Droplet-based Single Cell Research Articles

ScCDC: a computational method for gene-specific contamination detection and correction in single-cell and single-nucleus RNA-seq data

In droplet-based single-cell and single-nucleus RNA-seq assays, systematic contamination of ambient RNA molecules biases the quantification of gene expression levels. Existing methods correct the contamination for all genes globally. However, there lacks specific evaluation of correction efficacy for varying contamination levels. Here, we show that DecontX and CellBender under-correct highly contaminating genes, while SoupX and scAR over-correct lowly/non-contaminating genes. Here, we develop scCDC as the first method to detect the contamination-causing genes and only correct expression levels of these genes, some of which are cell-type markers. Compared with existing decontamination methods, scCDC excels in decontaminating highly contaminating genes while avoiding over-correction of other genes.

Heavy Metal-Laden Particulate Dust Alters Transcriptional Regulation in Human Colonoids

Chronic heavy metals exposure in the southwestern United States co-occurs with greater incidences of metabolic and digestive diseases, particularly in the Indigenous and Hispanic populations. There is a need to understand how particulate heavy metals drive this dysbiotic state and propose a molecular explanation as a result of these exposures. Previously, our group demonstrated human colonoids to be a relevant model for investigating the physiological impact of environmental toxicants on the intestinal tract. The objective of this study is to elucidate the mechanism behind the transcriptional and cellular changes present in the intestinal epithelia upon acute exposure to non fissile uranium particulate dust. We hypothesize that non-fissile uranium exposure biases the differentiation of progenitor cells in the crypt to secretory roles through miRNA regulation. Colonoids were exposed (18 hours) to non-fissile uranium dust obtained from the Jackpile uranium mine, one of the largest open pit uranium mines, located on the Laguna Pueblo in New Mexico. Control and dust-exposed colonoids (n=3 unique donors) were digested into single cells and processed for droplet-based single cell sequencing (scRNAseq). Upon exposure, enteroendocrine cells (EEC) expanded >4 fold, along with increases in serotonin and PYY, as well as goblet cells (>3 fold) which indicates changes to the secretory lineage. Downstream pathway analysis found microRNAs miR-625-3p, miR-320a, miR-29b-3p to be differentially expressed. These results suggest that acute uranium dust exposure induces changes in differentiation pathways which are modulated by regulatory miRNAs. We would like to expand these findings by performing miRNA sequencing and comparing miRNA expression profiles between UBD exposed and control samples. Our results also provide an improved understanding of uranium dust’s impact on the gastrointestinal system, which may inform other physiological studies on the health of individuals exposed to heavy metals. This study was funded by K01DK106323, R56ES034400, P42ES025589, P20GM121176, P20GM130422, and AGA SURF. This is the full abstract presented at the American Physiology Summit 2024 meeting and is only available in HTML format. There are no additional versions or additional content available for this abstract. Physiology was not involved in the peer review process.

Proteomic and Transcriptomic Analysis of Human Colonoids Exposed to Bacterial Serine Protease, EspP

