Rachel Finck

Single-Cell Mass Cytometry of Differential Immune and Drug Responses Across a Human Hematopoietic Continuum

Simultaneous measurement of more than 30 properties in individual human cells is used to characterize signaling in the immune system. Flow cytometry is an essential tool for dissecting the functional complexity of hematopoiesis. We used single-cell “mass cytometry” to examine healthy human bone marrow, measuring 34 parameters simultaneously in single cells (binding of 31 antibodies, viability, DNA content, and relative cell size). The signaling behavior of cell subsets spanning a defined hematopoietic hierarchy was monitored with 18 simultaneous markers of functional signaling states perturbed by a set of ex vivo stimuli and inhibitors. The data set allowed for an algorithmically driven assembly of related cell types defined by surface antigen expression, providing a superimposable map of cell signaling responses in combination with drug inhibition. Visualized in this manner, the analysis revealed previously unappreciated instances of both precise signaling responses that were bounded within conventionally defined cell subsets and more continuous phosphorylation responses that crossed cell population boundaries in unexpected manners yet tracked closely with cellular phenotype. Collectively, such single-cell analyses provide system-wide views of immune signaling in healthy human hematopoiesis, against which drug action and disease can be compared for mechanistic studies and pharmacologic intervention.

Multiplexed mass cytometry profiling of cellular states perturbed by small-molecule regulators

Mass cytometry facilitates high-dimensional, quantitative analysis of the effects of bioactive molecules on human samples at single-cell resolution, but instruments process only one sample at a time. Here we describe mass-tag cellular barcoding (MCB), which increases mass cytometry throughput by using n metal ion tags to multiplex up to 2n samples. We used seven tags to multiplex an entire 96-well plate, and applied MCB to characterize human peripheral blood mononuclear cell (PBMC) signaling dynamics and cell-to-cell communication, signaling variability between PBMCs from eight human donors, and the effects of 27 inhibitors on this system. For each inhibitor, we measured 14 phosphorylation sites in 14 PBMC types at 96 conditions, resulting in 18,816 quantified phosphorylation levels from each multiplexed sample. This high-dimensional, systems-level inquiry allowed analysis across cell-type and signaling space, reclassified inhibitors and revealed off-target effects. High-content, high-throughput screening with MCB should be useful for drug discovery, preclinical testing and mechanistic investigation of human disease.

Data-driven phenotypic dissection of AML reveals progenitor-like cells that correlate with prognosis

Acute myeloid leukemia (AML) manifests as phenotypically and functionally diverse cells, often within the same patient. Intratumor phenotypic and functional heterogeneity have been linked primarily by physical sorting experiments, which assume that functionally distinct subpopulations can be prospectively isolated by surface phenotypes. This assumption has proven problematic, and we therefore developed a data-driven approach. Using mass cytometry, we profiled surface and intracellular signaling proteins simultaneously in millions of healthy and leukemic cells. We developed PhenoGraph, which algorithmically defines phenotypes in high-dimensional single-cell data. PhenoGraph revealed that the surface phenotypes of leukemic blasts do not necessarily reflect their intracellular state. Using hematopoietic progenitors, we defined a signaling-based measure of cellular phenotype, which led to isolation of a gene expression signature that was predictive of survival in independent cohorts. This study presents new methods for large-scale analysis of single-cell heterogeneity and demonstrates their utility, yielding insights into AML pathophysiology.

Multiplexed ion beam imaging of human breast tumors

Immunohistochemistry (IHC) is a tool for visualizing protein expression that is employed as part of the diagnostic workup for the majority of solid tissue malignancies. Existing IHC methods use antibodies tagged with fluorophores or enzyme reporters that generate colored pigments. Because these reporters exhibit spectral and spatial overlap when used simultaneously, multiplexed IHC is not routinely used in clinical settings. We have developed a method that uses secondary ion mass spectrometry to image antibodies tagged with isotopically pure elemental metal reporters. Multiplexed ion beam imaging (MIBI) is capable of analyzing up to 100 targets simultaneously over a five-log dynamic range. Here, we used MIBI to analyze formalin-fixed, paraffin-embedded human breast tumor tissue sections stained with ten labels simultaneously. The resulting data suggest that MIBI can provide new insights into disease pathogenesis that will be valuable for basic research, drug discovery and clinical diagnostics.

Normalization of mass cytometry data with bead standards.

Mass cytometry uses atomic mass spectrometry combined with isotopically pure reporter elements to currently measure as many as 40 parameters per single cell. As with any quantitative technology, there is a fundamental need for quality assurance and normalization protocols. In the case of mass cytometry, the signal variation over time due to changes in instrument performance combined with intervals between scheduled maintenance must be accounted for and then normalized. Here, samples were mixed with polystyrene beads embedded with metal lanthanides, allowing monitoring of mass cytometry instrument performance over multiple days of data acquisition. The protocol described here includes simultaneous measurements of beads and cells on the mass cytometer, subsequent extraction of the bead‐based signature, and the application of an algorithm enabling correction of both short‐ and long‐term signal fluctuations. The variation in the intensity of the beads that remains after normalization may also be used to determine data quality. Application of the algorithm to a one‐month longitudinal analysis of a human peripheral blood sample reduced the range of median signal fluctuation from 4.9‐fold to 1.3‐fold.

