The use of spatial mapping tools allows for a better understanding of tissue processes in pathophysiology. However, due to specific platform-to-platform incompatibility, protocols that maximize output from a single tissue section are lacking. Moreover, a central mechanism for regulating immunoglobulin (Ig) effector functions is through Fc glycosylation. Here, we present a workflow for the sequential imaging of the same tissue section using matrix assisted laser desorption ionization (MALDI) and multiplexed ion beam imaging (MIBI). We first profiled N-glycosylation on human lymphatic tissues to investigate how Ig Fc glycosylation is regulated within B cells. We stained the same tissue sections to quantify approximately 30 protein markers, targeting the single-cell composition of B cell follicles. After spatial registration, the imaging data was combined into a single dataset where each pixel retains bimodal information (N-glycans and MIBI probes) from the same tissue section. By using MIBI markers to guide the analysis throughout the follicular regions (i.e. dark/light zone, mantle zone), we studied the dynamic changes in mannosylation, fucosylation and sialylation across unique B cell populations in situ. Overall, these findings streamline a strategy that allows mass spectrometry imaging by MALDI, high-definition spatial proteomics by MIBI and H&E on the same tissue section. Moreover, it clarifies how Ig glycosylation is structurally organized during the follicular reaction. Computational and Systems Immunology (COMP)

Gliomas are among the most lethal cancers, with limited treatment options. To uncover hallmarks of therapeutic escape and tumor microenvironment (TME) landscape, we applied spatial proteomics, transcriptomics, and glycomics to 670 lesions from 310 adult and pediatric patients. Single-cell analysis shows high B7H3+ tumor cell prevalence in glioblastoma (GBM) and pleomorphic xanthoastrocytoma, while most gliomas, including pediatric cases, express targetable tumor antigens in less than 50% of tumor cells, potentially explaining trial failures. Paired samples of isocitrate dehydrogenase (IDH)-mutant gliomas reveal recurrence driven by tumor-immune spatial reorganization, shifting from T cell and vasculature-associated myeloid cell-enriched niches to microglia and CD206+ macrophage-dominated tumors. Multi-omic integration identified N-glycosylation as the best classifier of grade, while the immune transcriptome best predicted GBM survival. Provided as a community resource, this study offers a framework for glioma targeting, classification, outcome prediction, and a baseline of TME composition across all stages.

Lymphoid specification in human hematopoietic progenitors is not fully understood. To better associate lymphoid identity with protein-level cell features, we conduct a highly multiplexed single-cell proteomic screen on human bone marrow progenitors. This screen identifies terminal deoxynucleotidyl transferase (TdT), a specialized DNA polymerase intrinsic to VDJ recombination, broadly expressed within CD34+ progenitors prior to B/T cell emergence. While these TdT+ cells coincide with granulocyte-monocyte progenitor (GMP) immunophenotype, their accessible chromatin regions show enrichment for lymphoid-associated transcription factor (TF) motifs. TdT expression on GMPs is inversely related to the SLAM family member CD84. Prospective isolation of CD84lo GMPs demonstrates robust lymphoid potentials ex vivo, while still retaining significant myeloid differentiation capacity, akin to LMPPs. This multi-omic study identifies human bone marrow lymphoid-primed progenitors, further defining the lympho-myeloid axis in human hematopoiesis.

Multiplexed ion beam imaging (MIBI) is a next-generation mass spectrometry-based microscopy technique that generates 40+ plex images of protein expression in histologic tissues, enabling detailed dissection of cellular phenotypes and histoarchitectural organization. A key bottleneck in operation occurs when users select the physical locations on the tissue for imaging. As the scale and complexity of MIBI experiments have increased, the manufacturer-provided interface and third-party tools have become increasingly unwieldy for imaging large tissue microarrays and tiled tissue areas. Thus, a web-based, interactive, what-you-see-is-what-you-get (WYSIWYG) graphical interface layer - the tile/SED/array Interface (TSAI) - was developed for users to set imaging locations using familiar and intuitive mouse gestures such as drag-and-drop, click-and-drag, and polygon drawing. Written according to web standards already built into modern web browsers, it requires no installation of external programs, extensions, or compilers. Of interest to the hundreds of current MIBI users, this interface dramatically simplifies and accelerates the setup of large, complex MIBI runs.

