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Single Cell Transcriptomics
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Sorafenib, a multikinase inhibitor, is an FDA-approved first line drug for the treatment of patients with unresectable hepatocellular carcinoma (HCC). Unfortunately, these patients achieve minimal therapeutic benefit with an improvement in overall survival of only 3 months. After an initial response, the majority of HCC patients develop drug resistance and disease progression. Although multiple mechanisms such as crosstalk involving PI3K/Akt and MAPK/ERK pathways or activation of EMT have been reported, the major drivers of sorafenib resistance remain obscure. Recently, rapidly evolving single-cell transcriptome analysis techniques have been used to comprehensively assess the genetics of the tumour microenvironment and the mechanisms for intra-tumoral heterogeneity which can impact anti-cancer treatment responses. This technology has the potential for higher transcriptomic resolution and sensitivity than bulk sequencing techniques. Single-cell analysis also enables a deep interrogation of hundreds of cancer drivers and identifies individual cells or genes with specific genetic modifications or expression profiles which could contribute to the development of therapeutic resistance. Here, we conducted a single cell RNA seq analysis in sorafenib resistant HCC cells to systematically investigate drug-resistance signatures to uncover the mechanisms of sorafenib resistance.
During adaptive immunity, B cells differentiate either into memory B cells or plasma cells and produce antibodies against foreign antigens to fight infection. Additionally, they behave as antigen-presenting cells and participate in T cell activation during cellular immune responses. However, their functional dysregulation can result in various autoimmune diseases and cancers. With significant breakthroughs in single cell technologies, assessing individual B cell genomics, transcriptomics, and proteomics can give deeper insights into mammalian B cell development, differentiation, antibody repertoire, and responses under conditions of homeostasis, infection, and aberrations during disease. In this review, we discuss the adoption of single cell approaches to identify different B cell gene signatures and biomarkers in normal and diseased tissues, and subsequent benefits for future therapeutic discoveries.
The coexistence of DNA replication and transcription during S-phase requires their tight coordination to prevent harmful conflicts. While extensive research revealed important mechanisms for minimizing these conflicts and their consequences, little is known regarding how the replication and transcription machinery are coordinated in real-time. Here, we developed a live-cell imaging approach for the real-time monitoring of replisome progression and transcription dynamics during a transcription-replication encounter. We found a wave of partial transcriptional repression ahead of the moving replication fork, which may contribute to efficient fork progression through the transcribed gene. Real-time detection of conflicts revealed their negative impact on both processes, leading to fork stalling or slowdown as well as lower transcription levels during gene replication, with different trade-offs observed in defined subpopulations of cells. Our real-time measurements of transcription-replication encounters demonstrate how these processes can proceed simultaneously while maintaining genomic stability, and how conflicts can arise when coordination is impaired.
The bacterial microbiota works as a community that consists of many individual organisms, i.e., cells. To fully understand the function of bacterial microbiota, individual cells must be identified; however, it is difficult with current techniques. Here, we develop a method, Barcoding Bacteria for Identification and Quantification (BarBIQ), which classifies single bacterial cells into taxa–named herein cell-based operational taxonomy units (cOTUs)–based on cellularly barcoded 16S rRNA sequences with single-base accuracy, and quantifies the cell number for each cOTU in the microbiota in a high-throughput manner. We apply BarBIQ to murine cecal microbiotas and quantify in total 3.4 × 105 bacterial cells containing 810 cOTUs. Interestingly, we find location-dependent global differences in the cecal microbiota depending on the dietary vitamin A deficiency, and more differentially abundant cOTUs at the proximal location than the distal location. Importantly, these location differences are not clearly shown by conventional 16S rRNA gene-amplicon sequencing methods, which quantify the 16S rRNA genes, not the cells. Thus, BarBIQ enables microbiota characterization with the identification and quantification of individual constituent bacteria, which is a cornerstone for microbiota studies.
