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α-Fetoprotein (AFP) is expressed by stem-like and poor outcome hepatocellular cancer tumors and is a clinical tumor biomarker. AFP has been demonstrated to inhibit dendritic cell (DC) differentiation and maturation and to block oxidative phosphorylation. To identify the critical metabolic pathways leading to human DC functional suppression, here, we used two recently described single-cell profiling methods, scMEP (single-cell metabolic profiling) and SCENITH (single-cell energetic metabolism by profiling translation inhibition). Glycolytic capacity and glucose dependence of DCs were significantly increased by tumor-derived, but not normal cord blood–derived, AFP, leading to increased glucose uptake and lactate secretion. Key molecules in the electron transport chain in particular were regulated by tumor-derived AFP. These metabolic changes occurred at mRNA and protein levels, with negative impact on DC stimulatory capacity. Tumor-derived AFP bound significantly more polyunsaturated fatty acids (PUFA) than cord blood–derived AFP. PUFAs bound to AFP increased metabolic skewing and promoted DC functional suppression. PUFAs inhibited DC differentiation in vitro, and ω-6 PUFAs conferred potent immunoregulation when bound to tumor-derived AFP. Together, these findings provide mechanistic insights into how AFP antagonizes the innate immune response to limit antitumor immunity. Significance: α-Fetoprotein (AFP) is a secreted tumor protein and biomarker with impact on immunity. Fatty acid–bound AFP promotes immune suppression by skewing human dendritic cell metabolism toward glycolysis and reduced immune stimulation.

Subunits from the chromatin remodelers mammalian SWItch/Sucrose Non-Fermentable (mSWI/SNF) are mutated, deleted, or amplified in more than 40% of cancers. Understanding their functions in normal cells and the consequences of cancerous alterations will provide insight into developing new targeted therapies. Here we examined whether mSWI/SNF mutations increase cellular sensitivity to specific drugs. Taking advantage of the DepMap studies, we demonstrate that cancer cells harboring mutations of specific mSWI/SNF subunits exhibit a genetic dependency on translation factors and are sensitive to translation pathway inhibitors. Furthermore, mSWI/SNF subunits were present in the cytoplasm and interacted with the translation initiation machinery, and short-term inhibition and depletion of specific subunits decreased global translation, implicating a direct role for these factors in translation. Depletion of specific mSWI/SNF subunits also increased sensitivity to mTOR-PI3K inhibitors. In patient-derived breast cancer samples, mSWI/SNF subunits expression in both the nucleus and the cytoplasm was substantially altered. In conclusion, an unexpected cytoplasmic role for mSWI/SNF complexes in translation suggests potential new therapeutic opportunities for patients afflicted by cancers demonstrating alterations in their subunits. Significance: This work establishes direct functions for mSWI/SNF in translation and demonstrates that alterations in mSWI/SNF confer a therapeutic vulnerability to translation pathway inhibitors in cancer cells.

Mass cytometry (MC) is a recent technology that pairs plasma-based ionization of cells in suspension with time-of-flight (TOF) mass spectrometry to sensitively quantify the single-cell abundance of metal-isotope-tagged affinity reagents to key proteins, RNA, and peptides. Given the ability to multiplex readouts (~50 per cell) and capture millions of cells per experiment, MC offers a robust way to assay rare, transitional cell states that are pertinent to human development and disease. Here, we review MC approaches that let us probe the dynamics of cellular regulation across multiple conditions and sample types in a single experiment. Additionally, we discuss current limitations and future extensions of MC as well as computational tools commonly used to extract biological insight from single-cell proteomic datasets.

Next-generation tools for multiplexed imaging have driven a new wave of innovation in understanding how single-cell function and tissue structure are interrelated. In previous work, we developed multiplexed ion beam imaging by time of flight, a highly multiplexed platform that uses secondary ion mass spectrometry to image dozens of antibodies tagged with metal reporters. As instrument throughput has increased, the breadth and depth of imaging data have increased as well. To extract meaningful information from these data, we have developed tools for cell identification, cell classification, and spatial analysis. In this review, we discuss these tools and provide examples of their application in various contexts, including ductal carcinoma in situ, tuberculosis, and Alzheimer's disease. We hope the synergy between multiplexed imaging and automated image analysis will drive a new era in anatomic pathology and personalized medicine wherein quantitative spatial signatures are used routinely for more accurate diagnosis, prognosis, and therapeutic selection. Expected final online publication date for the Annual Review of Pathology: Mechanisms of Disease, Volume 17 is January 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Abstract Neurodegenerative disorders are characterized by phenotypic changes and hallmark proteopathies. Quantifying these in archival human brain tissues remains indispensable for validating animal models and understanding disease mechanisms. We present a framework for nanometer-scale, spatial proteomics with multiplex ion beam imaging (MIBI) for capturing neuropathological features. MIBI facilitated simultaneous, quantitative imaging of 36 proteins on archival human hippocampus from individuals spanning cognitively normal to dementia. Customized analysis strategies identified cell types and proteopathies in the hippocampus across stages of Alzheimer’s disease (AD) neuropathologic change. We show microglia-pathologic tau interactions in hippocampal CA1 subfield in AD dementia. Data driven, sample independent creation of spatial proteomic regions identified persistent neurons in pathologic tau neighborhoods expressing mitochondrial protein MFN2, regardless of cognitive status, suggesting a survival advantage. Our study revealed unique insights from multiplexed imaging and data-driven approaches for neuropathologic analysis and serves broadly as a methodology for spatial proteomic analysis of archival human neuropathology. Teaser Multiplex Ion beam Imaging enables deep spatial phenotyping of human neuropathology-associated cellular and disease features.

Cellular metabolism underpins immune cell functionality, yet our understanding of metabolic influences in human dendritic cell biology and their ability to orchestrate immune responses is poorly developed. Here, we map single-cell metabolic states and immune profiles of inflammatory and tolerogenic monocytic dendritic cells using recently developed multiparametric approaches. Single-cell metabolic pathway activation scores reveal simultaneous engagement of multiple metabolic pathways in distinct monocytic dendritic cell differentiation stages. GM-CSF/IL4-induce rapid reprogramming of glycolytic monocytes and transient co-activation of mitochondrial pathways followed by TLR4-dependent maturation of dendritic cells. Skewing of the mTOR:AMPK phosphorylation balance and upregulation of OXPHOS, glycolytic and fatty acid oxidation metabolism underpin metabolic hyperactivity and an immunosuppressive phenotype of tolerogenic dendritic cells, which exhibit maturation-resistance and a de-differentiated immune phenotype marked by unique immunoregulatory receptor signatures. This single-cell dataset provides important insights into metabolic pathways impacting the immune profiles of human dendritic cells.