Gut regeneration mechanisms remain an important, yet elusive, facet of intestinal injury research. The intestinal epithelium must be intact for critical gut functions to remain in place, yet injury via microbe interactions or environmental toxicants is common. EspP is a potent serine protease that functions as a cytotoxin and is secreted by enterohemorrhagic Escherichia coli. This bacterial toxin has been recently shown to cause significant colonic epithelial damage in human colonoids. Previous proteomics and single cell RNA-seq analysis of human colonoids exposed to EspP found that there is a marked expansion of enteroendocrine cells (EECs) at acute exposures. There is also an increase in vascular endothelial growth factor (VEGF)A and B, but the reasons for this remains unknown. Therefore, our goals are to understand the effects of altered secretory lineage differentiation upon EspP exposure during EHEC infection and characterize angiogenesis as a key factor in disease progression. We hypothesize that EspP induced EEC differentiation leads to increased enterohormone section, such as 5-HT, which ultimately influences the mucosal immune response and indirectly leads to increased VEGFA and VEGFB expression. Together, these factors promote systemic disease progression through epithelial-endothelial interactions. Human colonoids derived from healthy adult colonic biopsies (UNM IRB approved study 18-626 and 18-171) were established and shown to physiologically model the colonic epithelia. Colonoids were acutely exposed to EspP. Control and EspP-exposed colonoids (n=3 unique donors) were dissociated into single cells and processed for droplet-based single cell sequencing (scRNA-seq) or tandem mass spectrometry. The scRNA-seq data was analyzed using the Seurat pipeline and integrated with the proteomics dataset. scRNA-seq results identified a 4-fold expansion of EECs, with increases in EEC hormones 5-HT and PYY as well as a 2-fold expansion of VEGF expression. These transcriptomic changes seen were validated in colonoids (>5 biologically unique human donors) via RNA FISH and immunofluorescence. Our results demonstrate that acute EspP exposure directly induces transcriptomic and cellular changes in intestinal epithelia independent of microbiota, stroma, and immune cells. As EEC expansion is seen broadly in disease states from colorectal cancer to celiac disease, determining the role of enterohormones upon these changes, as well as the function of EECs during acute injury, will fill a gap in knowledge relevant to a wider problem of intestinal dysfunction. This work was supported by grants from the National Institutes of Health: K01DK106323, R56ES034400, P42ES025589; and AGA SURF. This is the full abstract presented at the American Physiology Summit 2024 meeting and is only available in HTML format. There are no additional versions or additional content available for this abstract. Physiology was not involved in the peer review process.

Pi-seq—A customizable multichannel syringe pump for microfluidics

The advent of single cell technologies resulted in growing demand for microfluidics in the biological sciences. Commercial platforms have remained expensive, inflexible, and non-customizable black boxes. We developed an open source, multichannel, zero-backflow microfluidics device based on syringe pumps controlled by a Raspberry Pi computer. It uses both readily available and 3D-printed parts as well as a custom PCB and is easily serviceable. Moreover, it is fully customizable for various applications. Total cost is under €600. We equipped one channel with a custom Peltier-based temperature controller for precise heating or cooling and a mixer mechanism to prevent sedimentation of the cells within the syringe. Depending on the cells in the sample, heating and cooling can be useful to maintain a beneficial environment or to slow down cellular processes and cell death, respectively. Combined with microfluidics consumables and a microscope, the device is capable of integration into a high quality droplet-based single cell RNA sequencing workflow as shown here. Analysis of a mixture of human and insect cells resulted in a dataset of 17,769 single cells and demonstrates reliable operation and separation.

Unraveling the timeline of gene expression: A pseudotemporal trajectory analysis of single-cell RNA sequencing data.

Single-cell RNA sequencing (scRNA-seq) technologies have rapidly developed in recent years. The droplet-based single cell platforms enable the profiling of gene expression in tens of thousands of cells per sample. The goal of a typical scRNA-seq analysis is to identify different cell subpopulations and their respective marker genes. Additionally, trajectory analysis can be used to infer the developmental or differentiation trajectories of cells. This article demonstrates a comprehensive workflow for performing trajectory inference and time course analysis on a multi-sample single-cell RNA-seq experiment of the mouse mammary gland. The workflow uses open-source R software packages and covers all steps of the analysis pipeline, including quality control, doublet prediction, normalization, integration, dimension reduction, cell clustering, trajectory inference, and pseudo-bulk time course analysis. Sample integration and cell clustering follows the Seurat pipeline while the trajectory inference is conducted using the monocle3 package. The pseudo-bulk time course analysis uses the quasi-likelihood framework of edgeR. Cells are ordered and positioned along a pseudotime trajectory that represented a biological process of cell differentiation and development. The study successfully identified genes that were significantly associated with pseudotime in the mouse mammary gland. The demonstrated workflow provides a valuable resource for researchers conducting scRNA-seq analysis using open-source software packages. The study successfully demonstrated the usefulness of trajectory analysis for understanding the developmental or differentiation trajectories of cells. This analysis can be applied to various biological processes such as cell development or disease progression, and can help identify potential biomarkers or therapeutic targets.

