T cells are fundamental components of the adaptive immune system, and following exposure to a pathogen, diverse populations of memory T cells persist to provide enhanced protection against re-exposure. While the importance of circulating memory T cells has been appreciated for many years, it is only over the last decade that it has become clear that subsets of memory T cells reside throughout peripheral tissues (known as tissue-resident memory, or T RM) and provide potent, front-line protective immunity. The identification of T RM has resulted in a paradigm shift in the way we need to monitor, target and promote T cell immunity in vaccines, diseases and immunotherapies. However, our understanding of the ontogeny, maintenance, and organization of these cells - their ecology - is lacking, even at a very basic level. For instance, humans retain T-cell immunity to pathogens for years or decades, but it is unclear whether this memory persists as long-lived cells or more dynamically, sustained by self-renewal and/or supplemented by newly generated cells. There are many other open questions; for example, what factors govern the development and maintenance of T RM and how might we manipulate them to boost their numbers? What underlies heterogeneity in their capacity to persist? Do T RM compete with each other, either intra- or inter-clonally? What role does their spatial arrangement play in any competitive dynamics? What are the rules of replacement within T RM niches? In this proposal we will take a multidisciplinary approach to addressing these questions by integrating mathematical and experimental tools in both mouse and human settings. Specifically: (i) We will use a mouse model of influenza infection and quantitative imaging to build a set of validated models of the developmental and homeostatic dynamics of T RM By combining information regarding the time-varying spatial distribution of T RM in the lung, and tracking the responses of pre-existing and newly generated T RM during and after repeat infections, we will refine these models to include competition and spatial niches, and to understand how interaction between T RM influences the rules of replacement within tissues and the durability of T cell memory. (ii) We will use a powerful cell fate-mapping system to model the ontogeny and homeostasis of T RM that are naturally and constitutively produced in multiple tissues across the mouse lifetime, and compare their dynamics to those produced in overt infections. (iii) We will combine a unique human tissue resource at Columbia with a novel application of 14C dating of DNA, a dedicated modeling framework, and quantitative image analysis. This approach will define the contributions of antigen-driven influx and self-renewal to T RM homeostasis, and identify heterogeneity in T RM dynamics, across tissues and ages. In summary, this project will deliver a suite of quantitative tools for defining the life-histories of tissue-specific memory T cells, in both mice and humans, across space and time.

Public Health Relevance

Tissue-resident memory T cells (T RM) reside throughout the body and provide potent, front-line protective immunity. However, our understanding of the ontogeny, maintenance, and organization of these cells - their ecology - is incomplete. This project will integrate multiple modeling approaches and data from diverse experimental systems, including a unique human tissue resource, to provide a suite of modeling tools for defining the life-histories of T RM in both mice and humans.

Agency
National Institute of Health (NIH)
Institute
National Institute of Allergy and Infectious Diseases (NIAID)
Type
Research Project--Cooperative Agreements (U01)
Project #
1U01AI150680-01
Application #
9949341
Study Section
Special Emphasis Panel (ZAI1)
Program Officer
Gondre-Lewis, Timothy A
Project Start
2020-08-19
Project End
2025-05-31
Budget Start
2020-08-19
Budget End
2021-05-31
Support Year
1
Fiscal Year
2020
Total Cost
Indirect Cost
Name
Columbia University (N.Y.)
Department
Pathology
Type
Schools of Medicine
DUNS #
621889815
City
New York
State
NY
Country
United States
Zip Code
10032