Mass-tag cell barcoding has increased the throughput, multiplexing, and robustness of multiple cytometry approaches. Previously, we adapted mass cytometry for cells to analyze synaptosome preparations (mass synaptometry or SynTOF), extending mass cytometry to these smaller, anuclear particles. To improve throughput and individual event resolution, we report here the application of palladium-based barcoding in human synaptosomes. Up to 20 individual samples, each with a unique combinatorial barcode, were pooled for labeling with an antibody cocktail. Our synaptosome protocol used six palladium-based barcoding reagents, and in combination with sequential gating increased the identification of presynaptic events approximately 4-fold. These same parameters also efficiently resolved two other anuclear particles: human red blood cells (RBCs) and platelets. The addition of palladium-based mass-tag barcoding to our approach improves mass cytometry of synaptic particles.

Cellular metabolism regulates immune cell activation, differentiation and effector functions, but current metabolic approaches lack single-cell resolution and simultaneous characterization of cellular phenotype. In this study, we developed an approach to characterize the metabolic regulome of single cells together with their phenotypic identity. The method, termed single-cell metabolic regulome profiling (scMEP), quantifies proteins that regulate metabolic pathway activity using high-dimensional antibody-based technologies. We employed mass cytometry (cytometry by time of flight, CyTOF) to benchmark scMEP against bulk metabolic assays by reconstructing the metabolic remodeling of in vitro-activated naive and memory CD8+ T cells. We applied the approach to clinical samples and identified tissue-restricted, metabolically repressed cytotoxic T cells in human colorectal carcinoma. Combining our method with multiplexed ion beam imaging by time of flight (MIBI-TOF), we uncovered the spatial organization of metabolic programs in human tissues, which indicated exclusion of metabolically repressed immune cells from the tumor–immune boundary. Overall, our approach enables robust approximation of metabolic and functional states in individual cells.

The increasing use of mass cytometry for analyzing clinical samples offers the possibility to perform comparative analyses across public datasets. However, challenges in batch normalization and data integration limit the comparison of datasets not intended to be analyzed together. Here, we present a data integration strategy, CytofIn, using generalized anchors to integrate mass cytometry datasets from the public domain. We show that low-variance controls, such as healthy samples and stable channels, are inherently homogeneous, robust against stimulation, and can serve as generalized anchors for batch correction. Single-cell quantification comparing mass cytometry data from 989 leukemia files pre- and post normalization with CytofIn demonstrates effective batch correction while recapitulating the gold-standard bead normalization. CytofIn integration of public cancer datasets enabled the comparison of immune features across histologies and treatments. We demonstrate the ability to integrate public datasets without necessitating identical control samples or bead standards for fast and robust analysis using CytofIn.

The latent HIV-1 reservoir represents a major barrier to achieving a long-term antiretroviral therapy (ART)-free remission or cure for HIV-1. Natural Killer (NK) cells are innate immune cells that play a critical role in controlling viral infections and have been shown to be involved in preventing HIV-1 infection and, in those who are infected, delaying time to progression to AIDS. However, their role in limiting HIV-1 persistence on long term ART is still uncharacterized. To identify associations between markers of HIV-1 persistence and the NK cell receptor-ligand repertoire, we used twin mass cytometry panels to characterize the peripheral blood NK receptor-ligand repertoire in individuals with long-term antiretroviral suppression enrolled in the AIDS Clinical Trial Group A5321 study. At the time of testing, participants had been on ART for a median of 7 years, with virological suppression +CD56dimCD57-LILRB1-NKG2C-) was associated with lower HIV-1 cell associated DNA. Finally, we found that surface expression of HLA-Bw6 measured by CyTOF was associated with lower HIV-1 persistence. Genetic analysis revealed that this was driven by lower HIV-1 persistence in HLA-Bw4/6 heterozygotes. These findings suggest that there may be a role for NK cells in controlling HIV-1 persistence in individuals on long-term ART, which must be corroborated by future studies.

Tuberculosis (TB) in humans is characterized by formation of immune-rich granulomas in infected tissues, the architecture and composition of which are thought to affect disease outcome. However, our understanding of the spatial relationships that control human granulomas is limited. Here, we used multiplexed ion beam imaging by time of flight (MIBI-TOF) to image 37 proteins in tissues from patients with active TB. We constructed a comprehensive atlas that maps 19 cell subsets across 8 spatial microenvironments. This atlas shows an IFN-γ-depleted microenvironment enriched for TGF-β, regulatory T cells and IDO1+ PD-L1+ myeloid cells. In a further transcriptomic meta-analysis of peripheral blood from patients with TB, immunoregulatory trends mirror those identified by granuloma imaging. Notably, PD-L1 expression is associated with progression to active TB and treatment response. These data indicate that in TB granulomas, there are local spatially coordinated immunoregulatory programs with systemic manifestations that define active TB.

Multiplexed ion beam imaging by time-of-flight (MIBI-TOF) is a form of mass spectrometry imaging that uses metal labeled antibodies and secondary ion mass spectrometry to image dozens of proteins simultaneously in the same tissue section. Working with the National Cancer Institute's (NCI) Cancer Immune Monitoring and Analysis Centers (CIMAC), we undertook a validation study, assessing concordance across a dozen serial sections of a tissue microarray of 21 samples that were independently processed and imaged by MIBI-TOF or single-plex immunohistochemistry (IHC) over 12 days. Pixel-level features were highly concordant across all 16 targets assessed in both staining intensity (R

Regulatory B cells (Bregs) suppress immune responses through the secretion of interleukin-10 (IL-10). This immunomodulatory capacity holds therapeutic potential, yet a definitional immunophenotype for enumeration and prospective isolation of B cells capable of IL-10 production remains elusive. Here, we simultaneously quantify cytokine production and immunophenotype in human peripheral B cells across a range of stimulatory conditions and time points using mass cytometry. Our analysis shows that multiple functional B cell subsets produce IL-10 and that no phenotype uniquely identifies IL-10

Summary Immune checkpoint blockade using PD-1 inhibition is an effective approach for treating a wide variety of cancer subtypes. While lower gastrointestinal (GI) side effects are more common, upper gastrointestinal adverse events are rarely reported. Here, we present a case of nivolumab-associated autoimmune gastritis. To elucidate the immunology underlying this condition, we leverage multiplexed ion beam imaging by time-of-flight (MIBI-TOF) to identify the presence and proportion of infiltrating immune cells from a single section of biopsy specimen. Using MIBI-TOF, we analyze formalin-fixed, paraffin-embedded human gastric tissue with 28 labels simultaneously. Our analyses reveal a gastritis characterized by severe mucosal injury, interferon gamma (IFN-γ)-producing gastric epithelial cells, and mixed inflammation that includes CD8 and CD4 T cell infiltrates with reduced expression of granzyme B and FOXP3, respectively. Here, we provide a comprehensive multiplexed histopathological mapping of gastric tissue, which identifies IFN-γ-producing epithelial cells as possible contributors to the nivolumab-associated gastritis., Graphical abstract, Highlights Multiplexed imaging of gastric toxicity associated with anti-PD-1 immunotherapy Analysis reveals severe mucosal injury associated with IFN-γ-expressing epithelial cells Inflamed gastric epithelium is accompanied by mixed infiltration of CD4 and CD8 T cells, Ferrian et al. leverage multiplexed ion beam imaging by time-of-flight to characterize a case of anti-PD-1-associted autoimmune gastritis. This study reveals gastritis characterized by severe mucosal injury, IFN-γ-producing gastric epithelial cells, and inflammation that includes CD8 and CD4 T cell infiltrates with reduced expression of granzyme B and FOXP3, respectively.

