Primary immune responses generate short-term effectors and long-term protective memory cells. The delineation of the genealogy linking naive, effector, and memory cells has been complicated by the lack of phenotypes discriminating effector from memory differentiation stages. Using transcriptomics and phenotypic analyses, we identify Bcl2 and Mki67 as a marker combination that enables the tracking of nascent memory cells within the effector phase. We then use a formal approach based on mathematical models describing the dynamics of population size evolution to test potential progeny links and demonstrate that most cells follow a linear naive→early effector→late effector→memory pathway. Moreover, our mathematical model allows long-term prediction of memory cell numbers from a few early experimental measurements. Our work thus provides a phenotypic means to identify effector and memory cells, as well as a mathematical framework to investigate their genealogy and to predict the outcome of immunization regimens in terms of memory cell numbers generated.

CD8 T-cells are critical in controlling infection by intracellular pathogens. Upon encountering antigen presenting cells, T-cell receptor activation promotes the differentiation of naïve CD8 T-cells into strongly proliferating activated and effector stages. We propose a 2D-multiscale computational model to study the maturation of CD8 T-cells in a lymph node controlled by their molecular profile. A novel molecular pathway is presented and converted into an ordinary differential equation model, coupled with a cellular Potts model to describe cell-cell interactions. Key molecular players such as activated IL2 receptor and Tbet levels Computation 2014, 2 160 control the differentiation from naïve into activated and effector stages, respectively, while caspases and Fas-Fas ligand interactions control cell apoptosis. Coupling this molecular model to the cellular scale successfully reproduces qualitatively the evolution of total CD8 T-cell counts observed in mice lymph node, between Day 3 and 5.5 post-infection. Furthermore, this model allows us to make testable predictions of the evolution of the different CD8 T-cell stages.

IL-4 is one of the main cytokines produced during Th2-inducing pathologies. This cytokine has been shown to affect a number of immune processes such as Th differentiation and innate immune responses. However, the impact of IL-4 on CD8 T cell responses remains unclear. In this study, we analyzed the effects of IL-4 on global gene expression profiles of Ag-induced memory CD8 T cells in the mouse. Gene ontology analysis of this signature revealed that IL-4 regulated most importantly genes associated with immune responses. Moreover, this IL-4 signature overlapped with the set of genes preferentially expressed by memory CD8 T cells over naive CD8 T cells. In particular, IL-4 downregulated in vitro and in vivo in a STAT6-dependent manner the memory-specific expression of NKG2D, thereby increasing the activation threshold of memory CD8 T cells. Furthermore, IL-4 impaired activation of memory cells as well as their differentiation into effector cells. This phenomenon could have an important clinical relevance as patients affected by Th2 pathologies such as parasitic infections or atopic dermatitis often suffer from viral-induced complications possibly linked to inefficient CD8 T cell responses.

The primary CD8 T cell immune response constitutes a major mechanism to fight an infection by intra-cellular pathogens. We aim at assessing whether pathogen-specific dynamical parameters of the CD8 T cell response can be identified, based on measurements of CD8 T cell counts, using a modeling approach. We generated experimental data consisting in CD8 T cell counts kinetics during the response to three different live intra-cellular pathogens: two viruses (influenza, vaccinia) injected intranasally, and one bacteria (Listeria monocytogenes) injected intravenously. All pathogens harbor the same antigen (NP68), but differ in their interaction with the host. In parallel, we developed a mathematical model describing the evolution of CD8 T cell counts and pathogen amount during an immune response. This model is characterized by 9 parameters and includes relevant feedback controls. The model outputs were compared with the three data series and an exhaustive estimation of the parameter values was performed. By focusing on the ability of the model to fit experimental data and to produce a CD8 T cell population mainly composed of memory cells at the end of the response, critical parameters were identified. We show that a small number of parameters (2-4) define the main features of the CD8 T cell immune response and are characteristic of a given pathogen. Among these parameters, two are related to the effector CD8 T cell mediated control of cell and pathogen death. The parameter associated with memory cell death is shown to play no relevant role during the main phases of the CD8 T cell response, yet it becomes essential when looking at the predictions of the model several months after the infection.

The pool of memory-phenotype CD8 T cells is composed of Ag-induced (AI) and cytokine-induced innate (IN) cells. IN cells have been described as having properties similar to those of AI memory cells. However, we found that pathogen-induced AI memory cells can be distinguished in mice from naturally generated IN memory cells by surface expression of NKG2D. Using this marker, we described the increased functionalities of AI and IN memory CD8 T cells compared with naive cells, as shown by comprehensive analysis of cytokine secretion and gene expression. However, AI differed from IN memory CD8 T cells by their capacity to migrate to the lung parenchyma upon inflammation or infection, a process dependent on their expression of ITGA1/CD49a and ITGA4/CD49d integrins.

Besides the classically described subsets of memory CD8 T cells generated under infectious conditions, are T inflammatory memory cells generated under sterile priming conditions, such as sensitization to allergens. Although not fully differentiated as pathogen-induced memory cells, they display memory properties that distinguish them from naive CD8 T cells. Given these memory cells are generated in an antigen-specific context that is devoid of pathogen-derived danger signals and CD4 T cell help, we herein questioned whether they maintained their activation and differentiation potential, could be recruited in an immune response directed against a pathogen expressing their cognate antigen and further differentiate in fully competent secondary memory cells. We show that T inflammatory memory cells can indeed take part to the immune response triggered by a viral infection, differentiate into secondary effectors and further generate typical central memory CD8 T cells and effector memory CD8 T cells. Furthermore, the secondary memory cells they generate display a functional advantage over primary memory cells in their capacity to produce TNF-α and the XCL1 chemokine. These results suggest that cross-reactive stimulations and differentiation of cells directed against allergens or self into fully competent pathogen-induced memory cells might have incidences in inflammatory immuno-pathologies.

Memory CD8 T lymphocyte populations are remarkably heterogeneous and differ in their ability to protect the host. In order to identify the whole range of qualities uniquely associated with protective memory cells we compared the gene expression signatures of two qualities of memory CD8 T cells sharing the same antigenic-specificity: protective (Influenza-induced, Flu-TM) and non-protective (peptide-induced, TIM) spleen memory CD8 T cells. Although Flu-TM and TIM express classical phenotypic memory markers and are polyfunctional, only Flu-TM protects against a lethal viral challenge. Protective memory CD8 T cells express a unique set of genes involved in migration and survival that correlate with their unique capacity to rapidly migrate within the infected lung parenchyma in response to influenza infection. We also enlighten a new set of poised genes expressed by protective cells that is strongly enriched in cytokines and chemokines such as Ccl1, Ccl9 and Gm-csf. CCL1 and GM-CSF genes are also poised in human memory CD8 T cells. These immune signatures are also induced by two other pathogens (vaccinia virus and Listeria monocytogenes). The immune signatures associated with immune protection were identified on circulating cells, i.e. those that are easily accessible for immuno-monitoring and could help predict vaccines efficacy.

The pool of memory-phenotype CD8 T cells is composed of antigen-induced (AI) and