Integration of whole transcriptome spatial profiling with protein markers.

Spatial transcriptomics and proteomics provide complementary information that independently transformed our understanding of complex biological processes. However, experimental integration of these modalities is limited. To overcome this, we developed Spatial PrOtein and Transcriptome Sequencing (SPOTS) for high-throughput simultaneous spatial transcriptomics and protein profiling. Compared with unimodal measurements, SPOTS substantially improves signal resolution and cell clustering and enhances the discovery power in differential gene expression analysis across tissue regions.

Intratumor heterogeneity and T cell exhaustion in primary CNS lymphoma.

BACKGROUND: Primary central nervous system lymphoma (PCNSL) is a rare lymphoma of the central nervous system, usually of diffuse large B cell phenotype. Stereotactic biopsy followed by histopathology is the diagnostic standard. However, limited material is available from CNS biopsies, thus impeding an in-depth characterization of PCNSL. METHODS: We performed flow cytometry, single-cell RNA sequencing, and B cell receptor sequencing of PCNSL cells released from biopsy material, blood, and cerebrospinal fluid (CSF), and spatial transcriptomics of biopsy samples. RESULTS: PCNSL-released cells were predominantly activated CD19+CD20+CD38+CD27+ B cells. In single-cell RNA sequencing, PCNSL cells were transcriptionally heterogeneous, forming multiple malignant B cell clusters. Hyperexpanded B cell clones were shared between biopsy- and CSF- but not blood-derived cells. T cells in the tumor microenvironment upregulated immune checkpoint molecules, thereby recognizing immune evasion signals from PCNSL cells. Spatial transcriptomics revealed heterogeneous spatial organization of malignant B cell clusters, mirroring their transcriptional heterogeneity across patients, and pronounced expression of T cell exhaustion markers, co-localizing with a highly malignant B cell cluster. CONCLUSIONS: Malignant B cells in PCNSL show transcriptional and spatial intratumor heterogeneity. T cell exhaustion is frequent in the PCNSL microenvironment, co-localizes with malignant cells, and highlights the potential of personalized treatments.

A RORγt+ cell instructs gut microbiota-specific Treg cell differentiation.

The mutualistic relationship of gut-resident microbiota and the host immune system promotes homeostasis that ensures maintenance of the microbial community and of a largely non-aggressive immune cell compartment1,2. The consequences of disturbing this balance include proximal inflammatory conditions, such as Crohn's disease, and systemic illnesses. This equilibrium is achieved in part through the induction of both effector and suppressor arms of the adaptive immune system. Helicobacter species induce T regulatory (Treg) and T follicular helper (TFH) cells under homeostatic conditions, but induce inflammatory T helper 17 (TH17) cells when induced Treg (iTreg) cells are compromised3,4. How Helicobacter and other gut bacteria direct T cells to adopt distinct functions remains poorly understood. Here we investigated the cells and molecular components required for iTreg cell differentiation. We found that antigen presentation by cells expressing RORγt, rather than by classical dendritic cells, was required and sufficient for induction of Treg cells. These RORγt+ cells-probably type 3 innate lymphoid cells and/or Janus cells5-require the antigen-presentation machinery, the chemokine receptor CCR7 and the TGFß activator αv integrin. In the absence of any of these factors, there was expansion of pathogenic TH17 cells instead of iTreg cells, induced by CCR7-independent antigen-presenting cells. Thus, intestinal commensal microbes and their products target multiple antigen-presenting cells with pre-determined features suited to directing appropriate T cell differentiation programmes, rather than a common antigen-presenting cell that they endow with appropriate functions.

Multiplexed single-cell analysis reveals prognostic and nonprognostic T cell types in human colorectal cancer.