Multiplexed ion beam imaging (MIBI) is a next-generation mass spectrometry-based microscopy technique that generates 40+ plex images of protein expression in histologic tissues, enabling detailed dissection of cellular phenotypes and histoarchitectural organization. A key bottleneck in operation occurs when users select the physical locations on the tissue for imaging. As the scale and complexity of MIBI experiments have increased, the manufacturer-provided interface and third-party tools have become increasingly unwieldy for imaging large tissue microarrays and tiled tissue areas. Thus, a web-based, interactive, what-you-see-is-what-you-get (WYSIWYG) graphical interface layer - the tile/SED/array Interface (TSAI) - was developed for users to set imaging locations using familiar and intuitive mouse gestures such as drag-and-drop, click-and-drag, and polygon drawing. Written according to web standards already built into modern web browsers, it requires no installation of external programs, extensions, or compilers. Of interest to the hundreds of current MIBI users, this interface dramatically simplifies and accelerates the setup of large, complex MIBI runs.

Cyclic thrombocytopenia (CTP) is a rare disease of periodic platelet count oscillations. The pathogenesis of CTP remains elusive. To study the underlying pathophysiology and genetic and cellular associations with CTP, we applied systems biology approaches to 2 patients with stable platelet cycling and reciprocal thrombopoietin (TPO) cycling at multiple time points through 2 cycles. Blood transcriptome analysis revealed cycling of platelet-specific genes, which are in parallel with and precede platelet count oscillation, indicating that cyclical platelet production leads platelet count cycling in both patients. Additionally, neutrophil and erythrocyte-specific genes also showed fluctuations correlating with platelet count changes, consistent with TPO effects on hematopoietic progenitors. Moreover, we found novel genetic associations with CTP. One patient had a novel germline heterozygous loss-of-function (LOF) thrombopoietin receptor (MPL) c.1210G>A mutation, and both had pathogenic somatic gain-of-function (GOF) variants in signal transducer and activator of transcription 3 (STAT3). In addition, both patients had clonal T-cell populations that remained stable throughout platelet count cycles. These mutations and clonal T cells may potentially involve in the pathogenic baseline in these patients, rendering exaggerated persistent thrombopoiesis oscillations of their intrinsic rhythm upon homeostatic perturbations. This work provides new insights into the pathophysiology of CTP and possible therapies.

Lymphoid specification in human hematopoietic progenitors is not fully understood. To better associate lymphoid identity with protein-level cell features, we conducted a highly multiplexed single-cell proteomic screen on human bone marrow progenitors. This screen identified terminal deoxynucleotidyl transferase (TdT), a specialized DNA polymerase intrinsic to VDJ recombination, broadly expressed within CD34+ progenitors prior to B/T cell emergence. While these TdT+ cells coincided with granulocyte-monocyte progenitor (GMP) immunophenotype, their accessible chromatin regions showed enrichment for lymphoid-associated transcription factor (TF) motifs. TdT expression on GMPs was inversely related to the SLAM family member CD84. Prospective isolation of CD84 lo GMPs demonstrated robust lymphoid potential ex vivo , while still retaining significant myeloid differentiation capacity, akin to LMPPs. This multi-omic study identifies previously unappreciated lymphoid-primed progenitors, redefining the lympho-myeloid axis in human hematopoiesis.

Single-cell technologies generate large, high-dimensional datasets encompassing a diversity of omics. Dimensionality reduction enables visualization of data by representing cells in two-dimensional plots that capture the structure and heterogeneity of the original dataset. Visualizations contribute to human understanding of data and are useful for guiding both quantitative and qualitative analysis of cellular relationships. Existing algorithms are typically unsupervised, utilizing only measured features to generate manifolds, disregarding known biological labels such as cell type or experimental timepoint. Here, we repurpose the classification algorithm, linear discriminant analysis (LDA), for supervised dimensionality reduction of single-cell data. LDA identifies linear combinations of predictors that optimally separate a priori classes, enabling users to tailor visualizations to separate specific aspects of cellular heterogeneity. We implement feature selection by hybrid subset selection (HSS) and demonstrate that this flexible, computationally-efficient approach generates non-stochastic, interpretable axes amenable to diverse biological processes, such as differentiation over time and cell cycle. We benchmark HSS-LDA against several popular dimensionality reduction algorithms and illustrate its utility and versatility for exploration of single-cell mass cytometry, transcriptomics and chromatin accessibility data.

