An interactive reference framework for modeling a dynamic immune system

Single-cell measurements map immunity Multiple characteristics of individual cells define cell types and their physiological states. Spitzer et al. quantitated the abundance of 39 different cell surface proteins or transcription factors on individual cells of the mouse immune system. They used these measurements to create a map that clustered similar individual cells into groups corresponding to cell type and function. Their extensible experimental platform will allow the inclusion of other data types and data from independent laboratories. Science, this issue 10.1126/science.1259425 Cytometry meets mass spectrometry to create a functional map of the immune system. INTRODUCTION Immune cells constitute an interacting hierarchy that coordinates its activities according to genetic and environmental contexts. This systemically mobile network of cells results in emergent properties that are derived from dynamic cellular interactions. Unlike many solid tissues, where cells of given functions are localized into substructures that can be readily defined, the distribution of phenotypically similar immune cells into various organs complicates discerning any modest differences between them. Over decades of investigation into immune functions during health and disease, research has necessarily focused on understanding the individual cell types within the immune system, and, more recently, toward identifying interacting cells and the messengers they use to communicate. RATIONALE Methods of single-cell analysis, such as flow cytometry, have led the effort to enumerate and quantitatively characterize immune cell populations. As research has accelerated, our understanding of immune organization has surpassed the technical limitations of fluorescence-based flow cytometry. With the advent of mass cytometry, which enables measuring significantly more features of individual cells, most known immune cell types can now be identified from within a single experiment. Leveraging this capability, we set out to initiate an immune system reference framework to provide a working definition of immune organization and enable the integration of new data sets. RESULTS To build a reference framework from mass cytometry data, we developed a novel algorithm to transform the single-cell data into intuitive maps. These Scaffold maps provide a data-driven interpretation of immune organization while also integrating conventional immune cell populations as landmarks to orient the user. By applying Scaffold maps to data from the bone marrow of wild-type C57BL/6 mice, the method reconstructed the organization within this complex developmental organ. Using this sample as a reference point, the unique organization of immune cells within various organs across the body was revealed. The maps recapitulated canonical cellular phenotypes while revealing reproducible, tissue-specific deviations. The approach revealed influences of genetic variation and circadian rhythms on immune structure, permitted direct comparisons of murine and human blood cell phenotypes, and even enabled archival fluorescence-based flow cytometry data to be mapped onto the reference framework. CONCLUSION This foundational reference map provides a working definition of systemic immune organization to which new data can be integrated to reveal deviations driven by genetics, environment, or pathology. Beyond providing an analytical framework to understand immune organization from the unified data set generated here, the approaches we describe can serve as a data repository for collating experimental data from the research community, including gene expression and mutational analysis. Efforts that characterize cellular behavior in this open-source approach will continue to improve upon the initiating reference presented here to reveal the inherent structure in biological networks of immunity for clinical benefit. Building a dynamic immune system reference framework. By combining mass cytometry with the Scaffold maps algorithm, the cellular organization of any complex sample can be transformed into an intuitive and interactive map for further analysis. By first choosing one foundational sample as a reference (i.e., the bone marrow of wild-type mice), the effects of any perturbation can be readily identified in this framework. Immune cells function in an interacting hierarchy that coordinates the activities of various cell types according to genetic and environmental contexts. We developed graphical approaches to construct an extensible immune reference map from mass cytometry data of cells from different organs, incorporating landmark cell populations as flags on the map to compare cells from distinct samples. The maps recapitulated canonical cellular phenotypes and revealed reproducible, tissue-specific deviations. The approach revealed influences of genetic variation and circadian rhythms on immune system structure, enabled direct comparisons of murine and human blood cell phenotypes, and even enabled archival fluorescence-based flow cytometry data to be mapped onto the reference framework. This foundational reference map provides a working definition of systemic immune organization to which new data can be integrated to reveal deviations driven by genetics, environment, or pathology.