Clinical outcomes in colorectal cancer (CRC) correlate with T cell infiltrates, but the specific contributions of heterogenous T cell types remain unclear. To investigate the diverse function of T cells in CRC, we profiled 37,931 T cells from tumors and adjacent normal colon of 16 patients with CRC with respect to transcriptome, TCR sequence, and cell surface markers. Our analysis identified phenotypically and functionally distinguishable effector T cell types. We employed single-cell gene signatures from these T cell subsets to query the TCGA database to assess their prognostic significance. We found 2 distinct cytotoxic T cell types. GZMK+KLRG1+ cytotoxic T cells were enriched in CRC patients with good outcomes. GNLY+CD103+ cytotoxic T cells with a dysfunctional phenotype were not associated with good outcomes, despite coexpression of CD39 and CD103, markers that denote tumor reactivity. We found 2 distinct Treg subtypes associated with opposite outcomes. While total Tregs were associated with good outcomes, CD38+ Tregs were associated with bad outcomes independently of stage and possessed a highly suppressive phenotype, suggesting that they inhibit antitumor immunity in CRC. These findings highlight the potential utility of these subpopulations in predicting outcomes and support the potential for novel therapies directed at CD38+ Tregs or CD8+CD103+ T cells.

Clonal lineage tracing reveals shared origin of conventional and plasmacytoid dendritic cells.

Developmental origins of dendritic cells (DCs) including conventional DCs (cDCs, comprising cDC1 and cDC2 subsets) and plasmacytoid DCs (pDCs) remain unclear. We studied DC development in unmanipulated adult mice using inducible lineage tracing combined with clonal DNA "barcoding" and single-cell transcriptome and phenotype analysis (CITE-seq). Inducible tracing of Cx3cr1+ hematopoietic progenitors in the bone marrow showed that they simultaneously produce all DC subsets including pDCs, cDC1s, and cDC2s. Clonal tracing of hematopoietic stem cells (HSCs) and of Cx3cr1+ progenitors revealed clone sharing between cDC1s and pDCs, but not between the two cDC subsets or between pDCs and B cells. Accordingly, CITE-seq analyses of differentiating HSCs and Cx3cr1+ progenitors identified progressive stages of pDC development including Cx3cr1+ Ly-6D+ pro-pDCs that were distinct from lymphoid progenitors. These results reveal the shared origin of pDCs and cDCs and suggest a revised scheme of DC development whereby pDCs share clonal relationship with cDC1s.

Integrated analysis of multimodal single-cell data.

The simultaneous measurement of multiple modalities represents an exciting frontier for single-cell genomics and necessitates computational methods that can define cellular states based on multimodal data. Here, we introduce "weighted-nearest neighbor" analysis, an unsupervised framework to learn the relative utility of each data type in each cell, enabling an integrative analysis of multiple modalities. We apply our procedure to a CITE-seq dataset of 211,000 human peripheral blood mononuclear cells (PBMCs) with panels extending to 228 antibodies to construct a multimodal reference atlas of the circulating immune system. Multimodal analysis substantially improves our ability to resolve cell states, allowing us to identify and validate previously unreported lymphoid subpopulations. Moreover, we demonstrate how to leverage this reference to rapidly map new datasets and to interpret immune responses to vaccination and coronavirus disease 2019 (COVID-19). Our approach represents a broadly applicable strategy to analyze single-cell multimodal datasets and to look beyond the transcriptome toward a unified and multimodal definition of cellular identity.

Single Cell Analysis of Blood Mononuclear Cells Stimulated Through Either LPS or Anti-CD3 and Anti-CD28.

