Short-Range Spread of Cytokines: Generality, Dynamics, and Impact on Population Variability

Immune cells produce an array of cytokines that signal the type and severity of pathogenic threats to nearby cells, coordinating an apt immune response. The spatial reach of cytokines determines whether immune response coordination is localized or systemic. We have previously shown that the cytokines Interleukin-2 (IL-2) and Interferon-γ (IFNγ) spread only a few cell diameters (~4-10) from their source. Moreover, cytokine spread in dense tissues follows diffusion-consumption dynamics, enabling precise predictions about tissue distribution, gradient sharpness, and heterogeneous exposure among neighboring cells. Consequently, when cytokine receptors are abundant, cytokines spatially-confine and form steep concentration gradients. These emergent cytokine signaling niches can drive downstream gene expression heterogeneity, and functional differences between cells. This project explores the central hypothesis that T-cell derived cytokines have limited spread, creating transient localized signaling niches that drive cellular variability within tissues. Although we have extensive data on the limited spatial spread of IL-2 and IFNγ, it's still uncertain if localized signaling niches are typical for all T-cell derived cytokines. In Aim 1, we will combine in vitro cytokine penetration assays with cyclic immunofluorescence measurements of cytokine responses around activated T cells in lymph nodes to characterize the spatial extent of T cell derived cytokines. Secondly, cytokine exposure can trigger cellular responses like proliferation, death, or changes in receptor expression, dynamically influencing the range of cytokine spread. In Aim 2, we will combine spatial modeling of cytokine spread and response, live-cell microscopy of regulatory T cells within IL-2 signaling niches in 3D in vitro culture systems, and whole organ imaging of mouse lymph nodes to explore the dynamics of IL-2 signaling niche formation, maintenance, and resolution. Lastly, single-cell studies reveal significant gene expression variability among cells of the same type within the same organ. This variability is often attributed to stochastic factors or cell-intrinsic phenomena. However, differential exposure to cytokines due to their heterogeneous spatial distribution can be a substantial driver of population variability in gene expression. In Aim 3, we'll use a probabilistic model to link gene expression variability in cell populations to cytokine spatial heterogeneity. Using gene expression response to IL-2 in regulatory T cells as a test case, we will combine 3D culture experiments with in vivo experiments in mice to quantify the degree of gene expression variability attributable to differential exposure to the cytokine. Our research bridges detailed single-cell transcriptomics and tissue immunology, focusing on a range of cytokines to understand their spread and impact on immune responses in dense organ environments. Leveraging biophysical theory, advanced 3D cell cultures, in vivo mouse models, and mathematical modeling, we're uniquely positioned to answer these fundamental questions about cytokine-driven immune dynamics. Project Number: 1R01HL182417-01A1 | Fiscal Year: 2025 | NIH Institute/Center: National Heart Lung and Blood Institute (NHLBI) | Principal Investigator: Jennifer Oyler-Yaniv | Institution: HARVARD MEDICAL SCHOOL, BOSTON, MA | Award Amount: $570,814 | Activity Code: R01 | Study Section: Modeling and Analysis of Biological Systems Study Section[MABS] View on NIH RePORTER: https://reporter.nih.gov/project-details/1R01HL18241701A1