An interactive reference framework for modeling a dynamic immune system

Abstract

Immune cells function in an interacting hierarchy that coordinates 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.

Computational flow cytometry: helping to make sense of high-dimensional immunology data

“…In a subsequent step, either an MST or t-SNE-based algorithm can be used to better highlight the relationships between the cell type clusters. The scaffold map algorithm 53 , however, uses the CLARA (clustering for large applications) algorithm to cluster the cells and then uses a force-directed algorithm to show a weighted graph, in which the edge weights represent the cosine similarity between the median marker values. Next to the clusters, scaffold maps also include manually gated populations as landmarks on the graph (FIG.…”

The role of myeloid cells in cancer therapies

“…Human phagocyte studies remain limited by the scarcity of biopsy material, without which it is difficult to identify and manipulate tumourinfiltrating cell populations. However, techniques such as novel single-cell RNAseq approaches (for example, DropSeq) 217,218 , single-cell mass cytometry (CyTOF) 219 , protein mass spectrometry 220 and high-throughput protein analysis from fine-needle aspirates 221 permit the extraction of substantially more information from limited tissue samples, which should help to discriminate between tumour-promoting and tumour-suppressing cells and, in turn, improve patient stratification and survival prediction. Additionally, myeloid cells could be mapped noninvasively in patients.…”

Advances in high-dimensional mass cytometry cell and tissue analyses for translational biomarker discovery

“…Using these advanced algorithms, Spitzer et al have used mass cytometry to interrogate and analyze the bone marrow from wildtype and mutant C57BL/6 mice and process cell data onto intuitive maps, allowing to distinguish between immune cell organization in specific genetic variants and even circadian rhythms tissues [70]. These studies exemplify how genetic, environmental, and pathophysiological causative factors can be linked to disease initiation and progression [70].…”

“…More recently, multifaceted tools, allowing integration of features common to a number of algorithms, such as ImmunoClust [69] and Scaffold/immune reference maps [70] have further facilitated automated mapping of cellular phenotypes in the whole organism. Using these advanced algorithms, Spitzer et al have used mass cytometry to interrogate and analyze the bone marrow from wildtype and mutant C57BL/6 mice and process cell data onto intuitive maps, allowing to distinguish between immune cell organization in specific genetic variants and even circadian rhythms tissues [70].…”