Immune cell activation assays have been widely used for immune monitoring and for understanding disease mechanisms. However, these assays are typically limited in scope. A holistic study of circulating immune cell responses to different activators is lacking. Here we developed a cost-effective high-throughput multiplexed single-cell RNA-seq combined with epitope tagging (CITE-seq) to determine how classic activators of T cells (anti-CD3 coupled with anti-CD28) or monocytes (LPS) alter the cell composition and transcriptional profiles of peripheral blood mononuclear cells (PBMCs) from healthy human donors. Anti-CD3/CD28 treatment activated all classes of lymphocytes either directly (T cells) or indirectly (B and NK cells) but reduced monocyte numbers. Activated T and NK cells expressed senescence and effector molecules, whereas activated B cells transcriptionally resembled autoimmune disease- or age-associated B cells (e.g., CD11c, T-bet). In contrast, LPS specifically targeted monocytes and induced two main states: early activation characterized by the expression of chemoattractants and a later pro-inflammatory state characterized by expression of effector molecules. These data provide a foundation for future immune activation studies with single cell technologies (https://czi-pbmc-cite-seq.jax.org/).

Tracing tumorigenesis in a solid tumor model at single-cell resolution.

Characterizing the complex composition of solid tumors is fundamental for understanding tumor initiation, progression and metastasis. While patient-derived samples provide valuable insight, they are heterogeneous on multiple molecular levels, and often originate from advanced tumor stages. Here, we use single-cell transcriptome and epitope profiling together with pathway and lineage analyses to study tumorigenesis from a developmental perspective in a mouse model of salivary gland squamous cell carcinoma. We provide a comprehensive cell atlas and characterize tumor-specific cells. We find that these cells are connected along a reproducible developmental trajectory: initiated in basal cells exhibiting an epithelial-to-mesenchymal transition signature, tumorigenesis proceeds through Wnt-differential cancer stem cell-like subpopulations before differentiating into luminal-like cells. Our work provides unbiased insights into tumor-specific cellular identities in a whole tissue environment, and emphasizes the power of using defined genetic model systems.

Genome wide analysis of 3' UTR sequence elements and proteins regulating mRNA stability during maternal-to-zygotic transition in zebrafish.

Posttranscriptional regulation plays a crucial role in shaping gene expression. During the maternal-to-zygotic transition (MZT), thousands of maternal transcripts are regulated. However, how different cis-elements and trans-factors are integrated to determine mRNA stability remains poorly understood. Here, we show that most transcripts are under combinatorial regulation by multiple decay pathways during zebrafish MZT. By using a massively parallel reporter assay, we identified cis-regulatory sequences in the 3' UTR, including U-rich motifs that are associated with increased mRNA stability. In contrast, miR-430 target sequences, UAUUUAUU AU-rich elements (ARE), CCUC, and CUGC elements emerged as destabilizing motifs, with miR-430 and AREs causing mRNA deadenylation upon genome activation. We identified trans-factors by profiling RNA-protein interactions and found that poly(U)-binding proteins are preferentially associated with 3' UTR sequences and stabilizing motifs. We show that this activity is antagonized by C-rich motifs and correlated with protein binding. Finally, we integrated these regulatory motifs into a machine learning model that predicts reporter mRNA stability in vivo.

Comprehensive Integration of Single-Cell Data.

Single-cell transcriptomics has transformed our ability to characterize cell states, but deep biological understanding requires more than a taxonomic listing of clusters. As new methods arise to measure distinct cellular modalities, a key analytical challenge is to integrate these datasets to better understand cellular identity and function. Here, we develop a strategy to "anchor" diverse datasets together, enabling us to integrate single-cell measurements not only across scRNA-seq technologies, but also across different modalities. After demonstrating improvement over existing methods for integrating scRNA-seq data, we anchor scRNA-seq experiments with scATAC-seq to explore chromatin differences in closely related interneuron subsets and project protein expression measurements onto a bone marrow atlas to characterize lymphocyte populations. Lastly, we harmonize in situ gene expression and scRNA-seq datasets, allowing transcriptome-wide imputation of spatial gene expression patterns. Our work presents a strategy for the assembly of harmonized references and transfer of information across datasets.

Multiplexed detection of proteins, transcriptomes, clonotypes and CRISPR perturbations in single cells.

