Immune cells function in an interacting hierarchy that coordinates activities of

Immune cells function in an interacting hierarchy that coordinates activities of various cell types according to genetic and environmental contexts. the reference framework. This foundational reference map provides a working definition of systemic immune business to which new data can be integrated to reveal deviations driven by genetics environment or pathology. The immune system is usually a systemically mobile network of cells with emergent properties 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 comparable immune cells into numerous organs complicates discerning differences between them. Much research has necessarily focused on understanding the individual cell types within the immune system and more recently towards identifying interacting cells and the messengers they use to communicate. Methods of single cell analysis such as flow cytometry have been at the heart of this effort to enumerate and quantitatively characterize immune cell populations (1-3). As research has accelerated the number of markers required to identify cell types and explain detailed mechanisms has surpassed the technical limitations of fluorescence-based circulation cytometry (1-4). Consequently insights have often been limited because only a few cell subsets could AZD-2461 AZD-2461 be examined independent of the immune system as a whole (5 6 Although individual immune cell populations have been examined extensively no comprehensive or standardized reference map of the immune system has been developed primarily because of the difficulty of data normalization and lack of co-expression measurements that would enable “merging” of Rabbit polyclonal to HMGCL. results. In other analysis modalities such as transcript profiling of cell populations reference requirements and minable databases have shown remarkable utility (7-14). A comprehensive research map defining the organization of the immune system at the single cell level would similarly offer new opportunities for organized data analysis. For example macrophages exhibit tissue-specific phenotypes (15) and adaptive immune responses are influenced by genetics (16) but discerning AZD-2461 these properties of immune organization required integrating the results of many disparate studies. Even current analytical tools that do provide a systems-level view do not compare new samples to an existing reference framework making them unsuitable for this objective (17 18 In contrast a AZD-2461 reference map that is extensible could provide a biomedical foundation for any systematized dynamic community-collated AZD-2461 resource to guide future analyses and mechanistic studies. We leveraged mass cytometry a platform that allows measurement of multiple parameters simultaneously at the single-cell level to initiate a reference map of the immune system (19-21). By combining the throughput of circulation cytometry with the resolution of mass spectrometry this hybrid technology enables the simultaneous quantification of 40 parameters in single cells. AZD-2461 Use of mass cytometry allows fluorophore reporters to be replaced with isotopically-pure stable heavy metal ions conjugated to antibodies or affinity reagents (22). These reporter ions are then quantified by time-of-flight mass spectrometry to provide single-cell measurements enabling a more detailed characterization of complex cellular systems for any robust research map. An Analytical Framework for a Research Map A useful research map should enable a data-driven business of cells and should be flexible enough to accommodate different types of measurements. This would result in a map with underlying regularity but also strong enough to allow overlay of new data (or even of archival data from different measurement modalities) according to cell similarities. The approach is meant to provide themes for representing the system as a whole to enable systems-level comparisons much like other efforts to compare biological networks (23-28). Although we provide one template here the framework is built to enable users to construct individualized or community-organized versions. Building a research map.