The immune system and placenta have a dynamic relationship across gestation to accommodate fetal growth and development. High-resolution characterization of this maternal-fetal interface is necessary to better understand the immunology of pregnancy and its complications. We developed a single-cell framework to simultaneously immuno-phenotype circulating, endovascular, and tissue-resident cells at the maternal-fetal interface throughout gestation, discriminating maternal and fetal contributions. Our data reveal distinct immune profiles across the endovascular and tissue compartments with tractable dynamics throughout gestation that respond to a systemic immune challenge in a gestationally dependent manner. We uncover a significant role for the innate immune system where phagocytes and neutrophils drive temporal organization of the placenta through remarkably diverse populations, including PD-L1

Alzheimer’s disease (AD) differentially and specifically affects brain regions and neuronal cell types in a predictable pattern. Damage to the brain appears to spread and worsens with time, taking over more regions and activating multiple stressors that can converge to promote vulnerability of certain cell types. At the same time, other cell types and brain regions remain intact in the face of this onslaught of neuropathology. Although neuropathologic descriptions of AD have been extensively expanded and mapped over the last several decades, our understanding of the mechanisms underlying how certain regions and cell populations are specifically vulnerable or resistant has lagged behind. In this review, we detail what is known about the selectivity of local initiation of AD pathology in the hippocampus, its proposed spread via synaptic connections, and the diversity of clinical phenotypes and brain atrophy patterns that may arise from different fibrillar strains of pathologic proteins or genetic predispositions. We summarize accumulated and emerging knowledge of the cellular and molecular basis for neuroanatomic selectivity, consider potential disease-relevant differences between vulnerable and resistant neuronal cell types and isolate molecular markers to identify them.

Cellular products derived from the activity of DNA, RNA, and protein synthesis collectively control cell identity and function. Yet there is little information on how these three biosynthesis activities are coordinated during transient and sparse cellular processes, such as activation and differentiation. Here, we describe Simultaneous Overview of tri-Molecule Biosynthesis (SOM3B), a molecular labeling and simultaneous detection strategy to quantify DNA, RNA, and protein synthesis in individual cells. Comprehensive interrogation of biosynthesis activities during transient cell states, such as progression through cell cycle or cellular differentiation, is achieved by partnering SOM3B with parallel quantification of select biomolecules with conjugated antibody reagents. Here, we investigate differential de novo DNA, RNA, and protein synthesis dynamics in transformed human cell lines, primary activated human immune cells, and across the healthy human hematopoietic continuum, all at a single-cell resolution., Simultaneous quantification of DNA, RNA and protein at the single cell level has not yet been possible. Here the authors introduce a molecular labelling and detection strategy to quantify synthesis of these biomolecules and couple it to transient cell states through parallel quantification of state-dependent biomolecules.

Selective differentiation of naive T cells into multipotent T cells is of great interest clinically for the generation of cell-based cancer immunotherapies. Cellular differentiation depends crucially on division state and time. Here we adapt a dye dilution assay for tracking cell proliferative history through mass cytometry and uncouple division, time and regulatory protein expression in single naive human T cells during their activation and expansion in a complex ex vivo milieu. Using 23 markers, we defined groups of proteins controlled predominantly by division state or time and found that undivided cells account for the majority of phenotypic diversity. We next built a map of cell state changes during naive T-cell expansion. By examining cell signaling on this map, we rationally selected ibrutinib, a BTK and ITK inhibitor, and administered it before T cell activation to direct differentiation toward a T stem cell memory (TSCM)-like phenotype. This method for tracing cell fate across division states and time can be broadly applied for directing cellular differentiation.

Background Synaptic alterations, especially presynaptic changes, are cardinal features of neurodegenerative diseases and strongly correlate with cognitive decline. New method We report “Mass Synaptometry” for the high-dimensional analysis of individual human synaptosomes, enriched nerve terminals from brain. This method was adapted from cytometry by time-of-flight mass spectrometry (CyTOF), which is commonly used for single-cell analysis of immune and blood cells. Result Here we overcome challenges for single synapse analysis by optimizing synaptosome preparations, generating a ‘SynTOF panel,’ recalibrating acquisition settings, and applying computational analyses. Through the analysis of 390,000 individual synaptosomes, we also provide proof-of principle validation by characterizing changes in synaptic diversity in Lewy Body Disease (LBD), Alzheimer’s disease and normal brain. Comparison with existing method(s) Current imaging methods to study synapses in humans are capable of analyzing a limited number of synapses, and conventional flow cytometric techniques are typically restricted to fewer than 6 parameters. Our method allows for the simultaneous detection of 34 parameters from tens of thousands of individual synapses. Conclusion We applied Mass Synaptometry to analyze 34 parameters simultaneously on more than 390,000 synaptosomes from 13 human brain samples. This new approach revealed regional and disease-specific changes in synaptic phenotypes, including validation of this method with the expected changes in the molecular composition of striatal dopaminergic synapses in Lewy body disease and Alzheimer’s disease. Mass synaptometry enables highly parallel molecular profiling of individual synaptic terminals.