Multimodal single-cell assays provide high-resolution snapshots of complex cell populations, but are mostly limited to transcriptome plus an additional modality. Here, we describe expanded CRISPR-compatible cellular indexing of transcriptomes and epitopes by sequencing (ECCITE-seq) for the high-throughput characterization of at least five modalities of information from each single cell. We demonstrate application of ECCITE-seq to multimodal CRISPR screens with robust direct single-guide RNA capture and to clonotype-aware multimodal phenotyping of cancer samples.

Cell Hashing with barcoded antibodies enables multiplexing and doublet detection for single cell genomics.

Despite rapid developments in single cell sequencing, sample-specific batch effects, detection of cell multiplets, and experimental costs remain outstanding challenges. Here, we introduce Cell Hashing, where oligo-tagged antibodies against ubiquitously expressed surface proteins uniquely label cells from distinct samples, which can be subsequently pooled. By sequencing these tags alongside the cellular transcriptome, we can assign each cell to its original sample, robustly identify cross-sample multiplets, and "super-load" commercial droplet-based systems for significant cost reduction. We validate our approach using a complementary genetic approach and demonstrate how hashing can generalize the benefits of single cell multiplexing to diverse samples and experimental designs.

Single-cell stabilization method identifies gonadotrope transcriptional dynamics and pituitary cell type heterogeneity.

Immediate-early response genes (IEGs) are rapidly and transiently induced following an extracellular signal. Elucidating the IEG response patterns in single cells (SCs) requires assaying large numbers of timed samples at high accuracy while minimizing handling effects. To achieve this, we developed and validated RNA stabilization Buffer for Examination of Single-cell Transcriptomes (RNA-Best), a versatile single-step cell and tissue preservation protocol that stabilizes RNA in intact SCs without perturbing transcription patterns. We characterize for the first time SC heterogeneity in IEG responses to pulsatile gonadotropin-releasing hormone (GnRH) stimuli in pituitary gonadotrope cells. Our study identifies a gene-specific hierarchical pattern of all-or-none transcript induction elicited by increasing concentrations of GnRH. This quantal pattern of gene activation raises the possibility that IEG activation, when accurately resolved at the SC level, may be mediated by gene bits that behave as pure binary switches.

Simultaneous epitope and transcriptome measurement in single cells.

High-throughput single-cell RNA sequencing has transformed our understanding of complex cell populations, but it does not provide phenotypic information such as cell-surface protein levels. Here, we describe cellular indexing of transcriptomes and epitopes by sequencing (CITE-seq), a method in which oligonucleotide-labeled antibodies are used to integrate cellular protein and transcriptome measurements into an efficient, single-cell readout. CITE-seq is compatible with existing single-cell sequencing approaches and scales readily with throughput increases.

Paternal diet defines offspring chromatin state and intergenerational obesity.

The global rise in obesity has revitalized a search for genetic and epigenetic factors underlying the disease. We present a Drosophila model of paternal-diet-induced intergenerational metabolic reprogramming (IGMR) and identify genes required for its encoding in offspring. Intriguingly, we find that as little as 2 days of dietary intervention in fathers elicits obesity in offspring. Paternal sugar acts as a physiological suppressor of variegation, desilencing chromatin-state-defined domains in both mature sperm and in offspring embryos. We identify requirements for H3K9/K27me3-dependent reprogramming of metabolic genes in two distinct germline and zygotic windows. Critically, we find evidence that a similar system may regulate obesity susceptibility and phenotype variation in mice and humans. The findings provide insight into the mechanisms underlying intergenerational metabolic reprogramming and carry profound implications for our understanding of phenotypic variation and evolution.

Paternal RNA contributions in the Caenorhabditis elegans zygote.

