Cyton2: A Model of Immune Cell Population Dynamics That Includes Familial Instructional Inheritance

High-resolution mapping of cell cycle dynamics during steady-state T cell development and regeneration in vivo

Control of cell proliferation is critical for the lymphocyte life cycle. However, little is known about how stage-specific alterations in cell cycle behavior drive proliferation dynamics during T cell development. Here, we employed in vivo dual-nucleoside pulse labeling combined with the determination of DNA replication over time as well as fluorescent ubiquitination-based cell cycle indicator mice to establish a quantitative high-resolution map of cell cycle kinetics of thymocytes. We developed an agent-based mathematical model of T cell developmental dynamics. To generate the capacity for proliferative bursts, cell cycle acceleration followed a "stretch model" characterized by the simultaneous and proportional contraction of both G1 and S phases. Analysis of cell cycle phase dynamics during regeneration showed tailored adjustments of cell cycle phase dynamics. Taken together, our results highlight intrathymic cell cycle regulation as an adjustable system to maintain physiologic tissue homeostasis and foster our understanding of dysregulation of the T cell developmental program.

Programmed death receptor 1 (PD-1) ligand Fc fusion proteins reduce T-cell proliferation in vitro independently of PD-1

Programmed death receptor 1 (PD-1) is an inhibitory receptor on T cells shown to restrain T-cell proliferation. PD-1 immune checkpoint blockade has emerged as a highly promising approach in cancer treatment. Much of our understanding of the function of PD-1 is derived from in vitro T-cell activation assays. Here we set out to further investigate how T cells integrate inhibitory signals such as PD-1 in vitro using the PD-1 agonist, PD-1 ligand 1 (PD-L1) fusion protein (PD-L1.Fc), coimmobilized alongside anti-CD3 agonist monoclonal antibody (mAb) on plates to deliver PD-1 signals to wild-type and PD-1-/- CD8+ T cells. Surprisingly, we found that the PD-L1.Fc fusion protein inhibited T-cell proliferation independently of PD-1. This PD-L1.Fc inhibition was observed in the presence and absence of CD28 and interleukin-2 signaling. Binding of PD-L1.Fc was restricted to PD-1-expressing T cells and thus inhibition was not mediated by the interaction of PD-L1.Fc with CD80 or other yet unknown binding partners. Furthermore, a similar PD-1-independent reduction of T-cell proliferation was observed with plate-bound PD-L2.Fc. Hence, our results suggest that the coimmobilization of PD-1 ligand fusion proteins with anti-CD3 mAb leads to a reduction of T-cell engagement with plate-bound anti-CD3 mAb. This study demonstrates a nonspecific mechanism of T-cell inhibition when PD-L1.Fc or PD-L2.Fc fusion proteins are delivered in a plate-bound coimmobilization assay and highlights the importance of careful optimization of assay systems and reagents when interpreting their influence on T-cell proliferation.

Survival and division fate programs are preserved but retuned during the naïve to memory CD8+ T-cell transition

Memory T cells are generated from naïve precursors undergoing proliferation during the initial immune response. Both naïve and memory T cells are maintained in a resting, quiescent state and respond to activation with a controlled proliferative burst and differentiation into effector cells. This similarity in the maintenance and response dynamics points to the preservation of key cellular fate programs; however, whether memory T cells have acquired intrinsic changes in these programs that may contribute to the enhanced immune protection in a recall response is not fully understood. Here we used a quantitative model-based analysis of proliferation and survival kinetics of in vitro-stimulated murine naïve and memory CD8+ T cells in response to homeostatic and activating signals to establish intrinsic similarities or differences within these cell types. We show that resting memory T cells display heightened sensitivity to homeostatic cytokines, responding to interleukin (IL)-2 in addition to IL-7 and IL-15. The proliferative response to αCD3 was equal in size and kinetics, demonstrating that memory T cells undergo the same controlled division burst and automated return to quiescence as naïve T cells. However, perhaps surprisingly, we observed reduced expansion of αCD3-stimulated memory T cells in response to activating signals αCD28 and IL-2 compared with naïve T cells. Overall, we demonstrate that although sensitivities to cytokine and costimulatory signals have shifted, fate programs regulating the scale of the division burst are conserved in memory T cells.

