Rodent models of organ transplantation may deviate from transplantation in the clinic both because there are species differences in basic properties of the immune system and because of extensive changes in the state of the immune system induced by encounters with microbes that do not occur in typical laboratory mice. Furthermore, the graft plays a major role in shaping the immune response and human tissue cells, especially endothelial cells (ECs), differ significantly in their immunological properties. As an important example, human CD4+ effector memory T cells are particularly effective at recognition of alloantigens displayed by human graft ECs, an interaction lacking in mice. Consequently, therapeutic strategies and reagents developed using mouse models often fail in the clinic. ?Humanized mice,? i.e. immunodeficient mice that are provided with a human immune system and then transplanted with human tissues, can address these issues and complement conventional mouse models. Humanized mice also allow testing of biologic therapeutics that often do not cross species. The principal limitation of humanized mice is that their human immune systems are incomplete, often lacking either functional T cells or functional myeloid accessory cells, cell types that must collaborate for an effective immune system. This proposal outlines an approach to improve an existing bioengineered humanized mouse model, known as MISTRG mice, that form a well differentiated myeloid compartment when inoculated as neonates with human hematopoietic stem cells (HSCs). However, MISTRG mice lack well functioning T cell responses. We propose, to remedy this by combining HSC engraftment with adoptive transfer of mature naive and/or memory T cells from the same donor as the HSCs when the mice reach adulthood. We hypothesize and will test if our approach creates a more complete human immune response without causing graft-versus-host disease (specific aim 1) and then analyze the functions of engrafted myeloid cells both on different pathways of T cell recognition of alloantigen and on T cell-mediated rejection of human skin grafts, artery grafts or synthetic tissue grafts (specific aim 2). Successful completion of these aims will provide transplantation scientists and tissue engineers with a better model to develop and test new anti-rejection strategies that can be more readily transferred to humans.

Public Health Relevance

Organ transplantation is the best available therapy for end stage organ failure, but the human immune system presents a significant barrier to replacing failing organs with grafts from another person or with bioengineered organs made from cells from another person to be used when natural organs are not available. Transplantation scientists generally use animal models, most often mice, to understand how the host's immune system rejects transplanted organs, but results from mice and other small animal models are imperfect systems for understanding how the human immune system rejects organs or for testing therapies to prevent rejection. We propose to produce mice that have been given a more functional human immune system than that achieved in earlier models and also receive natural or synthetic human tissues from a donor different from the source of the immune cells, producing a better experimental model that will allow scientists to develop and test new and more effective therapies to reduce rejection in transplant patients.

Agency
National Institute of Health (NIH)
Institute
National Institute of Allergy and Infectious Diseases (NIAID)
Type
Exploratory/Developmental Grants (R21)
Project #
1R21AI136017-01A1
Application #
9444934
Study Section
Transplantation, Tolerance, and Tumor Immunology Study Section (TTT)
Program Officer
Kehn, Patricia J
Project Start
2018-01-18
Project End
2019-12-31
Budget Start
2018-01-18
Budget End
2018-12-31
Support Year
1
Fiscal Year
2018
Total Cost
Indirect Cost
Name
Yale University
Department
Microbiology/Immun/Virology
Type
Schools of Medicine
DUNS #
043207562
City
New Haven
State
CT
Country
United States
Zip Code