Clinical recovery from surgery correlates with single-cell immune signatures

Single-cell mass cytometry revealed immune correlates of patient-associated variability in surgical recovery. Signaling Surgical Recovery The speed and ease of recovery after surgery differ for every patient, and determining the mechanisms that drive recovery could lead to patient-specific recovery protocols. Gaudilliere et al. used mass cytometry to characterize postsurgical immunological insult at a single-cell level and found a surgical immune signature that correlated with clinical recovery across patients. Specifically, cell signaling responses, but not cell frequency, were linked to recovery. Moreover, the correlated signaling responses occurred most notably in CD14+ monocytes, suggesting that these cells may play a predominant role in surgical recovery. The consistency of this signature across patients suggests a tightly regulated immune response to surgical trauma, which, if validated, may form the basis of a diagnostic guideline for personalized postsurgical care. Delayed recovery from surgery causes personal suffering and substantial societal and economic costs. Whether immune mechanisms determine recovery after surgical trauma remains ill-defined. Single-cell mass cytometry was applied to serial whole-blood samples from 32 patients undergoing hip replacement to comprehensively characterize the phenotypic and functional immune response to surgical trauma. The simultaneous analysis of 14,000 phosphorylation events in precisely phenotyped immune cell subsets revealed uniform signaling responses among patients, demarcating a surgical immune signature. When regressed against clinical parameters of surgical recovery, including functional impairment and pain, strong correlations were found with STAT3 (signal transducer and activator of transcription), CREB (adenosine 3′,5′-monophosphate response element–binding protein), and NF-κB (nuclear factor κB) signaling responses in subsets of CD14+ monocytes (R = 0.7 to 0.8, false discovery rate <0.01). These sentinel results demonstrate the capacity of mass cytometry to survey the human immune system in a relevant clinical context. The mechanistically derived immune correlates point to diagnostic signatures, and potential therapeutic targets, that could postoperatively improve patient recovery.

Palladium-based mass tag cell barcoding with a doublet-filtering scheme and single-cell deconvolution algorithm

Mass-tag cell barcoding (MCB) labels individual cell samples with unique combinatorial barcodes, after which they are pooled for processing and measurement as a single multiplexed sample. The MCB method eliminates variability between samples in antibody staining and instrument sensitivity, reduces antibody consumption and shortens instrument measurement time. Here we present an optimized MCB protocol. The use of palladium-based labeling reagents expands the number of measurement channels available for mass cytometry and reduces interference with lanthanide-based antibody measurement. An error-detecting combinatorial barcoding scheme allows cell doublets to be identified and removed from the analysis. A debarcoding algorithm that is single cell–based rather than population-based improves the accuracy and efficiency of sample deconvolution. This debarcoding algorithm has been packaged into software that allows rapid and unbiased sample deconvolution. The MCB procedure takes 3–4 h, not including sample acquisition time of ∼1 h per million cells.

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.

Transient Partial Permeabilization with Saponin Enables Cellular Barcoding Prior to Surface Marker Staining

Fluorescent cellular barcoding and mass‐tag cellular barcoding are cytometric methods that enable high sample throughput, minimize inter‐sample variation, and reduce reagent consumption. Previously employed barcoding protocols require that barcoding be performed after surface marker staining, complicating combining the technique with measurement of alcohol‐sensitive surface epitopes. This report describes a method of barcoding fixed cells after a transient partial permeabilization with 0.02% saponin that results in efficient and consistent barcode staining with fluorescent or mass‐tagged reagents while preserving surface marker staining. This approach simplifies barcoding protocols and allows direct comparison of surface marker staining of multiple samples without concern for variations in the antibody cocktail volume, antigen‐antibody ratio, or machine sensitivity. Using this protocol, cellular barcoding can be used to reliably detect subtle differences in surface marker expression.

Coordinate actions of innate immune responses oppose those of the adaptive immune system during Salmonella infection of mice

Multiparametric analysis of immune cell signaling, cytokines, and bacteria identifies connections that balance innate and adaptive immune responses to infection. Assembling the immune system jigsaw Analysis of individual components of the immune response to infection solves only small parts of the immune system puzzle. Hotson et al. analyzed the variable immune responses of Salmonella-infected mice over time by measuring the numbers and signaling states of multiple immune cell types and combining these data with measurements of serum cytokine concentrations, antibody responses, and bacterial burden. Mathematical analysis of this multiparametric data set revealed response elements that clustered together into patterns that showed how different components of the immune system interacted with each other. For example, neutrophils inhibited the functions of B cells during the course of infection. Thus, this systems biology approach enables the assembly of interconnected sections of the immune system puzzle. The immune system enacts a coordinated response when faced with complex environmental and pathogenic perturbations. We used the heterogeneous responses of mice to persistent Salmonella infection to model system-wide coordination of the immune response to bacterial burden. We hypothesized that the variability in outcomes of bacterial growth and immune response across genetically identical mice could be used to identify immune elements that serve as integrators enabling co-regulation and interconnectedness of the innate and adaptive immune systems. Correlation analysis of immune response variation to Salmonella infection linked bacterial load with at least four discrete, interacting functional immune response “cassettes.” One of these, the innate cassette, in the chronically infected mice included features of the innate immune system, systemic neutrophilia, and high serum concentrations of the proinflammatory cytokine interleukin-6. Compared with mice with a moderate bacterial load, mice with the highest bacterial burden exhibited high activity of this innate cassette, which was associated with a dampened activity of the adaptive T cell cassette—with fewer plasma cells and CD4+ T helper 1 cells and increased numbers of regulatory T cells—and with a dampened activity of the cytokine signaling cassette. System-wide manipulation of neutrophil numbers revealed that neutrophils regulated signal transducer and activator of transcription (STAT) signaling in B cells during infection. Thus, a network-level approach demonstrated unappreciated interconnections that balanced innate and adaptive immune responses during the dynamic course of disease and identified signals associated with pathogen transmission status, as well as a regulatory role for neutrophils in cytokine signaling.