NLGN4X TCR transgenic T cells to treat gliomas.

Neuroligin 4 X-linked (NLGN4X) harbors a human leukocyte antigen (HLA)-A*02-restricted tumor-associated antigen, overexpressed in human gliomas, that was found to induce specific cytotoxic T cell responses following multi-peptide vaccination in patients with newly diagnosed glioblastoma. T cell receptor (TCR) discovery was performed using droplet-based single-cell TCR sequencing of NLGN4X-tetramer-sorted T cells postvaccination. The identified TCR was delivered to Jurkat T cells and primary human T cells (NLGN4X-TCR-T). Functional profiling of NLGN4X-TCR-T was performed by flow cytometry and cytotoxicity assays. Therapeutic efficacy of intracerebroventricular NLGN4X-TCR-T was assessed in NOD scid gamma (NSG) major histocompatibility complex (MHC) I/II knockout (KO) (NSG MHC I/II KO) mice bearing NLGN4X-expressing experimental gliomas. An HLA-A*02-restricted vaccine-induced T cell receptor specifically binding NLGN4X131-139 was applied for preclinical therapeutic use. Reactivity, cytotoxicity, and polyfunctionality of this NLGN4X-specific TCR are demonstrated in various cellular models. Intracerebroventricular administration of NLGN4X-TCR-T prolongs survival and leads to an objective response rate of 44.4% in experimental glioma-bearing NSG MHC I/II KO mice compared to 0.0% in control groups. NLGN4X-TCR-T demonstrate efficacy in a preclinical glioblastoma model. On a global scale, we provide the first evidence for the therapeutic retrieval of vaccine-induced human TCRs for the off-the-shelf treatment of glioblastoma patients.Keywords cell therapy | glioblastoma | T cell receptor | tumor antigen.

Unsupervised removal of systematic background noise from droplet-based single-cell experiments using CellBender.

Droplet-based single-cell assays, including single-cell RNA sequencing (scRNA-seq), single-nucleus RNA sequencing (snRNA-seq) and cellular indexing of transcriptomes and epitopes by sequencing (CITE-seq), generate considerable background noise counts, the hallmark of which is nonzero counts in cell-free droplets and off-target gene expression in unexpected cell types. Such systematic background noise can lead to batch effects and spurious differential gene expression results. Here we develop a deep generative model based on the phenomenology of noise generation in droplet-based assays. The proposed model accurately distinguishes cell-containing droplets from cell-free droplets, learns the background noise profile and provides noise-free quantification in an end-to-end fashion. We implement this approach in the scalable and robust open-source software package CellBender. Analysis of simulated data demonstrates that CellBender operates near the theoretically optimal denoising limit. Extensive evaluations using real datasets and experimental benchmarks highlight enhanced concordance between droplet-based single-cell data and established gene expression patterns, while the learned background noise profile provides evidence of degraded or uncaptured cell types.

The effect of background noise and its removal on the analysis of single-cell expression data

