisherOA PDFDOI

Frequent coauthors

• Michael M. Desai

  Quantitative BioSciences

  45 shared

• Alex N. Nguyen Ba

  University of Toronto

  14 shared

• Sergey Kryazhimskiy

  University of California, San Diego

  13 shared

• Katherine R. Lawrence

  Oxford Nanopore Technologies (United Kingdom)

  12 shared

• Stephen R. Quake

  Stanford University

  9 shared

• Shreyas Gopalakrishnan

  Harvard University

  8 shared

• Ivana Cvijović

  Stanford University

  8 shared

• Ramya Purkanti

  University of Lausanne

  8 shared

Labs

• Elizabeth Jerison's LabPI

Education

• PhD, Physics

  Harvard University

  2016

• BS, Physics

  Yale University

  2010