Development of the early embryo is thought to be mainly driven by maternal gene products and post-transcriptional gene regulation. Here, we used metabolic labeling to show that RNA can be transferred by sperm into the oocyte upon fertilization. To identify genes with paternal expression in the embryo, we performed crosses of males and females from divergent Caenorhabditis elegans strains. RNA sequencing of mRNAs and small RNAs in the 1-cell hybrid embryo revealed that about one hundred sixty paternal mRNAs are reproducibly expressed in the embryo and that about half of all assayed endogenous siRNAs and piRNAs are also of paternal origin. Together, our results suggest an unexplored paternal contribution to early development.

Global characterization of the oocyte-to-embryo transition in Caenorhabditis elegans uncovers a novel mRNA clearance mechanism.

The oocyte-to-embryo transition (OET) is thought to be mainly driven by post-transcriptional gene regulation. However, expression of both RNAs and proteins during the OET has not been comprehensively assayed. Furthermore, specific molecular mechanisms that regulate gene expression during OET are largely unknown. Here, we quantify and analyze transcriptome-wide, expression of mRNAs and thousands of proteins in Caenorhabditis elegans oocytes, 1-cell, and 2-cell embryos. This represents a first comprehensive gene expression atlas during the OET in animals. We discovered a first wave of degradation in which thousands of mRNAs are cleared shortly after fertilization. Sequence analysis revealed a statistically highly significant presence of a polyC motif in the 3' untranslated regions of most of these degraded mRNAs. Transgenic reporter assays demonstrated that this polyC motif is required and sufficient for mRNA degradation after fertilization. We show that orthologs of human polyC-binding protein specifically bind this motif. Our data suggest a mechanism in which the polyC motif and binding partners direct degradation of maternal mRNAs. Our data also indicate that endogenous siRNAs but not miRNAs promote mRNA clearance during the OET.

Conservation of mRNA and protein expression during development of C. elegans.

Spatiotemporal control of gene expression is crucial for development and subject to evolutionary changes. Although proteins are the final product of most genes, the developmental proteome of an animal has not yet been comprehensively defined, and the correlation between mRNA and protein abundance during development is largely unknown. Here, we globally measured and compared protein and mRNA expression changes during the life cycle of the nematodes C. elegans and C. briggsae, separated by ~30 million years of evolution. We observed that developmental mRNA and protein changes were highly conserved to a surprisingly similar degree but were poorly correlated within a species, suggesting important and widespread posttranscriptional regulation. Posttranscriptional control was particularly well conserved if mRNA fold changes were buffered on the protein level, indicating a predominant repressive function. Finally, among divergently expressed genes, we identified insulin signaling, a pathway involved in lifespan determination, as a putative target of adaptive evolution.

Essential roles of Raf/extracellular signal-regulated kinase/mitogen-activated protein kinase pathway, YY1, and Ca2+ influx in growth arrest of human vascular smooth muscle cells by bilirubin.

The biological effects of bilirubin, still poorly understood, are concentration-dependent ranging from cell protection to toxicity. Here we present data that at high nontoxic physiological concentrations, bilirubin inhibits growth of proliferating human coronary artery smooth muscle cells by three events. It impairs the activation of Raf/ERK/MAPK pathway and the cellular Raf and cyclin D1 content that results in retinoblastoma protein hypophosphorylation on amino acids S608 and S780. These events impede the release of YY1 to the nuclei and its availability to regulate the expression of genes and to support cellular proliferation. Moreover, altered calcium influx and calpain II protease activation leads to proteolytical degradation of transcription factor YY1. We conclude that in the serum-stimulated human vascular smooth muscle primary cell cultures, bilirubin favors growth arrest, and we propose that this activity is regulated by its interaction with the Raf/ERK/MAPK pathway, effect on cyclin D1 and Raf content, altered retinoblastoma protein profile of hypophosphorylation, calcium influx, and YY1 proteolysis. We propose that these activities together culminate in diminished 5 S and 45 S ribosomal RNA synthesis and cell growth arrest. The observations provide important mechanistic insight into the molecular mechanisms underlying the transition of human vascular smooth muscle cells from proliferative to contractile phenotype and the role of bilirubin in this transition.