BackgroundIn droplet-based single-cell and single-nucleus RNA-seq experiments, not all reads associated with one cell barcode originate from the encapsulated cell. Such background noise is attributed to spillage from cell-free ambient RNA or barcode swapping events.ResultsHere, we characterize this background noise exemplified by three scRNA-seq and two snRNA-seq replicates of mouse kidneys. For each experiment, cells from two mouse subspecies are pooled, allowing to identify cross-genotype contaminating molecules and thus profile background noise. Background noise is highly variable across replicates and cells, making up on average 3–35% of the total counts (UMIs) per cell and we find that noise levels are directly proportional to the specificity and detectability of marker genes. In search of the source of background noise, we find multiple lines of evidence that the majority of background molecules originates from ambient RNA. Finally, we use our genotype-based estimates to evaluate the performance of three methods (CellBender, DecontX, SoupX) that are designed to quantify and remove background noise. We find that CellBender provides the most precise estimates of background noise levels and also yields the highest improvement for marker gene detection. By contrast, clustering and classification of cells are fairly robust towards background noise and only small improvements can be achieved by background removal that may come at the cost of distortions in fine structure.ConclusionsOur findings help to better understand the extent, sources and impact of background noise in single-cell experiments and provide guidance on how to deal with it.

Unraveling the timeline of gene expression: A pseudotemporal trajectory analysis of single-cell RNA sequencing data

Background: Single-cell RNA sequencing (scRNA-seq) technologies have rapidly developed in recent years. The droplet-based single cell platforms enable the profiling of gene expression in tens of thousands of cells per sample. The goal of a typical scRNA-seq analysis is to identify different cell subpopulations and their respective marker genes. Additionally, trajectory analysis can be used to infer the developmental or differentiation trajectories of cells. Methods: This article demonstrates a comprehensive workflow for performing trajectory inference and time course analysis on a multi-sample single-cell RNA-seq experiment of the mouse mammary gland. The workflow uses open-source R software packages and covers all steps of the analysis pipeline, including quality control, doublet prediction, normalization, integration, dimension reduction, cell clustering, trajectory inference, and pseudo-bulk time course analysis. Sample integration and cell clustering follows the Seurat pipeline while the trajectory inference is conducted using the monocle3 package. The pseudo-bulk time course analysis uses the quasi-likelihood framework of edgeR. Results: Cells are ordered and positioned along a pseudotime trajectory that represented a biological process of cell differentiation and development. The study successfully identified genes that were significantly associated with pseudotime in the mouse mammary gland. Conclusions: The demonstrated workflow provides a valuable resource for researchers conducting scRNA-seq analysis using open-source software packages. The study successfully demonstrated the usefulness of trajectory analysis for understanding the developmental or differentiation trajectories of cells. This analysis can be applied to various biological processes such as cell development or disease progression, and can help identify potential biomarkers or therapeutic targets.

LACK OF SMARCB1 EXPRESSION CHARACTERIZES A SUBSET OF PERIPHERAL T‐CELL LYMPHOMAS ENRICHED IN CHILDREN AND YOUNG ADULTS

Introduction: Peripheral T-cell lymphoma, not otherwise specified (PTCL-NOS) is a heterogeneous group of malignancies with poor outcome. Because patients respond poorly to current treatment regimens, identification of new therapeutic strategies is required. In a mouse tumor model, conditional deletion of Smarcb1 encoding a member of the SWI/SNF chromatin remodeling complex causes the majority of mice to develop mature T-cell lymphomas. The human counterpart, SMARCB1, is a bona fide tumor suppressor gene associated with the development of for example, rhabdoid tumors and schwannomas, but has also been shown to be involved in lymphocyte development. Methods: SMARCB1 (INI1) gene and protein expression was assessed in 315 patients with diverse mature T cell lymphomas by array-based mRNA profiling, immunohistochemistry and/or Western Blot. The DNA methylome was analyzed in SMARCB1-negative pediatric PTCL-NOS patients (n = 5) and murine T cell lymphomas of the Cd4-cre::Smarcb1fl/fl model (n = 5) using the Infinium MethylationEPIC and Mouse Methylation BeadChip, respectively. Murine Smarcb1-deficient T-cell lymphomas were further studied using droplet-based single cell RNA sequencing (Chromium, 10X Genomics). Results: SMARCB1 expression was heterogeneous between and within the 315 different human mature T-cell lymphoma entities. Loss of SMARCB1 expression in PTCL-NOS patients correlated with young age (Wald test, p value = 0.011). Molecular characterization and DNA methylation analysis revealed that loss of SMARCB1 expression in human PTCL largely occurs via somatic mutation and/or epigenetic silencing, whereas in contrast to rhabdoid tumors, germline SMARCB1 mutations were not observed. Comparison of the DNA methylome of human and murine PTCL-NOSSmarcb1- showed similar DNA methylation profiles, with hypermethylation of T-cell-related genes and hypomethylation of genes involved in myeloid development. Increase of myeloid cell populations was confirmed in murine tumors by scRNA-seq analyses, which further revealed an immunosuppressive and pro-inflammatory tumor microenvironment (TME). Treatment of tumor-bearing mice with SAHA, a pan-HDACi, triggered remodeling of the TME, promoting replenishment of lymphoid compartments and reversion of the exhaustion phenotype. Conclusions: Here we describe SMARCB1-negative PTCL-NOS as a potential new molecular subtype of PTCL-NOS significantly enriched in young patients. A strong concordance between naturally occurring SMARCB1-deficient PTCL in humans and in the targeted mouse model were found regarding epigenetic features. Our results provide a rationale for further investigation of potential HDACi combination therapies in SMARCB1-negative PTCL-NOS. Keywords: aggressive T-cell non-Hodgkin lymphoma, genomics, epigenomics, and other-omics No conflicts of interests pertinent to the abstract.