Single-cell (sc)RNA-seq, together with RNA velocity and metabolic labeling, reveals cellular states and transitions at unprecedented resolution. Fully exploiting these data, however, requires kinetic models capable of unveiling governing regulatory functions. Here, we introduce an analytical framework dynamo (https://github.com/aristoteleo/dynamo-release), which infers absolute RNA velocity, reconstructs continuous vector fields that predict cell fates, employs differential geometry to extract underlying regulations, and ultimately predicts optimal reprogramming paths and perturbation outcomes. We highlight dynamo's power to overcome fundamental limitations of conventional splicing-based RNA velocity analyses to enable accurate velocity estimations on a metabolically labeled human hematopoiesis scRNA-seq dataset. Furthermore, differential geometry analyses reveal mechanisms driving early megakaryocyte appearance and elucidate asymmetrical regulation within the PU.1-GATA1 circuit. Leveraging the least-action-path method, dynamo accurately predicts drivers of numerous hematopoietic transitions. Finally, in silico perturbations predict cell-fate diversions induced by gene perturbations. Dynamo, thus, represents an important step in advancing quantitative and predictive theories of cell-state transitions.
Chronic lymphocytic leukemia (CLL) is characterized by a clonal expansion of mature CD19+CD5+ B cells, which are highly dependent on microenvironmental cues for their survival. This common adult leukemia is preceded by a precursor phase termed monoclonal B-cell lymphocytosis (MBL), which has been characterized as indistinguishable from CLL at the genetic, transcriptomic, and epigenomic level. However, how leukemia cells coevolve with immune cells in their circulating microenvironment during the onset of MBL and upon progression to CLL remains incompletely characterized.
Acute kidney injury (AKI) is a complex clinical disorder associated with poor outcomes. Targeted regulation of the degree of inflammation has been a potential strategy for AKI management. Macrophages are the main effector cells of kidney inflammation. However, macrophage heterogeneity in ischemia reperfusion injury induced AKI (IRI-AKI) remains unclear. Using single-cell RNA sequencing of the mononuclear phagocytic system in the murine IRI model, the authors demonstrate the complementary roles of kidney resident macrophages (KRMs) and monocyte-derived infiltrated macrophages (IMs) in modulating tissue inflammation and promoting tissue repair. A unique population of S100a9hiLy6chi IMs is identified as an early responder to AKI, mediating the initiation and amplification of kidney inflammation. Kidney infiltration of S100A8/A9+ macrophages and the relevance of renal S100A8/A9 to tissue injury is confirmed in human AKI. Targeting the S100a8/a9 signaling with small-molecule inhibitors exhibits renal protective effects represented by improved renal function and reduced mortality in bilateral IRI model, and decreased inflammatory response, ameliorated kidney injury, and improved long-term outcome with decreased renal fibrosis in the unilateral IRI model. The findings support S100A8/A9 blockade as a feasible and clinically relevant therapy potentially waiting for translation in human AKI.
N6-methyladenosine (m6A) is an abundant RNA modification that plays critical roles in RNA regulation and cellular function. Global m6A profiling has revealed important aspects of m6A distribution and function, but to date such studies have been restricted to large populations of cells. Here, we develop a method to identify m6A sites transcriptome-wide in single cells. We uncover surprising heterogeneity in the presence and abundance of m6A sites across individual cells and identify differentially methylated mRNAs across the cell cycle. Additionally, we show that cellular subpopulations can be distinguished based on their RNA methylation signatures, independent from gene expression. These studies reveal fundamental features of m6A that have been missed by m6A profiling of bulk cells and suggest the presence of cell-intrinsic mechanisms for m6A deposition.