Single-cell technologies generate large, high-dimensional datasets encompassing a diversity of omics. Dimensionality reduction captures the structure and heterogeneity of the original dataset, creating lowdimensional visualizations that contribute to the human understanding of data. Existing algorithms are typically unsupervised, using measured features to generate manifolds, disregarding known biological labels such as cell type or experimental time point. We repurpose the classification algorithm, linear discriminant analysis (LDA), for supervised dimensionality reduction of single-cell data. LDA identifies linear combinations of predictors that optimally separate a priori classes, enabling the study of specific aspects of cellular heterogeneity. We implement feature selection by hybrid subset selection (HSS) and demonstrate that this computationally efficient approach generates non-stochastic, interpretable axes amenable to diverse biological processes such as differentiation over time and cell cycle. We benchmark HSS-LDA against several popular dimensionality-reduction algorithms and illustrate its utility and versatility for the exploration of single-cell mass cytometry, transcriptomics, and chromatin accessibility data.

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).

An embryo experiences increasingly complex spatial and temporal patterns of gene expression as it matures, guiding the morphogenesis of its body. Using super-resolution fluorescence microscopy in Drosophila melanogaster embryos, we observed that the nuclear distributions of transcription factors and histone modifications undergo a similar transformation of increasing heterogeneity. This spatial partitioning of the nucleus could lead to distinct local regulatory environments in space and time that are tuned for specific genes. Accordingly, transcription sites driven by different cis-regulatory regions each had their own temporally and spatially varying local histone environments, which could facilitate the finer spatial and temporal regulation of genes to consistently differentiate cells into organs and tissues. Thus, 'nuclear morphogenesis' may be a microscopic counterpart of the macroscopic process that shapes the animal body.

Natural Killer (NK) cells are cytotoxic innate lymphoid cells that contribute to clearing viral infections and cancer cells. Despite their abundance and short-lived nature, a significant source of their progenitors has not been identified in the human. We performed a multiplexed, single cell proteomic analysis of NK cell states in human bone marrow (BM). We identified a significant source (~5% of CD45+) of putative molecular progenitors (MPs) expressing NK-associated regulators ETS1 and ID2 in cells lacking the CD34sup>+ ‘stemness’ immunophenotype, instead expressing myeloid associated marks (Lin- CD34-CD38+CD45RA+CD11c+CD36+). Epigenetic analysis indicated they were primed to towards a mature NK cell lineage based on accessibility of T-Bet and EOMES programs while still possessing myeloid potential. Isolation of these NKMPs generated mature CD56sup>+ NK cells through ex vivo differentiation. This study identified new precursors to NK cell lineage commitment that could serve as a significant source for study and therapeutic application in the future.Funding Information: Data and sorting were collected/performed on an instrument in the Stanford University Shared FACS Facility obtained using NIH S10 Shared Instrument Grant S10RR027431-01(analysis) and S10RR025518-01 (sorting). Thanks to Stanford Immunology Graduate Program leadership and administration for training and support. A.A.C. was supported by the NIAID of the National Institutes of Health under award number 5T32AI007290-32, the National Science Foundation Graduate Research Fellowship Program under Grant No. DGE – 1656518 and the Stanford DARE Graduate Fellowship. Y.K was supported by the Stanford Immunology Baker Fellowship and the Korea Foundation for Advanced Studies International Fellowship. R.B. was supported by A*STAR National Science Scholarship (PHD) from A*STAR Graduate Academy, Singapore. D.R.G. was supported by a Stanford Graduate Fellowship and a Bio-X Stanford Interdisciplinary Graduate Fellowship. A.G.T. was supported by a Damon Runyon Cancer Research Foundation – DRCRF (DRG-118-16) and Stanford Department of Pathology Seed Grant. S.C.B. was supported by the NIH 1DP2OD022550-01, 1R01AG056287–01, 1R01AG057915-01, R01AG068279, 1U24CA224309-01, 5U19AI116484-02, U19 AI104209, and The Bill and Melinda Gates Foundation, and the Parker Institute for Cancer Immunotherapy.Declaration of Interests: The authors report no competing interests.Ethics Approval Statement: All samples were obtained under informed consent and in accordance with Stanford’s Institutional Review Board.

