Inference of systems-level behaviors in the immune system from single-cell data

Abstract

Understanding the systems-level behaviours of the immune system requires profiling many parameters of its constituents as well as identifying environmental factors influencing the time evolution of immune response. Recent advances in technologies enable multiple cellular components to be measured simultaneously at an unprecedented scale and resolution across many individuals, and the resulting data could be used to meet this goal. Such data allows studying the immune system as a whole enabling a holistic approach. The goal here is to analyze such high-dimensional data by examining the measured parameters interdependence in order to infer the emergent behaviours of the immune system. This thesis involves different techniques to analyze various datasets in order to reveal new insights into mechanisms of human immunity of relevance to environmental exposures. This dissertation presents results from four studies.

I. The human immune variation is continuous, rather than described by discrete groups of individuals with similar immune cell populations. How can collective states of many immune system components describe immune variation across individuals? Using partial least squares method, we derived a set of aggregate immune cell population frequencies that define an individual’s immunotype, and robustly predict diverse functional responses to cytokine stimulations. In immunotype space, individuals of younger age are similar to one another than older individuals are. Cytomegalovirus seropositivity induces a shift of one’s immunotype towards a more aged immunotype.

II. Mothers transfer antibodies but we don’t know what their composition looks like. What are the transferred maternal antibodies? How large is the repertoire of maternal antibodies, their specificities, and duration after birth? Using VirScan method, we assayed around 107 antibody-peptide interactions in mother-child dyads. The repertoire of antiviral maternal antibodies target between 5-10 different viruses, and the transferred antibodies mirrors those found in the mothers. Although IgG transfer happen principally during the final trimester, very preterm (<30 weeks of gestation) and term (>37 weeks of gestation) children receive a similar repertoire. However, the concentrations of antibodies at birth are lower in preterm than in term children, and determine how long the conferred immunity lasts for.

III. Newborns adapt to living outside the womb, suddenly exposed to new bacteria and viruses, which leads to a rapid biological change of human newborn immune system. Can phenotypic variants of developing human newborn lymphocyte be explained regarding of trade-offs between specialist and generalist phenotypes? In immune system, individual cells face a dilemma. No single cell can be optimally suited for all possible tasks, and therefore cells specialize to perform specific tasks. For example, in the human immune system, cytotoxic lymphocyte kills virus-infected cells, and B-lymphocytes produce antibodies, etc. Using Pareto archetype analysis, we learned geometrical shapes of protein expression space from longitudinal human newborn lymphocyte data. Single B cells are arranged in a triangle, while CD4+ T cells are best represented by pentahedron. The vertices of these shapes are extreme protein expression profiles optimal for tasks and correspond to major cell subsets. Cells lie along a continuum of expression inside polytope. In triangle B cells, a 1D continuum of states describes cells specialization pattern to tasks and suggests pseudo-time trajectories in the developmental path of the newborn B cells.

IV. The variation of transcriptional responses to microbial stimulants is large among primary immunodeficiency disorder (PID) patients, and little in healthy individuals. How can functional defects in PID patients be inferred from transcriptional variation of human immune responses to bacterial and viral challenges? We deduced a collective set of genes that can predict variation of transcriptional responses to stimulant antigens in PID patients. Lastly, we identified gene variants associated with the differences in transcriptional responses between PID patients and healthy individuals allowing understanding immune functional defects in patients.