A hallmark of the humoral immune response is a two phased antibody response, the first being rapid and providing for low affinity antibodies, and the second occurring with a week delay but providing high affinity antibodies. An appropriate balance of both phases of the response is critical for an effective immune response. The two phased humoral immune response is governed by B-cell population dynamics that represent the composite of the decisions made by individual cells whether to enter a growth phase and the cell cycle that results in division, whether to survive or die, and whether to differentiate into antibody secreting plasma cells and/or memory B-cells. At any given timepoint there is a great variety of B-cell fates, and prior studies assumed that this is due to stochastic fate decisions by individual cells at each generation. Instead, our recently established long-term microscopy workflow revealed that cells make highly deterministic fate decisions, and that the cell-to-cell variability within the population is largely due to heterogeneity in the founder cells. This renders humoral immunity substantially more predictable, so long as we have a mechanistic understanding of how molecular networks control B-cell decision making in proliferation and differentiation. The overarching goal of the proposed project is to develop quantitative understanding and multi-scale model of how the multi-dimeric NF?B system controls B-cell decision making to effect cell survival, proliferation, and differentiation. The overarching hypothesis of the proposed studies is that the coordinated dynamics of NF?B family members RelA and cRel control the phasing of B-cell proliferation and differentiation and thus the affinity, abundance and diversity of antibodies and hence efficacy of the humoral immune response. We will address this hypothesis with an iterative systems biology approach structured into following three Specific Aims: 1. Delineate how NF?B system dynamics control the lineages of proliferating B-cells 2. Delineate how NF?B system dynamics control plasma B-cell differentiation 3. NF?B system control of humoral immunity in vivo: phasing low and high affinity antibody responses Each Aim involves novel multiscale mathematical modeling and quantitative experimentation, including unprecedented long term microscopy, novel fluorescent reporter mouse strains, and single cell genomic technologies.

Public Health Relevance

A hallmark of the humoral immune response is a two phased antibody response, the first being rapid and providing for low affinity antibodies, and the second occurring with a week delay but providing high affinity antibodies. An appropriate balance of both phases of the response is critical for an effective immune response. In this project we will investigate how the molecular network governing the dynamics of NF?B activity controls effectiveness of humoral immunity by phasing the affinity, abundance and diversity of antibodies.

Agency
National Institute of Health (NIH)
Institute
National Institute of Allergy and Infectious Diseases (NIAID)
Type
Research Project (R01)
Project #
5R01AI132731-04
Application #
10094180
Study Section
Modeling and Analysis of Biological Systems Study Section (MABS)
Program Officer
Gondre-Lewis, Timothy A
Project Start
2018-02-01
Project End
2023-01-31
Budget Start
2021-02-01
Budget End
2022-01-31
Support Year
4
Fiscal Year
2021
Total Cost
Indirect Cost
Name
University of California Los Angeles
Department
Microbiology/Immun/Virology
Type
Schools of Medicine
DUNS #
092530369
City
Los Angeles
State
CA
Country
United States
Zip Code
90095
Mitchell, Simon; Hoffmann, Alexander (2018) Identifying Noise Sources governing cell-to-cell variability. Curr Opin Syst Biol 8:39-45
Mitchell, Simon; Roy, Koushik; Zangle, Thomas A et al. (2018) Nongenetic origins of cell-to-cell variability in B lymphocyte proliferation. Proc Natl Acad Sci U S A 115:E2888-E2897
Roy, Koushik; Shokhirev, Maxim Nikolaievich; Mitchell, Simon et al. (2018) Deriving Quantitative Cell Biological Information from Dye-Dilution Lymphocyte Proliferation Experiments. Methods Mol Biol 1707:81-94