Purpose: Immunoprofiling to identify biomarkers and integration with clinical trial outcomes are critical to improving immunotherapy approaches for patients with cancer. However, the translational potential of individual studies is often limited by small sample size of trials and the complexity of immuno-oncology biomarkers. Variability in assay performance further limits comparison and interpretation of data across studies and laboratories. Experimental Design: To enable a systematic approach to biomarker identification and correlation with clinical outcome across trials, the Cancer Immune Monitoring and Analysis Centers and Cancer Immunologic Data Commons (CIMAC-CIDC) Network was established through support of the Cancer MoonshotSM Initiative of the National Cancer Institute (NCI) and the Partnership for Accelerating Cancer Therapies (PACT) with industry partners via the Foundation for the NIH. Results: The CIMAC-CIDC Network is composed of four academic centers with multidisciplinary expertise in cancer immunotherapy that perform validated and harmonized assays for immunoprofiling and conduct correlative analyses. A data coordinating center (CIDC) provides the computational expertise and informatics platforms for the storage, integration, and analysis of biomarker and clinical data. Conclusions: This overview highlights strategies for assay harmonization to enable cross-trial and cross-site data analysis and describes key elements for establishing a network to enhance immuno-oncology biomarker development. These include an operational infrastructure, validation and harmonization of core immunoprofiling assays, platforms for data ingestion and integration, and access to specimens from clinical trials. Published in the same volume are reports of harmonization for core analyses: whole-exome sequencing, RNA sequencing, cytometry by time of flight, and IHC/immunofluorescence.

Granulocytes encompass diverse roles, from fighting off pathogens to regulating inflammatory processes in allergies. These roles are represented by distinct cellular phenotypes that we captured with mass cytometry (CyTOF). Our protocol enables simultaneous evaluation of human basophils, eosinophils, and neutrophils under homeostasis and upon immune activation by anti-Immunoglobulin E (anti-IgE) or interleukin-3 (IL-3). Granulocyte integrity and detection of protein markers were optimized so that rare granulocyte populations could be deeply characterized by single cell mass cytometry. For complete details on the use and execution of this protocol, please refer to Vivanco Gonzalez et al. (2020).

Innate pattern recognition receptor agonists, including Toll-like receptors (TLRs), alter the tumor microenvironment and prime adaptive antitumor immunity. However, TLR agonists present toxicities associated with widespread immune activation after systemic administration. To design a TLR-based therapeutic suitable for systemic delivery and capable of safely eliciting tumor-targeted responses, we developed immune-stimulating antibody conjugates (ISACs) comprising a TLR7/8 dual agonist conjugated to tumor-targeting antibodies. Systemically administered human epidermal growth factor receptor 2 (HER2)-targeted ISACs were well tolerated and triggered a localized immune response in the tumor microenvironment that resulted in tumor clearance and immunological memory. Mechanistically, ISACs required tumor antigen recognition, Fcγ-receptor-dependent phagocytosis and TLR-mediated activation to drive tumor killing by myeloid cells and subsequent T-cell-mediated antitumor immunity. ISAC-mediated immunological memory was not limited to the HER2 ISAC target antigen since ISAC-treated mice were protected from rechallenge with the HER2− parental tumor. These results provide a strong rationale for the clinical development of ISACs. Alonso and colleagues develop immune-stimulating antibody conjugates capable of specific delivery of TLR7/8 agonists to tumors, which induces durable antitumor immunity.

Diagnosing lymphomas and leukemias requires challenging integration of microscopically-visible cellular morphology and antibody-identified cell type-specific molecule expression. Here, we merge these orthogonal techniques onto a single, high-throughput, highly-multiplexed, single cell assay. Using single cell mass cytometry, we simultaneously quantify 12 molecular components underlying cell morphological features with a multitude of phenotypes across 71 diverse hematologic diagnoses. This method, “single cell morphometric profiling,” reveals robust patterns of “morphometric” markers for each microscopically-identifiable cell type, distinct from other cell lineages. Individual features have particular diagnostic utilities, such as: VAMP-7 for flow cytometric side scatter; lamin B1 and rRNA highlighting progenitor populations comprising acute leukemias; and lamin A/C distinguishing mature T-cell lymphomas from normal T-cells. Computationally combined with machine learning, they form consistent two-dimensional maps for visualizing sample composition and tracing differentiation of normal and leukemic myeloid cells. Benchmarking against hematopathologists, we used morphometric machine learning for blast enumeration in myeloid leukemias – a classically difficult problem with existing technologies. Integrating morphometry with deep surface immunophenotyping yields a versatile platform amendable to both traditional cytometry plots and high-dimensional augmentation with new diagnostic capabilities, lending itself to automation for routine, systematic hematopathology diagnosis.

SUMMARY Ductal carcinoma in situ (DCIS) is a pre-invasive lesion that is thought to be a precursor to invasive breast cancer (IBC). To understand the changes in the tumor microenvironment (TME) accompanying transition to IBC, we used multiplexed ion beam imaging by time of flight (MIBI-TOF) and a 37-plex antibody staining panel to interrogate 79 clinically annotated surgical resections using machine learning tools for cell segmentation, pixel-based clustering, and object morphometrics. Comparison of normal breast with patient-matched DCIS and IBC revealed coordinated transitions between four TME states that were delineated based on the location and function of myoepithelium, fibroblasts, and immune cells. Surprisingly, myoepithelial disruption was more advanced in DCIS patients that did not develop IBC, suggesting this process could be protective against recurrence. Taken together, this HTAN Breast PreCancer Atlas study offers insight into drivers of IBC relapse and emphasizes the importance of the TME in regulating these processes., In brief A spatial imaging atlas of patient-matched ductal carcinoma in situ and invasive breast cancer depicts coordinated changes in the tumor microenviroment associated with invasive relapse, suggesting a potential protective role of myoepithelial disruption against invasive progression., Graphical Abstract

Insight into the cancer cell populations that are responsible for relapsed disease is needed to improve outcomes. Here we report a single-cell-based study of B cell precursor acute lymphoblastic leukemia at diagnosis that reveals hidden developmentally dependent cell signaling states that are uniquely associated with relapse. By using mass cytometry we simultaneously quantified 35 proteins involved in B cell development in 60 primary diagnostic samples. Each leukemia cell was then matched to its nearest healthy B cell population by a developmental classifier that operated at the single-cell level. Machine learning identified six features of expanded leukemic populations that were sufficient to predict patient relapse at diagnosis. These features implicated the pro-BII subpopulation of B cells with activated mTOR signaling, and the pre-BI subpopulation of B cells with activated and unresponsive pre-B cell receptor signaling, to be associated with relapse. This model, termed 'developmentally dependent predictor of relapse' (DDPR), significantly improves currently established risk stratification methods. DDPR features exist at diagnosis and persist at relapse. By leveraging a data-driven approach, we demonstrate the predictive value of single-cell 'omics' for patient stratification in a translational setting and provide a framework for its application to human cancer.

The cellular complexity and functional diversity of the human immune system necessitate the use of high-dimensional single-cell tools to uncover its role in multifaceted diseases such as rheumatic diseases, as well as other autoimmune and inflammatory disorders. Proteomic technologies that use elemental (heavy metal) reporter ions, such as mass cytometry (also known as CyTOF) and analogous high-dimensional imaging approaches (including multiplexed ion beam imaging (MIBI) and imaging mass cytometry (IMC)), have been developed from their low-dimensional counterparts, flow cytometry and immunohistochemistry, to meet this need. A growing number of studies have been published that use these technologies to identify functional biomarkers and therapeutic targets in rheumatic diseases, but the full potential of their application to rheumatic disease research has yet to be fulfilled. This Review introduces the underlying technologies for high-dimensional immune monitoring and discusses aspects necessary for their successful implementation, including study design principles, analytical tools and future developments for the field of rheumatology.