Abstract 503: Single Cell Transcriptomics Uncovers The Functional Complexity Of Peripheral Veins And Arteries

Methods: Twenty-six hundred cells from 4 human peripheral veins and 2 arteries were droplet-based single cell sequenced using the 10X Chromium protocol . Paired bulk RNA-seq from seven veins and arteries obtained from the same patient and immunofluorescence validated findings. Results: Arteries were richer in smooth muscle cell (39.1 vs. 13.8%) while vein contained abundant immune cells (14.5 vs. 39.8%). Both vessels had abundant fibroblasts, (28.1 vs. 34.5%), and endothelial Cells (16.5 vs. 11.1 %). Concordantly, contractility and ECM-related pathways were significantly highlighted in arteries while veins were enrich ed in leukocyte migration, antigen presentation, neutrophil activation, and other immune related genes . Quantitate immunofluorescence further confirmed SMC abundance in the arterial wall ( 56% vs. 18% n=11 pairs, p <0.001). There were two main fibroblast clusters equally abundant, the synthetic fibroblasts with high expression of ECM related genes (COL1A1, COL3A1), while the other cluster was defined by the immunomodulatory mediators (CXCL14, CFD). Vein were enriched for Mhem-like (CD163, HMOX1) macrophages important for detoxification and hemoglobin recycling and inflammatory macrophages (IL1B, CXCL8) were similar similarly distributed in both groups . We found a significant number of vasa vasorum (CD34, ICAM2) and luminal ECs(PECAM1,VWF) present in both groups. Furthermore, Intelectin-1 (ITLN1) was elucidated as a specific arterial endothelial marker, both at the single cell and bulk transcriptomic levels. There was also a minor lymphatic endothelial cell subcluster (PROX1 + ) detected in both veins and arteries. Finally, CellCall analysis identified 46 overrepresented ligand-receptor communication pathways in all clusters, including CXCL, FGF, IL-6, and complement signaling. Conclusions: We present a comparative single-cell atlas of peripheral human vein and arteries highlighting important vein enriched functions such as detoxification and hemoglobin recycling. We are now better able to identify cell subpopulations relevant for venous pathologies, without relying on extrapolations from arterial biology of distant models and focusing instead on the uniqueness of vein tissues.