von Willebrand factor (VWF) plays a key role in normal hemostasis, and deficiencies of VWF lead to clinically significant bleeding. We sought to identify novel modifiers of VWF levels in endothelial colony-forming cells (ECFCs) using single-cell RNA sequencing (scRNA-seq). ECFCs were isolated from patients with low VWF levels (plasma VWF antigen levels between 30 and 50 IU/dL) and from healthy controls. Human umbilical vein endothelial cells were used as an additional control cell line. Cells were characterized for their Weibel Palade body (WPB) content and VWF release. scRNA-seq of all cell lines was performed to evaluate for gene expression heterogeneity and for candidate modifiers of VWF regulation. Candidate modifiers identified by scRNA-seq were further characterized with small-interfering RNA (siRNA) experiments to evaluate for effects on VWF. We observed that ECFCs derived from patients with low VWF demonstrated alterations in baseline WPB metrics and exhibit impaired VWF release. scRNA-seq analyses of these endothelial cells revealed overall decreased VWF transcription, mosaicism of VWF expression, and genes that are differentially expressed in low VWF ECFCs and control endothelial cells (control ECs). An siRNA screen of potential VWF modifiers provided further evidence of regulatory candidates, and 1 such candidate, FLI1, alters the transcriptional activity of VWF. In conclusion, ECFCs from individuals with low VWF demonstrate alterations in their baseline VWF packaging and release compared with control ECs. scRNA-seq revealed alterations in VWF transcription, and siRNA screening identified multiple candidate regulators of VWF.
The liver is the largest solid organ in the body, yet it remains incompletely characterized. Here we present a spatial proteogenomic atlas of the healthy and obese human and murine liver combining single-cell CITE-seq, single-nuclei sequencing, spatial transcriptomics, and spatial proteomics. By integrating these multi-omic datasets, we provide validated strategies to reliably discriminate and localize all hepatic cells, including a population of lipid-associated macrophages (LAMs) at the bile ducts. We then align this atlas across seven species, revealing the conserved program of bona fide Kupffer cells and LAMs. We also uncover the respective spatially resolved cellular niches of these macrophages and the microenvironmental circuits driving their unique transcriptomic identities. We demonstrate that LAMs are induced by local lipid exposure, leading to their induction in steatotic regions of the murine and human liver, while Kupffer cell development crucially depends on their cross-talk with hepatic stellate cells via the evolutionarily conserved ALK1-BMP9/10 axis.
Computational trajectory inference enables the reconstruction of cell state dynamics from single-cell RNA sequencing experiments. However, trajectory inference requires that the direction of a biological process is known, largely limiting its application to differentiating systems in normal development. Here, we present CellRank (https://cellrank.org) for single-cell fate mapping in diverse scenarios, including regeneration, reprogramming and disease, for which direction is unknown. Our approach combines the robustness of trajectory inference with directional information from RNA velocity, taking into account the gradual and stochastic nature of cellular fate decisions, as well as uncertainty in velocity vectors. On pancreas development data, CellRank automatically detects initial, intermediate and terminal populations, predicts fate potentials and visualizes continuous gene expression trends along individual lineages. Applied to lineage-traced cellular reprogramming data, predicted fate probabilities correctly recover reprogramming outcomes. CellRank also predicts a new dedifferentiation trajectory during postinjury lung regeneration, including previously unknown intermediate cell states, which we confirm experimentally.
Brain metastasis (BrM) is the most common form of brain cancer, characterized by neurologic disability and an abysmal prognosis. Unfortunately, our understanding of the biology underlying human BrMs remains rudimentary. Here, we present an integrative analysis of >100,000 malignant and non-malignant cells from 15 human parenchymal BrMs, generated by single-cell transcriptomics, mass cytometry, and complemented with mouse model- and in silico approaches. We interrogated the composition of BrM niches, molecularly defined the blood-tumor interface, and revealed stromal immunosuppressive states enriched with infiltrated T cells and macrophages. Specific single-cell interrogation of metastatic tumor cells provides a framework of 8 functional cell programs that coexist or anticorrelate. Collectively, these programs delineate two functional BrM archetypes, one proliferative and the other inflammatory, that are evidently shaped through tumor-immune interactions. Our resource provides a foundation to understand the molecular basis of BrM in patients with tumor cell-intrinsic and host environmental traits.