This study defines a single-cell proteomic atlas of human OA cartilage to reveal rare subpopulations that stratify patients., Aging or injury leads to degradation of the cartilage matrix and the development of osteoarthritis (OA). Because of a paucity of single-cell studies of OA cartilage, little is known about the interpatient variability in its cellular composition and, more importantly, about the cell subpopulations that drive the disease. Here, we profiled healthy and OA cartilage samples using mass cytometry to establish a single-cell atlas, revealing distinct chondrocyte progenitor and inflammation-modulating subpopulations. These rare populations include an inflammation-amplifying (Inf-A) population, marked by interleukin-1 receptor 1 and tumor necrosis factor receptor II, whose inhibition decreased inflammation, and an inflammation-dampening (Inf-D) population, marked by CD24, which is resistant to inflammation. We devised a pharmacological strategy targeting Inf-A and Inf-D cells that significantly decreased inflammation in OA chondrocytes. Using our atlas, we stratified patients with OA in three groups that are distinguished by the relative proportions of inflammatory to regenerative cells, making it possible to devise precision therapeutic approaches.

Elucidating the spectrum of epithelial-mesenchymal transition (EMT) and mesenchymal-epithelial transition (MET) states in clinical samples promises insights on cancer progression and drug resistance. Using mass cytometry time-course analysis, we resolve lung cancer EMT states through TGFβ-treatment and identify, through TGFβ-withdrawal, a distinct MET state. We demonstrate significant differences between EMT and MET trajectories using a computational tool (TRACER) for reconstructing trajectories between cell states. In addition, we construct a lung cancer reference map of EMT and MET states referred to as the EMT-MET PHENOtypic STAte MaP (PHENOSTAMP). Using a neural net algorithm, we project clinical samples onto the EMT-MET PHENOSTAMP to characterize their phenotypic profile with single-cell resolution in terms of our in vitro EMT-MET analysis. In summary, we provide a framework to phenotypically characterize clinical samples in the context of in vitro EMT-MET findings which could help assess clinical relevance of EMT in cancer in future studies., Intermediate transitions between epithelial and mesenchymal states are associated with tumor progression. Here using mass cytometry, Plevritis and colleagues develop a computational framework to resolve and map these trajectories in lung cancer cells and clinical specimens.

The advent of mass cytometry (CyTOF®) has permitted simultaneous detection of more than 40 antibody parameters at the single-cell level, although a limited number of metal-labeled antibodies are commercially available. Here we present optimized and scalable protocols for conjugation of lanthanide as well as bismuth ions to immunoglobulin (Ig) using a maleimide-functionalized chelating polymer and for characterization of the conjugate. The maleimide functional group is reactive with cysteine sulfhydryl groups generated through partial reduction of the Ig Fc region. Incubation of Ig with polymer pre-loaded with lanthanide ions produces metal-labeled Ig without disrupting antigen specificity. Antibody recovery rates can be determined by UV spectrophotometry and frequently exceeds 60%. Each custom-conjugated antibody is validated using positive and negative cellular control populations and is titrated for optimal staining at concentrations ranging from 0.1 to 10μg/mL. The preparation of metal-labeled antibodies can be completed in 4.5h, and titration requires an additional 3-5h.

High-throughput single-cell technologies provide an unprecedented view into cellular heterogeneity, yet they pose new challenges in data analysis and interpretation. In this protocol, we describe the use of Spanning-tree Progression Analysis of Density-normalized Events (SPADE), a density-based algorithm for visualizing single-cell data and enabling cellular hierarchy inference among subpopulations of similar cells. It was initially developed for flow and mass cytometry single-cell data. We describe SPADE's implementation and application using an open-source R package that runs on Mac OS X, Linux and Windows systems. A typical SPADE analysis on a 2.27-GHz processor laptop takes ∼5 min. We demonstrate the applicability of SPADE to single-cell RNA-seq data. We compare SPADE with recently developed single-cell visualization approaches based on the t-distribution stochastic neighborhood embedding (t-SNE) algorithm. We contrast the implementation and outputs of these methods for normal and malignant hematopoietic cells analyzed by mass cytometry and provide recommendations for appropriate use. Finally, we provide an integrative strategy that combines the strengths of t-SNE and SPADE to infer cellular hierarchy from high-dimensional single-cell data.

Summary B cells are capable of a wide range of effector functions including antibody secretion, antigen presentation, cytokine production, and generation of immunological memory. A consistent strategy for classifying human B cells by using surface molecules is essential to harness this functional diversity for clinical translation. We developed a highly multiplexed screen to quantify the co-expression of 351 surface molecules on millions of human B cells. We identified differentially expressed molecules and aligned their variance with isotype usage, VDJ sequence, metabolic profile, biosynthesis activity, and signaling response. Based on these analyses, we propose a classification scheme to segregate B cells from four lymphoid tissues into twelve unique subsets, including a CD45RB+CD27− early memory population, a class-switched CD39+ tonsil-resident population, and a CD19hiCD11c+ memory population that potently responds to immune activation. This classification framework and underlying datasets provide a resource for further investigations of human B cell identity and function., Graphical Abstract, Highlights • A mass cytometry screen reveals 98 surface molecules expressed by human B cells • High-dimensional analysis identifies twelve B cell subsets across four tissues • CD45RB, CD11c, CD39, CD73, and CD95 define subsets of antigen-experienced B cells • Isotype usage, signaling, and metabolism vary in accordance with cell surface phenotype, To identify molecules that distinguish functionally distinct subsets of human B cells, Glass et al. screened the expression of 351 surface molecules by mass cytometry. By combining identified molecules with functional readouts, they propose a new classification scheme to segregate B cells from four lymphoid tissues into twelve unique subsets.