Heavy metal-laden particulate dust disrupts intestinal epithelial stem cells and lineage differentiation

Chronic heavy metals exposure has been associated with intestinal inflammation and higher incidences of colorectal cancer, however there is no molecular evidence that metal laden-particulates can cause injury to the gut epithelia. Communities that live adjacent to abandoned uranium mines have higher incidence of metabolic and digestive diseases; however, the cause is unknown. The goal of this study is to characterize particulate dust containing non-fissile uranium as an environmental toxicant that damages intestinal epithelia and characterize the subsequent transcriptomic changes. We hypothesized that non-fissile uranium will alter the differentiation pattern of progenitor cells in the crypt biasing them towards the secretory lineage. Human colonoids derived from healthy adult colonic biopsies (UNM IRB approved study 18-626 and 18-171) were established and shown to physiologically model the intestinal epithelia. Colonoids were acutely exposed (24h) to non-fissile uranium dust obtained near the Jackpile uranium mine in New Mexico, one of the largest open pit uranium mines in the US, located on the Laguna Pueblo. Control and dust-exposed colonoids (n=3 unique donors) were dissociated into single cells and processed for droplet-based single cell sequencing (scRNAseq). scRNAseq identified significant changes in the secretory lineage in uranium dust-exposed colonoids. Specifically, there was a four-fold expansion of enteroendocrine cells (EEC) with increases in EEC hormones serotonin and PYY in all colonoid lines. Proliferative pathways, such as Wnt signaling and negative regulation of apoptosis were upregulated in these EECs. These transcriptomic changes in EECs and proliferative cells and increased basolateral secretion of secretory granules and serotonin was validated in colonoids (˃5 biologically unique human donors) via RNA FISH, immunofluorescence and ELISAs. Our results demonstrate that acute uranium dust exposure directly induces transcriptomic and cellular changes in intestinal epithelia independently of microbiota, stroma, and immune cells. These results indicate that adult human colonoids are a relevant model for investigating environmental toxicants on intestinal epithelia and provide an improved understanding of uranium dust as a model of intestinal injury. This study was funded by NIDDK (K01DK106323), NIEHS (R56ES034400, P42ES025589), and NIGMS (P20GM121176, P20GM130422). This is the full abstract presented at the American Physiology Summit 2023 meeting and is only available in HTML format. There are no additional versions or additional content available for this abstract. Physiology was not involved in the peer review process.

Droplet-based transcriptome profiling of individual synapses.

Synapses are crucial structures that mediate signal transmission between neurons in complex neural circuits and display considerable morphological and electrophysiological heterogeneity. So far we still lack a high-throughput method to profile the molecular heterogeneity among individual synapses. In the present study, we develop a droplet-based single-cell (sc) total-RNA-sequencing platform, called Multiple-Annealing-and-Tailing-based Quantitative scRNA-seq in Droplets, for transcriptome profiling of individual neurites, primarily composed of synaptosomes. In the synaptosome transcriptome, or 'synaptome', profiling of both mouse and human brain samples, we detect subclusters among synaptosomes that are associated with neuronal subtypes and characterize the landscape of transcript splicing that occurs within synapses. We extend synaptome profiling to synaptopathy in an Alzheimer's disease (AD) mouse model and discover AD-associated synaptic gene expression changes that cannot be detected by single-nucleus transcriptome profiling. Overall, our results show that this platform provides a high-throughput, single-synaptosome transcriptome profiling tool that will facilitate future discoveries in neuroscience.

Normalizing and denoising protein expression data from droplet-based single cell profiling

Multimodal single-cell profiling methods that measure protein expression with oligo-conjugated antibodies hold promise for comprehensive dissection of cellular heterogeneity, yet the resulting protein counts have substantial technical noise that can mask biological variations. Here we integrate experiments and computational analyses to reveal two major noise sources and develop a method called “dsb” (denoised and scaled by background) to normalize and denoise droplet-based protein expression data. We discover that protein-specific noise originates from unbound antibodies encapsulated during droplet generation; this noise can thus be accurately estimated and corrected by utilizing protein levels in empty droplets. We also find that isotype control antibodies and the background protein population average in each cell exhibit significant correlations across single cells, we thus use their shared variance to correct for cell-to-cell technical noise in each cell. We validate these findings by analyzing the performance of dsb in eight independent datasets spanning multiple technologies, including CITE-seq, ASAP-seq, and TEA-seq. Compared to existing normalization methods, our approach improves downstream analyses by better unmasking biologically meaningful cell populations. Our method is available as an open-source R package that interfaces easily with existing single cell software platforms such as Seurat, Bioconductor, and Scanpy and can be accessed at “dsb [https://cran.r-project.org/package=dsb]”.

