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.
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.
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.
Display omitted
•“Weighted nearest neighbor” analysis integrates multimodal single-cell data•A multimodal reference “atlas” of the circulating human immune system•Identification and validation of novel sources of lymphoid heterogeneity•“Reference-based” mapping of query datasets onto a multimodal atlas
A framework that allows for the integration of multiple data types using single cells is applied to understand distinct immune cell states, previously unidentified immune populations, and to interpret immune responses to vaccinations.
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.
Animal mRNAs are regulated by hundreds of RNA binding proteins (RBPs). The identification of RBP targets is crucial for understanding their function. A recent method, PAR-CLIP, uses photoreactive ...nucleosides to crosslink RBPs to target RNAs in cells prior to immunoprecipitation. Here, we establish iPAR-CLIP (in vivo PAR-CLIP) to determine, at nucleotide resolution, transcriptome-wide binding sites of GLD-1, a conserved, germline-specific translational repressor in
C. elegans. We identified 439 reproducible target mRNAs and demonstrate an excellent dynamic range of target detection by iPAR-CLIP. Upon GLD-1 knockdown, protein but not mRNA expression of the 439 targets was specifically upregulated, demonstrating functionality. Finally, we discovered strongly conserved GLD-1 binding sites near the start codon of target genes. These sites are functional in vitro and likely confer strong repression in vivo. We propose that GLD-1 interacts with the translation machinery near the start codon, a so-far-unknown mode of gene regulation in eukaryotes.
► iPAR-CLIP identifies binding sites of RNA binding proteins (RBPs) in
C. elegans ► iPAR-CLIP identified hundreds of direct targets of the germline-specific RBP GLD-1 ► Effects of GLD-1 knockdown on protein expression of targets confirm functionality ► Conserved 5′ UTR sites near start codons are bound by GLD-1 and functional in vitro
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/).
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.
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.
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.
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.
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.
Caenorhabditis elegans is one of the most prominent model systems for embryogenesis, but collecting many precisely staged embryos has been impractical. Thus, early C. elegans embryogenesis has not ...been amenable to most high-throughput genomics or biochemistry assays. To overcome this problem, we devised a method to collect staged C. elegans embryos by fluorescence-activated cell sorting (eFACS). In a proof-of-principle experiment, we found that a single eFACS run routinely yielded tens of thousands of almost perfectly staged 1-cell stage embryos. As the earliest embryonic events are driven by posttranscriptional regulation, we combined eFACS with second-generation sequencing to profile the embryonic expression of small, noncoding RNAs. We discovered complex and orchestrated changes in the expression between and within almost all classes of small RNAs, including microRNAs and 26G-RNAs, during embryogenesis.
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.
Display omitted
•Seurat v3 identifies correspondences between cells in different experiments•These “anchors” can be used to harmonize datasets into a single reference•Reference labels and data can be projected onto query datasets•Extends beyond RNA-seq to single-cell protein, chromatin, and spatial data
A computational approach to integrate diverse modalities associated with single-cell sequencing datasets can be used to better understand cellular identity and function.
PDF