Summary The success of immunotherapy has led to a myriad of clinical trials accompanied by efforts to gain mechanistic insight and identify predictive signatures for personalization. However, many immune monitoring technologies face investigator bias, missing unanticipated cellular responses in limited clinical material. We present here a mass cytometry (CyTOF) workflow for standardized, systems-level biomarker discovery in immunotherapy trials. To broadly enumerate immune cell identity and activity, we established and extensively assessed a reference panel of 33 antibodies to cover major cell subsets, simultaneously quantifying activation and immune checkpoint molecules in a single assay. This assay enumerates ≥98% of peripheral immune cells with ≥4 positively identifying antigens. Robustness and reproducibility are demonstrated on multiple samples types, across two research centers and by orthogonal measurements. Using automated analysis, we identify stratifying immune signatures in bone marrow transplantation-associated graft-versus-host disease. Together, this validated workflow ensures comprehensive immunophenotypic analysis and data comparability and will accelerate biomarker discovery., Graphical Abstract, Highlights • Single assay to identify and characterize all major human immune cell lineages • Readily available and extensively validated antibody panel • Additional (>10) targets can be added to meet specific hypotheses • Allows identification of disease-associated immune signatures and biomarkers, Hartmann et al. provide an experimental framework to identify and characterize all major human immune cell lineages in a single assay using mass cytometry (CyTOF). This validated and readily available workflow ensures comprehensive immunophenotypic analysis, improves data comparability, and allows identification of disease-associated immune signatures and biomarkers for human immunotherapy.

Recent advances in single-cell molecular analytical methods and clonal growth assays are enabling more refined models of human hematopoietic lineage restriction processes to be conceptualized. Here, we report the results of integrating single-cell proteome measurements with clonally determined lymphoid, neutrophilic/monocytic, and/or erythroid progeny outputs from >1000 index-sorted CD34(+) human cord blood cells in short-term cultures with and without stromal cells. Surface phenotypes of functionally examined cells were individually mapped onto a molecular landscape of the entire CD34(+) compartment constructed from single-cell mass cytometric measurements of 14 cell surface markers, 20 signaling/cell cycle proteins, and 6 transcription factors in ∼300 000 cells. This analysis showed that conventionally defined subsets of CD34(+) cord blood cells are heterogeneous in their functional properties, transcription factor content, and signaling activities. Importantly, this molecular heterogeneity was reduced but not eliminated in phenotypes that were found to display highly restricted lineage outputs. Integration of the complete proteomic and functional data sets obtained revealed a continuous probabilistic topology of change that includes a multiplicity of lineage restriction trajectories. Each of these reflects progressive but variable changes in the levels of specific signaling intermediates and transcription factors but shared features of decreasing quiescence. Taken together, our results suggest a model in which increasingly narrowed hematopoietic output capabilities in neonatal CD34(+) cord blood cells are determined by a history of external stimulation in combination with innately programmed cell state changes.

Advances in single-cell mass cytometry have increasingly improved highly multidimensional characterization of immune cell heterogeneity. The immunoassay multiplexing capacity relies on monoclonal antibodies labeled with stable heavy-metal isotopes. To date, a variety of rare-earth elements and noble and post-transition metal isotopes have been used in mass cytometry; nevertheless, the methods used for antibody conjugation differ because of the individual metal coordination chemistries and distinct stabilities of various metal cations. Herein, we provide three optimized protocols for conjugating monoclonal IgG antibodies with 48 high-purity heavy-metal isotopes: (i) 38 isotopes of lanthanides, 2 isotopes of indium, and 1 isotope of yttrium; (ii) 6 isotopes of palladium; and (iii) 1 isotope of bismuth. Bifunctional chelating agents containing coordinative ligands of monomeric DOTA (1,4,7,10-tetraazacyclododecane-1,4,7,10-tetraacetic acid) or polymeric pentetic acid (DTPA) were used to stably sequester isotopic cations in aqueous solutions and were subsequently coupled to IgG antibodies using site-specific biorthogonal reactions. Furthermore, quantification methods based on antibody inherent absorption at 280 nm and on extrinsic absorption at 562 nm after staining with bicinchoninic acid (BCA) are reported to determine metal-isotope-tagged antibodies. In addition, a freeze-drying procedure to prepare palladium isotopic mass tags is described. To demonstrate the utility, experiments using six palladium-tagged CD45 antibodies for barcoding assays of live immune cells in cytometry by time-of-flight (CyTOF) are described. Conjugation of pure isotopes of lanthanides, indium, or yttrium takes ~3.5 h. Conjugation of bismuth takes ~4 h. Preparation of palladium mass tags takes ~8 h. Conjugation of pure isotopes of palladium takes ~2.5 h. Antibody titration takes ~4 h.

Single-cell barcoding enables the combined processing and acquisition of multiple individual samples as one. This maximizes assay efficiency and eliminates technical variability in both sample preparation and analysis. Remaining challenges are the barcoding of live, unprocessed cells to increase downstream assay performance combined with the flexibility of the approach towards a broad range of cell types. To that end, we developed a novel antibody-based platform that allows the robust barcoding of live human cells for mass cytometry (CyTOF). By targeting both the MHC class I complex (beta-2-microglobulin) and a broadly expressed sodium-potassium ATPase-subunit (CD298) with platinum-conjugated antibodies, human immune cells, stem cells as well as tumor cells could be multiplexed in the same single-cell assay. In addition, we present a novel palladium-based covalent viability reagent compatible with this barcoding strategy. Altogether, this platform enables mass cytometry-based, live-cell barcoding across a multitude of human sample types and provides a scheme for multiplexed barcoding of human single-cell assays in general.

Significance Single-cell high-throughput technologies enable the ability to identify combination cancer therapies that account for intratumoral heterogeneity, a phenomenon that has been shown to influence the effectiveness of cancer treatment. We developed and applied an approach that identifies top-ranking drug combinations based on the single-cell perturbation response when an individual tumor sample is screened against a panel of single drugs. This approach optimizes drug combinations by choosing the minimum number of drugs that produce the maximal intracellular desired effects for an individual sample., An individual malignant tumor is composed of a heterogeneous collection of single cells with distinct molecular and phenotypic features, a phenomenon termed intratumoral heterogeneity. Intratumoral heterogeneity poses challenges for cancer treatment, motivating the need for combination therapies. Single-cell technologies are now available to guide effective drug combinations by accounting for intratumoral heterogeneity through the analysis of the signaling perturbations of an individual tumor sample screened by a drug panel. In particular, Mass Cytometry Time-of-Flight (CyTOF) is a high-throughput single-cell technology that enables the simultaneous measurements of multiple (>40) intracellular and surface markers at the level of single cells for hundreds of thousands of cells in a sample. We developed a computational framework, entitled Drug Nested Effects Models (DRUG-NEM), to analyze CyTOF single-drug perturbation data for the purpose of individualizing drug combinations. DRUG-NEM optimizes drug combinations by choosing the minimum number of drugs that produce the maximal desired intracellular effects based on nested effects modeling. We demonstrate the performance of DRUG-NEM using single-cell drug perturbation data from tumor cell lines and primary leukemia samples.

