Department of Pathology · The University of Chicago
Learning how immune cells communicate
We are a multidisciplinary team studying T cells in tissues and the conversations they have with the cells around them. Our goal is to discover the rules that determine whether the immune system fights infection or turns on the body.

Artwork: Catherine Laplace
Welcome to the Zemmour Lab
Immune responses are built from many kinds of cells. We are working out what those parts are — and the rules that determine how they fit together — because that assembly is what decides whether a response fights infection and cancer, or instead triggers autoimmunity.
We are particularly fascinated by T cells and regulatory T cells (Tregs). Most cells in the body "do something": skin cells make a barrier, pancreatic cells make enzymes to digest food. Some T cells, including Tregs, instead specialize in modulating what other immune and non-immune cells do — making them the clearest window we have into cellular conversation. They are present in every organ, and we still puzzle over how they maintain tolerance, promote tissue homeostasis, and contribute to disease.
We explore the role of T cells directly in human tissues, using systems and synthetic biology approaches that illuminate these interactions. Human tissue comes first: it carries the disease as it occurs, and our mouse models are there to explain it. Findings move in both directions — from patients into mice where we can test mechanisms, and back to the clinic as new diagnostics and new points of treatment.

What we work on
Research page →immgenT, a mouse T cell atlas
An open-source reference of T cells in all their shapes and flavors, across infection, autoimmunity, aging, cancer, and more.
T cell interaction networks
We are not single-cell organisms. Understanding how cells talk to each other at scale is the next frontier in biology.
Building mechanistic models of human diseases
Multimodal measurements from patient tissue, turned into models we can test in mice and take back to the clinic.
Latest news
All news →- The immgenT CD4 paper is available on bioRxiv!immgenT CD4: a reference landscape of mouse CD4+ T cells
- Welcome, Clément Hedde, visiting student from École Centrale de Lyon, France!
- The first wave of immgenT papers is available on bioRxiv!immgenT: a comprehensive reference of convergent T-cell states · A reference landscape of regulatory T cell states · A comprehensive reference of CD8αβ T cell differentiation states · The αβTCR repertoire at scale · Diverse microbial exposure and CD8+ effector memory
- Welcome, Nitya Mehrotra, Immunology PhD student!
Research
We study what T cells do in tissues, why and how they do it — by measuring their conversations with the cells around them.
immgenT, a mouse T cell atlas
An open-source reference of T cells in all their shapes and flavors, across infection, autoimmunity, aging, cancer, and more.
T cells are very heterogeneous and versatile across tissues and pathologies — infections, cancer, autoimmunity. The previous classifications of T cells only scratched the surface of a world being revealed by single-cell genomics.
We are part of a consortium aiming to characterize T cells in all their shapes and flavors in mice: immgenT, an open-source project within the ImmGen consortium. We look at where and when T cells matter the most, beyond healthy tissues — in infection, autoimmunity, aging, and cancer.
The first wave of immgenT papers is now on bioRxiv: the reference atlas of convergent T-cell states, companion landscapes for CD4+ T cells, regulatory T cells, and CD8αβ T cells, the αβTCR repertoire at scale, and a study of how diverse microbial exposure shapes CD8+ effector memory output.