How epigenetic modulators of gene regulation affect the development and evolution of animals has been difficult to ascertain. Despite the widespread presence of histone 3 lysine 4 monomethylation (H3K4me1) on enhancers, hypomethylation appears to have minor effects on animal development and viability. In this study, we performed quantitative, unbiased and multi-dimensional explorations of key phenotypes on Drosophila melanogaster with genetically induced hypomethylation. Hypomethylation reduced transcription factor enrichment in nuclear microenvironments, leading to reduced gene expression, and phenotypes outside of standard laboratory conditions. Our developmental phenomics survey further showed that H3K4me1 hypomethylation led to context-dependent changes in morphology, metabolism, and behavior. Therefore, H3K4me1 may contribute to phenotypic evolution as a phenotypic capacitor by buffering the effects of chance, genotypes and environmental conditions on transcriptional enhancers. Quote “Developmental biologists are often not so much opposed to a role for ecology as they simply ignore it” –Doug Erwin 1

Human B cell development in adult human bone marrow (BM) is tightly regulated through well-defined stages to produce adaptive immune cells with assembled and functional B cell antigen receptor (BCR)(Martin et al., 2016). To produce mature B cells with functional immunoglobulin receptors, B cell progenitors must undergo multiple stages of highly regulated chromatin remodelling and transcriptional reprogramming which correspond to unique patterns of surface protein expression (Nutt and Kee, 2007). This complex process is frequently dysregulated in B cell neoplasia such as B cell Acute Lymphoblastic Leukemia (B-ALL). B-ALL is highly heterogenous in its phenotypic and clinical presentation, as well as in its underlying molecular features such as DNA methylation patterns and genetic aberrations (Cobaleda and Sánchez‐García, 2009). The lack of general mechanism of leukemogenesis has made it difficult to identify when and where adult and pediatric B-ALL blasts diverge from normal B cell development. Here we show that across 5 B-ALL patients and 3 cell lines with diverse phenotypic and clinical presentations, blasts are epigenetically arrested at a conserved point within healthy human B cell development.

Gene regulatory changes underlie much of phenotypic evolution. However, the evolutionary potential of regulatory evolution is unknown, because most evidence comes from either natural variation or limited experimental perturbations. Surveying an unbiased mutation library for a developmental enhancer in Drosophila melanogaster using an automated robotics pipeline, we found that most mutations alter gene expression. Our results suggest that regulatory information is distributed throughout most of a developmental enhancer and that parameters of gene expression—levels, location, and state—are convolved. The widespread pleiotropic effects of most mutations and the codependency of outputs may constrain the evolvability of developmental enhancers. Consistent with these observations, comparisons of diverse drosophilids reveal mainly stasis and apparent biases in the phenotypes influenced by this enhancer. Developmental enhancers may encode a much higher density of regulatory information than has been appreciated previously, which may impose constraints on regulatory evolution. Quote “Rock, robot rock Rock, robot rock Rock, robot rock” Daft Punk (2005)