The present study describes an efficient and reliable method for the preparation of MS2 viral capsids that are synthetically modified with antibodies using a rapid oxidative coupling strategy. The overall protocol delivers conjugates in high yields and recoveries, requires a minimal excess of antibody to achieve modification of more than 95% of capsids, and can be completed in a short period of time. Antibody-capsid conjugates targeting extracellular receptors on human breast cancer cell lines were prepared and characterized. Notably, conjugation to the capsid did not significantly perturb the binding of the antibodies, as indicated by binding affinities similar to those obtained for the parent antibodies. An array of conjugates was synthesized with various reporters on the interior surface of the capsids to be used in cell studies, including fluorescence-based flow cytometry, confocal microscopy, and mass cytometry. The results of these studies lay the foundation for further exploration of these constructs in the context of clinically relevant applications, including drug delivery and in vivo diagnostics.

Immune responses involve coordination across cell types and tissues. However, studies in cancer immunotherapy have focused heavily on local immune responses in the tumor microenvironment. To investigate immune activity more broadly, we performed an organism-wide study in genetically engineered cancer models using mass cytometry. We analyzed immune responses in several tissues after immunotherapy by developing intuitive models for visualizing single-cell data with statistical inference. Immune activation was evident in the tumor and systemically shortly after effective therapy was administered. However, during tumor rejection, only peripheral immune cells sustained their proliferation. This systemic response was coordinated across tissues and required for tumor eradication in several immunotherapy models. An emergent population of peripheral CD4 Tcells conferred protection against new tumors and was significantly expanded in patients responding to immunotherapy. These studies demonstrate the critical impact of systemic immune responses that drive tumor rejection.

Mutant RAS oncoproteins activate signaling molecules that drive oncogenesis in multiple human tumors including acute myelogenous leukemia (AML). However, the specific functions of these pathways in AML are unclear, thwarting the rational application of targeted therapeutics. To elucidate the downstream functions of activated NRAS in AML, we used a murine model that harbors Mll-AF9 and a tetracycline-repressible, activated NRAS (NRAS(G12V)). Using computational approaches to explore our gene-expression data sets, we found that NRAS(G12V) enforced the leukemia self-renewal gene-expression signature and was required to maintain an MLL-AF9- and Myb-dependent leukemia self-renewal gene-expression program. NRAS(G12V) was required for leukemia self-renewal independent of its effects on growth and survival. Analysis of the gene-expression patterns of leukemic subpopulations revealed that the NRAS(G12V)-mediated leukemia self-renewal signature is preferentially expressed in the leukemia stem cell-enriched subpopulation. In a multiplexed analysis of RAS-dependent signaling, Mac-1(Low) cells, which harbor leukemia stem cells, were preferentially sensitive to NRAS(G12V) withdrawal. NRAS(G12V) maintained leukemia self-renewal through mTOR and MEK pathway activation, implicating these pathways as potential targets for cancer stem cell-specific therapies. Together, these experimental results define a RAS oncogene-driven function that is critical for leukemia maintenance and represents a novel mechanism of oncogene addiction.

Summary Although pathogens must infect differentiated host cells that exhibit substantial diversity, documenting the consequences of infection against this heterogeneity is challenging. Single-cell mass cytometry permits deep profiling based on combinatorial expression of surface and intracellular proteins. We used this method to investigate varicella-zoster virus (VZV) infection of tonsil T cells, which mediate viral transport to skin. Our results indicate that VZV induces a continuum of changes regardless of basal phenotypic and functional T cell characteristics. Contrary to the premise that VZV selectively infects T cells with skin trafficking profiles, VZV infection altered T cell surface proteins to enhance or induce these properties. Zap70 and Akt signaling pathways that trigger such surface changes were activated in VZV-infected naive and memory cells by a T cell receptor (TCR)-independent process. Single-cell mass cytometry is likely to be broadly relevant for demonstrating how intracellular pathogens modulate differentiated cells to support pathogenesis in the natural host.

This work summarizes cellular apoptotic and signaling response to TRAIL across 10 cell lines and for the first time links signaling diversity to nongenetic resistance. This high-dimensional, single-cell approach toward TRAIL resistance sets a standard in studying nongenetic resistance., TNFα-related apoptosis-inducing ligand (TRAIL), specifically initiates programmed cell death, but often fails to eradicate all cells, making it an ineffective therapy for cancer. This fractional killing is linked to cellular variation that bulk assays cannot capture. Here, we quantify the diversity in cellular signaling responses to TRAIL, linking it to apoptotic frequency across numerous cell systems with single-cell mass cytometry (CyTOF). Although all cells respond to TRAIL, a variable fraction persists without apoptotic progression. This cell-specific behavior is nonheritable where both the TRAIL-induced signaling responses and frequency of apoptotic resistance remain unaffected by prior exposure. The diversity of signaling states upon exposure is correlated to TRAIL resistance. Concomitantly, constricting the variation in signaling response with kinase inhibitors proportionally decreases TRAIL resistance. Simultaneously, TRAIL-induced de novo translation in resistant cells, when blocked by cycloheximide, abrogated all TRAIL resistance. This work highlights how cell signaling diversity, and subsequent translation response, relates to nonheritable fractional escape from TRAIL-induced apoptosis. This refined view of TRAIL resistance provides new avenues to study death ligands in general.

Several growth factors (GFs) that together promote quiescent human hematopoietic stem cell (HSC) expansion ex vivo have been identified; however, the molecular mechanisms by which these GFs regulate the survival, proliferation. and differentiation of human HSCs remain poorly understood. We now describe experiments in which we used mass cytometry to simultaneously measure multiple surface markers, transcription factors, active signaling intermediates, viability, and cell-cycle indicators in single CD34+ cord blood cells before and up to 2 hours after their stimulation with stem cell factor, Fms-like tyrosine kinase 3 ligand, interleukin-3, interleukin-6, and granulocyte colony-stimulating factor (5 GFs) either alone or combined. Cells with a CD34+CD38-CD45RA-CD90+CD49f+ (CD49f+) phenotype (∼10% HSCs with >6-month repopulating activity in immunodeficient mice) displayed rapid increases in activated STAT1/3/5, extracellular signal-regulated kinase 1/2, AKT, CREB, and S6 by 1 or more of these GFs, and β-catenin only when the 5 GFs were combined. Certain minority subsets within the CD49f+ compartment were poorly GF-responsive and, among the more GF-responsive subsets of CD49f+ cells, different signaling intermediates correlated with the levels of the myeloid- and lymphoid-associated transcription factors measured. Phenotypically similar, but CD90-CD49f- cells (MPPs) contained lower baseline levels of multiple signaling intermediates than the CD90+CD49f+ cells, but showed similar response amplitudes to the same GFs. Importantly, we found activation or inhibition of AKT and β-catenin directly altered immediate CD49f+ cell survival and proliferation. These findings identify rapid signaling events that 5 GFs elicit directly in the most primitive human hematopoietic cell types to promote their survival and proliferation.