Key papers
- immgenT: A Comprehensive Reference of Convergent T-cell States in the MousebioRxiv 2026
- immgenT CD4: A Reference Landscape of Mouse CD4+ T CellsbioRxiv 2026
- A Reference Landscape of Regulatory T Cell States in MicebioRxiv 2026
- The CD8 immgenT framework as a universal reference of mouse CD8αβ T cell differentiation statesbioRxiv 2026
- The αβTCR repertoire at scale in the immgenT datasetbioRxiv 2026
- Diverse Microbial Exposure Enhances CD8(+) T Cell Effector Memory Output and FunctionbioRxiv 2026
- The ImmGen consortium OpenSource T cell projectNat Immunol 2022
- CD4(+) teff cell heterogeneity: the perspective from single-cell transcriptomicsCurr Opin Immunol 2020
T cell interaction networks
We are not single-cell organisms. Understanding how cells talk to each other at scale is the next frontier in biology.
Efforts in specific lab-based projects and larger consortia like the Human Cell Atlas or the first phase of immgenT mostly focus on cataloging all cell types in the human body. But we are not single-cell organisms! Understanding immune responses, tissue organization, and bodily functions requires understanding how cells communicate.
What are the different modes of communication? Are there independent channels? New channels? Can all cells talk to each other? We believe that a systematic analysis of cellular interactions is creating a new field in biology, with an impact on diagnosis and treatment. Many current medications already target cellular interactions — immune checkpoint blockade, biotherapies in autoimmunity — but none directly measure their impact on cell communication. Methods are largely lacking.
In the lab, we invent and use new methods from computational biology (modeling), systems biology, and synthetic biology to characterize and modulate cell communication in vivo and in situ in human tissues. Because T cells are fundamentally important, we dissect their network of cellular interactions across tissues and diseases.
Building mechanistic models of human diseases
Multimodal measurements from patient tissue, turned into models we can test in mice and take back to the clinic.
We combine systems biology technologies to extract the maximum amount of information from human tissues. Single-cell RNA-seq remains a core tool for defining the cellular composition of lesions. Building on this, the lab has established spatial biology pipelines — single-cell spatial transcriptomics and multiplexed immunofluorescence — that let us measure cell–cell interactions directly in tissues.
These multimodal datasets (molecules, cells, and their interactions) enable us to construct mechanistic models of disease, which we then test in mouse models. Whenever possible, we translate these insights back into patient care, for example by informing diagnostics.
Inflammatory bowel disease
Patients with medically refractory ulcerative colitis often undergo total colectomy with an ileal pouch–anal anastomosis — a J-pouch — which restores intestinal continuity. In a substantial fraction of patients the pouch later fails, and there is no good way to predict who is at risk. In the lab’s first paper, we went back to the colon removed at surgery and combined careful histopathologic evaluation with single-cell spatial transcriptomics, asking whether the original disease already carries the signature of what happens next. We found cellular and molecular abnormalities in those specimens that track with subsequent pouch failure, pointing both to candidate mechanisms and to features a pathologist could eventually report.
Olivas, Ngai, Schahrer et al., Cell Mol Gastroenterol Hepatol 2025
Immune checkpoint blockade-induced colitis
Immune checkpoint inhibitors (ICI) have revolutionized cancer treatment. But they also trigger autoimmunity in up to 40% of patients, which can be fatal or force the discontinuation of a potentially curative treatment. Although the cause of the disease is clear — drug-induced — the exact process leading to the pathology is still unknown.
ICI-induced autoimmunity is both a significant clinical challenge and a rare opportunity: a chance to watch the onset of autoimmunity in humans, on a known trigger and a known clock. We are investigating why Tregs aren’t sufficient to prevent ICI colitis, and ways to manipulate them to prevent autoimmunity while maintaining anti-tumor immunity — a major objective of tumor immunotherapy.
Kawasaki disease
An acute vasculitis of childhood that can damage the coronary arteries. Working with the Arditi and Noval-Rivas labs, we use single-cell and spatial genomics in human heart tissue and a mouse model to dissect the immune interactions that drive the vascular lesion, implicating NLRP3 inflammasome signaling, autophagy-mitophagy, or STING pathways as intervention points.

Key papers
- Histopathologic Evaluation and Single-cell Spatial Transcriptomics of the Colon Reveal Cellular and Molecular Abnormalities Linked to J-Pouch Failure in Patients With Inflammatory Bowel DiseaseCell Mol Gastroenterol Hepatol 2025
- NLRP3 Inflammasome Mediates Immune-Stromal Interactions in VasculitisCirc Res 2021