Inactivation of SARS-CoV-2 and COVID-19 Patient Samples for Contemporary Immunology and Metabolomics Studies.

Due to the severity of COVID-19 disease, the U.S. Centers for Disease Control and Prevention and World Health Organization recommend that manipulation of active viral cultures of SARS-CoV-2 and respiratory secretions from COVID-19 patients be performed in biosafety level (BSL)3 laboratories. Therefore, it is imperative to develop viral inactivation procedures that permit samples to be transferred to lower containment levels (BSL2), while maintaining the fidelity of complex downstream assays to expedite the development of medical countermeasures. In this study, we demonstrate optimal conditions for complete viral inactivation following fixation of infected cells with commonly used reagents for flow cytometry, UVC inactivation in sera and respiratory secretions for protein and Ab detection, heat inactivation following cDNA amplification for droplet-based single-cell mRNA sequencing, and extraction with an organic solvent for metabolomic studies. Thus, we provide a suite of viral inactivation protocols for downstream contemporary assays that facilitate sample transfer to BSL2, providing a conceptual framework for rapid initiation of high-fidelity research as the COVID-19 pandemic continues.

High precision, high throughput generation of droplets containing single cells.

The Poisson limit is a major problem for the isolation of single cells in different single-cell technologies and applications. In droplet-based single-cell assays, a scheme that is increasingly popular, the intrinsic randomness during single-cell encapsulation in droplets requires most of the created droplets to be empty, which has a profound impact on the efficiency and throughput of such techniques, and on the predictability of the combinatory droplet assays. Here we present a simple passive microfluidic system overcoming this limitation with unprecedented efficacy, allowing the generation of single-cell droplets for a wide range of operating conditions, with extremely high throughput (more than 22 000 single-cell loaded droplets per minute) and with an extremely low fault ratio (doublets or empty droplets), applicable to any cells and deformable particles. This versatile technique will shift the paradigm of single-cell encapsulation and will impact single-cell sequencing, rare cell isolation, multicellular/bead studies in immunology or cancer biology, etc.

Simultaneous Analysis of Single-Cell Transcriptomes and Cell Surface Protein Expression of Human Hematopoietic Stem Cells and Progenitors Using the 10x Genomics Platform.

The CITE-seq workflow combines conventional single-cell transcriptomic analysis with simultaneous analysis of cell surface protein expression using oligonucleotide-conjugated antibodies. This addition of immunophenotyping to mRNA data allows for a more detailed characterization of single-cell heterogeneity and can help to identify markers for the prospective isolation of transcriptionally defined novel cell subsets. Here, we describe the workflow for the preparation of human cord blood mononuclear cells and CD34+-enriched hematopoietic progenitors for the simultaneous characterization of protein and RNA using the commercially available TotalSeq™ antibodies from BioLegend and the droplet-based single-cell RNA-seq commercial platform from 10x Genomics.