The ability to comprehensively explore the impact of bio-active molecules on human samples at the single-cell level can provide great insight for biomedical research. Mass cytometry enables quantitative single-cell analysis with deep dimensionality, but currently lacks high-throughput capability. Here we report a method termed mass-tag cellular barcoding (MCB) that increases mass cytometry throughput by sample multiplexing. 96-well format MCB was used to characterize human peripheral blood mononuclear cell (PBMC) signaling dynamics, cell-to-cell communication, the signaling variability between 8 donors, and to define the impact of 27 inhibitors on this system. For each compound, 14 phosphorylation sites were measured in 14 PBMC types, 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. MCB enables high-content, high-throughput screening, with potential applications for drug discovery, pre-clinical testing, and mechanistic investigation of human disease.

In recent years, advances in technology have provided us with tools to quantify the expression of multiple genes in individual cells. The ability to simultaneously measure multiple genes on the same cell is necessary to resolve the incredible diversity of cell subsets, as well as to define their function in the host. Fluorescence-based flow cytometry is the benchmark for this; with it, we can quantify 18 proteins per cell, at >10,000 cells per second. “Mass cytometry” is a new technology that promises to significantly extend these capabilities. Immunophenotyping by mass spectrometry provides the ability to measure more than three dozen proteins at a rate of 1,000 cells per second. We review these cytometric technologies, capable of high-content, high-throughput single-cell assays.

Cytotoxic CD8(+) T lymphocytes directly kill infected or aberrant cells and secrete proinflammatory cytokines. By using metal-labeled probes and mass spectrometric analysis (cytometry by time-of-flight, or CyTOF) of human CD8(+) T cells, we analyzed the expression of many more proteins than previously possible with fluorescent labels, including surface markers, cytokines, and antigen specificity with modified peptide-MHC tetramers. With 3-dimensional principal component analysis (3D-PCA) to display phenotypic diversity, we observed a relatively uniform pattern of variation in all subjects tested, highlighting the interrelatedness of previously described subsets and the continuous nature of CD8(+) T cell differentiation. These data also showed much greater complexity in the CD8(+) T cell compartment than previously appreciated, including a nearly combinatorial pattern of cytokine expression, with distinct niches occupied by virus-specific cells. This large degree of functional diversity even between cells with the same specificity gives CD8(+) T cells a remarkable degree of flexibility in responding to pathogens.

Multiparametric single-cell analysis is critical for understanding cellular heterogeneity. Despite recent technological advances in single-cell measurements, methods for analyzing high-dimensional single-cell data are often subjective, labor intensive and require prior knowledge of the biological system under investigation. To objectively uncover cellular heterogeneity from single-cell measurements, we present a novel computational approach, Spanning-tree Progression Analysis of Density-normalized Events (SPADE). We applied SPADE to cytometry data of mouse and human bone marrow. In both cases, SPADE organized cells in a hierarchy of related phenotypes that partially recapitulated well-described patterns of hematopoiesis. In addition, SPADE produced a map of intracellular signal activation across the landscape of human hematopoietic development. SPADE revealed a functionally distinct cell population, natural killer (NK) cells, without using any NK-specific parameters. SPADE is a versatile method that facilitates the analysis of cellular heterogeneity, the identification of cell types, and comparison of functional markers in response to perturbations.

Human embryonic stem cells (hESCs) have unique self-renewal and differentiation properties, which are experimentally measured using functional assays. hESC cultures are known to be heterogeneous, but whether subsets of cells contribute differently to functional assays has yet to be examined. Here, using clonal tracking by retroviral integration, we analyzed in situ the propensity of individual hESCs to contribute to different functional assays. We observed different clonal distributions in teratomas versus in vitro differentiation assays. Some hESC subsets apparently contributed substantially to lineage-specific embryoid body differentiation and lacked clonogenic capacity, although they had self-renewal ability. In contrast, other subsets of self-renewing hESCs with clonogenic ability contributed to teratoma formation but were less frequently observed after in vitro differentiation. Our study suggests that assays used to measure pluripotency may detect distinct subsets of hESCs. These findings have direct implications for hESC-based therapies that may be optimized based on such functional assays.

We carried out a test sample study to try to identify errors leading to irreproducibility, including incompleteness of peptide sampling, in LC-MS-based proteomics. We distributed a test sample consisting of an equimolar mix of 20 highly purified recombinant human proteins, to 27 laboratories for identification. Each protein contained one or more unique tryptic peptides of 1250 Da to also test for ion selection and sampling in the mass spectrometer. Of the 27 labs, initially only 7 labs reported all 20 proteins correctly, and only 1 lab reported all the tryptic peptides of 1250 Da. Nevertheless, a subsequent centralized analysis of the raw data revealed that all 20 proteins and most of the 1250 Da peptides had in fact been detected by all 27 labs. The centralized analysis allowed us to determine sources of problems encountered in the study, which include missed identifications (false negatives), environmental contamination, database matching, and curation of protein identifications. Improved search engines and databases are likely to increase the fidelity of mass spectrometry-based proteomics.

The derivation and long-term maintenance of human embryonic stem cells (hESCs) has been established in culture formats that are both dependent and independent of support (feeder) cells. However, the factors responsible for preserving the viability of hESCs in a nascent state remain unknown. We describe a mass spectrometry-based method for probing the secretome of the hESC culture microenvironment to identify potential regulating protein factors that are in low abundance. Individual samples were analyzed several times, using successive mass (m/z) and retention time-directed exclusion, without sampling the same peptide ion twice. This iterative exclusion -mass spectrometry (IE-MS) approach more than doubled protein and peptide metrics in comparison to a simple repeat analysis method on the same instrument, even after extensive sample pre-fractionation. Furthermore, implementation of the IE-MS approach was shown to enhance the performance of an older quadrupole time of flight (Q-ToF) MS. The resulting number of identified peptides approached that of a parallel repeat analysis on a newer LTQ-Orbitrap MS. The combination of the results of both instruments proved to be superior to that achieved by a single instrument in the identification of additional proteins. Using the IE-MS strategy, combined with complementary gel- and solution-based fractionation methods, the hESC culture microenvironment was extensively probed. Over 10 to 12 times more extracellular proteins were observed compared with previously published surveys. The detection of previously undetectable growth factors, present at concentrations ranging from 10(-9) to 10(-11) g/ml, highlights the depth of our profiling. The IE-MS approach provides a simple and reliable technique that greatly enhances instrument performance by increasing the effective depth of MS-based proteomic profiling. This approach should be widely applicable to any LC-MS/MS instrument platform or biological system.