Quantifying Human Naïve B Cell Proliferation Kinetics and Differentiation in Controlled In Vitro Cell Culture

Division tracking dyes like Cell Trace Violet (CTV) enable the quantification of cell proliferation, division, and survival kinetics of human naïve B cell responses in vitro. Human naïve B cells exhibit distinct responses to different stimuli, with CpG and anti-Ig inducing a T cell-independent (TI) response, while CD40L and IL-21 promote a T cell-dependent (TD) response that induces isotype switching and differentiation into antibody-secreting cells (ASCs). Both stimulation methods yield valuable insights into the intrinsic programming of B cell health within individuals, making them useful for clinical investigations. For instance, quantitative analysis from these B cell populations could reveal biologically meaningful measurements such as the average number of division rounds and the time to cells' fate. Here, we describe a novel in vitro culture setup for CTV-labelled human naïve B cells and a method for obtaining precise time-based data on proliferation, division-linked isotype switching, and differentiation.

Is immunology doing well? A look at 100 immune-mediated inflammatory diseases for 100 years of the Journal

It is now 60 years since Ian Mackay and Macfarlane Burnet published their seminal text "The Autoimmune Diseases" in which they examined the full scope of human inflammatory pathology as a manifestation of the underlying structure and function of the immune system. Here I revisit this approach to ask to what extent has the promise of Mackay and Burnet's work been exploited in clinical medicine as currently practiced. In other words, is immunology doing well? Despite spectacular headline contributions of immunology in clinical medicine, I present evidence suggesting a performance ceiling in our capacity to answer the relatively straightforward questions that patients frequently ask about their own diseases and find that this ceiling exists across almost all of the 100 immune-mediated inflammatory diseases examined. I propose that these questions are difficult, not so much because the immune system is overwhelmingly complex but rather that we have more to learn about the relatively simple agents and rules that may underpin self-organizing complex interacting systems as revealed in studies from other disciplines. The way that the immune system has evolved to exploit the ancient machinery determining three independent cell fate timers as described in this Journal would be a great place to start to decode the self-organizing principles that underpin the emergent pathology that we observe in the clinic.

Modeling T Cell Fate

Many of the pathways that underlie the diversification of naive T cells into effector and memory subsets, and the maintenance of these populations, remain controversial. In recent years a variety of experimental tools have been developed that allow us to follow the fates of cells and their descendants. In this review we describe how mathematical models provide a natural language for describing the growth, loss, and differentiation of cell populations. By encoding mechanistic descriptions of cell behavior, models can help us interpret these new datasets and reveal the rules underpinning T cell fate decisions, both at steady state and during immune responses.

Lineage tracing reveals fate bias and transcriptional memory in human B cells

We combined single-cell transcriptomics and lineage tracing to understand fate choice in human B cells. Using the antibody sequences of B cells, we tracked clones during in vitro differentiation. Clonal analysis revealed a subset of IgM+ B cells which were more proliferative than other B-cell types. Whereas the population of B cells adopted diverse states during differentiation, clones had a restricted set of fates available to them; there were two times more single-fate clones than expected given population-level cell-type diversity. This implicated a molecular memory of initial cell states that was propagated through differentiation. We then identified the genes which had strongest coherence within clones. These genes significantly overlapped known B-cell fate determination programs, suggesting the genes which determine cell identity are most robustly controlled on a clonal level. Persistent clonal identities were also observed in human plasma cells from bone marrow, indicating that these transcriptional programs maintain long-term cell identities in vivo. Thus, we show how cell-intrinsic fate bias influences differentiation outcomes in vitro and in vivo.