OS12.4.A MHC class II-restricted transgenic T cell receptor therapy targeting mutant capicua transcriptional repressor in experimental gliomas

Abstract BACKGROUND Glioma subtypes are classified according to their characteristic mutations and show a high degree of resistance to standard therapeutic interventions such as radiotherapy and alkylating chemotherapy. Some of these characteristic mutations have shown to generate immunogenic neoepitopes that can be targeted with immunotherapy. 70% of oligodendrogliomas carry capicua transcriptional repressor (CIC) inactivating mutations. RESULTS In a screen for potential immunogenic glioma neoepitopes we identified recurrent CIC hotspot mutations at position 215 (CICR215W/Q) expressed in a subset of oligodendrogliomas as an immunogenic major histocompatibility complex (MHC) class II-restricted neoepitopes. Peptide-based vaccination of MHC-humanized mice resulted in the generation of robust mutation-specific T cell responses against CICR215W/Q, restricted to MHC class II. Droplet-based single cell T cell receptor (TCR) sequencing from CICR215W-specific T cell lines enabled retrieval of MHC class II-restricted CICR215W-reactive TCRs. By retroviral transduction of T cells, we established a flow cytometry-based testing platform of retrieved TCRs and were able to show the top reactive TCR against CICR215W to be shared between individual mice. Using a newly developed glioma model in MHC-humanized mice induced by CRISPR-based delivery of tumor suppressor targeting guide RNAs, we show that adoptive intraventricular transfer of CICR215W-specific TCR-transgenic T cells exert anti-tumor responses against CICR215W-expressing syngeneic gliomas. CONCLUSION The integration of immunocompetent MHC-humanized orthotopic glioma models in the discovery of shared immunogenic glioma neoepitopes facilitates the identification and preclinical testing of HLA-restricted neoepitope-specific TCRs for locoregional TCR-transgenic T cell adoptive therapy.

Single-cell CUT&Tag analysis of chromatin modifications in differentiation and tumor progression.

Methods for quantifying gene expression1 and chromatin accessibility2 in single cells are well established, but single-cell analysis of chromatin regions with specific histone modifications has been technically challenging. In this study, we adapted the CUT&Tag method3 to scalable nanowell and droplet-based single-cell platforms to profile chromatin landscapes in single cells (scCUT&Tag) from complex tissues and during the differentiation of human embryonic stem cells. We focused on profiling polycomb group (PcG) silenced regions marked by histone H3 Lys27 trimethylation (H3K27me3) in single cells as an orthogonal approach to chromatin accessibility for identifying cell states. We show that scCUT&Tag profiling of H3K27me3 distinguishes cell types in human blood and allows the generation of cell-type-specific PcG landscapes from heterogeneous tissues. Furthermore, we used scCUT&Tag to profile H3K27me3 in a patient with a brain tumor before and after treatment, identifying cell types in the tumor microenvironment and heterogeneity in PcG activity in the primary sample and after treatment.

Droplet-based mRNA sequencing of fixed and permeabilized cells by CLInt-seq allows for antigen-specific TCR cloning

T cell receptors (TCRs) are generated by somatic recombination of V/D/J segments to produce up to 1015 unique sequences. Highly sensitive and specific techniques are required to isolate and identify the rare TCR sequences that respond to antigens of interest. Here, we describe the use of mRNA sequencing via cross-linker regulated intracellular phenotype (CLInt-Seq) for efficient recovery of antigen-specific TCRs in cells stained for combinations of intracellular proteins such as cytokines or transcription factors. This method enables high-throughput identification and isolation of low-frequency TCRs specific for any antigen. As a proof of principle, intracellular staining for TNFα and IFNγ identified cytomegalovirus (CMV)- and Epstein-Barr virus (EBV)-reactive TCRs with efficiencies similar to state-of-the-art peptide-MHC multimer methodology. In a separate experiment, regulatory T cells were profiled based on intracellular FOXP3 staining, demonstrating the ability to examine phenotypes based on transcription factors. We further optimized the intracellular staining conditions to use a chemically cleavable primary amine cross-linker compatible with current single-cell sequencing technology. CLInt-Seq for TNFα and IFNγ performed similarly to isolation with multimer staining for EBV-reactive TCRs. We anticipate CLInt-Seq will enable droplet-based single-cell mRNA analysis from any tissue where minor populations need to be isolated by intracellular markers.