While single-cell sequencing techniques have elucidated transcriptomic and epigenetic heterogeneities among human hematopoietic stem and progenitor cell (HSPC) populations, the corresponding proteomic level information, where the action of these regulatory networks manifests, is still missing. As cell sorting relies on surface markers, the functional capabilities and lineage specificities of HSPCs can only be evaluated after interrogation of the proteome at a single cell resolution. To that end, based on a highly-multiplexed single-cell screening framework in our lab (Glass and Tsai et al. Immunity in press) we quantified the simultaneous expression of 353 surface molecules and 79 functional intracellular molecules (TFs, chromatin regulators, metabolic enzymes) with mass cytometry. In doing this, we created a core panel with probes against intracellular markers associated with lymphoid potential to better illuminate the lympho-myeloid axis. In total, we analyzed 556,226 CD34+ bone marrow HSPCs across 3 individuals and identified 81 molecules expressed by HSPCs, with heterogeneous expression among conventionally-defined HSPC cell types. Using unsupervised clustering, we identified 11 populations and defined their unique proteomic composition. At the same time, we were able to infer the identity of HSPC cell types based on prior knowledge and impute the functional proteomic data onto canonical cell types. Most interestingly, a population mostly consists of SATB1-high CMPs exhibits a distinct epigenetic proteomic profile, such as high CTCF and H3k4me3 levels, indicating a possible decision making point in lympho-myeloid differentiation. Overall, we supply a quantified summary of the proteomes of human HSPCs and create a framework to identify and characterize progenitor populations with unique functional states along the lympho-myeloid developmental process. While single-cell sequencing techniques have elucidated transcriptomic and epigenetic heterogeneities among human hematopoietic stem and progenitor cell (HSPC) populations, the corresponding proteomic level information, where the action of these regulatory networks manifests, is still missing. As cell sorting relies on surface markers, the functional capabilities and lineage specificities of HSPCs can only be evaluated after interrogation of the proteome at a single cell resolution. To that end, based on a highly-multiplexed single-cell screening framework in our lab (Glass and Tsai et al. Immunity in press) we quantified the simultaneous expression of 353 surface molecules and 79 functional intracellular molecules (TFs, chromatin regulators, metabolic enzymes) with mass cytometry. In doing this, we created a core panel with probes against intracellular markers associated with lymphoid potential to better illuminate the lympho-myeloid axis. In total, we analyzed 556,226 CD34+ bone marrow HSPCs across 3 individuals and identified 81 molecules expressed by HSPCs, with heterogeneous expression among conventionally-defined HSPC cell types. Using unsupervised clustering, we identified 11 populations and defined their unique proteomic composition. At the same time, we were able to infer the identity of HSPC cell types based on prior knowledge and impute the functional proteomic data onto canonical cell types. Most interestingly, a population mostly consists of SATB1-high CMPs exhibits a distinct epigenetic proteomic profile, such as high CTCF and H3k4me3 levels, indicating a possible decision making point in lympho-myeloid differentiation. Overall, we supply a quantified summary of the proteomes of human HSPCs and create a framework to identify and characterize progenitor populations with unique functional states along the lympho-myeloid developmental process.

Changes in gene regulation underlie much of phenotypic evolution1. However, our understanding of the potential for regulatory evolution is biased, because most evidence comes from either natural variation or limited experimental perturbations2. Using an automated robotics pipeline, we surveyed an unbiased mutation library for a developmental enhancer in Drosophila melanogaster. We found that almost all mutations altered gene expression and that parameters of gene expression-levels, location, and state-were convolved. The widespread pleiotropic effects of most mutations may constrain the evolvability of developmental enhancers. Consistent with these observations, comparisons of diverse Drosophila larvae revealed apparent biases in the phenotypes influenced by the enhancer. Developmental enhancers may encode a higher density of regulatory information than has been appreciated previously, imposing constraints on regulatory evolution.

The diagnosis of lymphomas and leukemias requires hematopathologists to integrate microscopically visible cellular morphology with antibody-identified cell surface molecule expression. To merge these into one high-throughput, highly multiplexed, single-cell assay, we quantify cell morphological features by their underlying, antibody-measurable molecular components, which empowers mass cytometers to ‘see’ like pathologists. When applied to 71 diverse clinical samples, single-cell morphometric profiling reveals robust and distinct patterns of ‘morphometric’ markers for each major cell type. Individually, lamin B1 highlights acute leukemias, lamin A/C helps distinguish normal from neoplastic mature T cells, and VAMP-7 recapitulates light-cytometric side scatter. Combined with machine learning, morphometric markers form intuitive visualizations of normal and neoplastic cellular distribution and differentiation. When recalibrated for myelomonocytic blast enumeration, this approach is superior to flow cytometry and comparable to expert microscopy, bypassing years of specialized training. The contextualization of traditional surface markers on independent morphometric frameworks permits more sensitive and automated diagnosis of complex hematopoietic diseases. A scalable mass cytometry-based method for morphometrically classifying hematopoietic cells demonstrates diagnostic utility when applied to clinical samples.

To evaluate the impact of heterogeneous B cells in health and disease, comprehensive profiling is needed at a single cell resolution. We developed a highly-multiplexed screen to quantify the co-expression of 351 surface molecules on low numbers of primary cells. We identified dozens of differentially expressed molecules and aligned their variance with B cell isotype usage, metabolism, biosynthesis activity, and signaling response. Here, we propose a new classification scheme to segregate peripheral blood B cells into ten unique subsets, including a CD45RB+ CD27- early memory population and a CD19 hi CD11c+ memory population that is a potent responder to immune activation. Furthermore, we quantify the contributions of antibody isotype and cell surface phenotype to various cell processes and find that phenotype largely drives B cell function. Taken together, these findings provide an extensive profile of human B cell diversity that can serve as a resource for further immunological investigations.