Severe immune-related adverse events (irAEs) occur in up to 60% of patients with melanoma treated with immune checkpoint inhibitors (ICIs). However, it is unknown whether a common baseline immunological state precedes irAE development. Here we applied mass cytometry by time of flight, single-cell RNA sequencing, single-cell V(D)J sequencing, bulk RNA sequencing and bulk T cell receptor (TCR) sequencing to study peripheral blood samples from patients with melanoma treated with anti-PD-1 monotherapy or anti-PD-1 and anti-CTLA-4 combination ICIs. By analyzing 93 pre- and early on-ICI blood samples and 3 patient cohorts (n = 27, 26 and 18), we found that 2 pretreatment factors in circulation—activated CD4 memory T cell abundance and TCR diversity—are associated with severe irAE development regardless of organ system involvement. We also explored on-treatment changes in TCR clonality among patients receiving combination therapy and linked our findings to the severity and timing of irAE onset. These results demonstrate circulating T cell characteristics associated with ICI-induced toxicity, with implications for improved diagnostics and clinical management.
Technologies for counting protein molecules are enabling single-cell proteomics at increasing depth and scale. New advances in single-molecule methods by Brinkerhoff and colleagues promise to further increase the sensitivity of protein analysis and motivate questions about scaling up the counting of the human proteome.
In mammals, white adipose tissues are largely divided into visceral epididymal adipose tissue (EAT) and subcutaneous inguinal adipose tissue (IAT) with distinct metabolic properties. Although emerging evidence suggests that subpopulations of adipose stem cells (ASCs) would be important to explain fat depot differences, ASCs of two fat depots have not been comparatively investigated. Here, we characterized heterogeneous ASCs and examined the effects of intrinsic and tissue micro-environmental factors on distinct ASC features. We demonstrated that ASC subpopulations in EAT and IAT exhibited different molecular features with three adipogenic stages. ASC transplantation experiments revealed that intrinsic ASC features primarily determined their adipogenic potential. Upon obesogenic stimuli, EAT-specific SDC1+ ASCs promoted fibrotic remodeling, whereas IAT-specific CXCL14+ ASCs suppressed macrophage infiltration. Moreover, IAT-specific BST2high ASCs exhibited a high potential to become beige adipocytes. Collectively, our data broaden the understanding of ASCs with new insights into the origin of white fat depot differences.
The T cell receptor (TCR) endows T cells with antigen specificity and is central to nearly all aspects of T cell function. Each naïve T cell has a unique TCR sequence that is stably maintained during cell division. In this way, the TCR serves as a molecular barcode that tracks processes such as migration, differentiation, and proliferation of T cells. Recent technological advances have enabled sequencing of the TCR from single cells alongside deep molecular phenotypes on an unprecedented scale. In this review, we discuss strengths and limitations of TCR sequences as molecular barcodes and their application to study immune responses following Programmed Death-1 (PD-1) blockade in cancer. Additionally, we consider applications of TCR data beyond use as a barcode.
In association with the pandemic spreading of obesity and metabolic syndrome, the prevalence of NAFLD-related HCC is increasing almost exponentially. In recent years, many of the underlining multifactorial causes of NAFLD have been identified, and the cellular mechanisms sustaining disease development have been dissected up to the single-cell level. However, there is still an urgent need to provide clinicians with more therapeutic targets, with particular attention on NAFLD-induced HCC, where immune checkpoint inhibitors do not work as efficiently. Whereas much effort has been invested in elucidating the role of innate immune response in the hepatic NAFLD microenvironment, only in the past decade have novel critical roles been unraveled for T cells in driving chronic inflammation toward HCC. The metabolic and immune microenvironment interact to recreate a tumor-promoting and immune-suppressive terrain, responsible for resistance to anticancer therapy. In this article, we will review the specific functions of several T-cell populations involved in NAFLD and NAFLD-driven HCC. We will illustrate the cellular crosstalk with other immune cells, regulatory networks or stimulatory effects of these interactions, and role of the metabolic microenvironment in influencing immune cell functionality. Finally, we will present the pros and cons of the current therapeutic strategies against NAFLD-related HCC and delineate possible novel approaches for the future.
HCC is a highly aggressive and heterogeneous cancer type with limited treatment options. Identifying drivers of tumor heterogeneity may lead to better therapeutic options and favorable patient outcomes. We investigated whether apoptotic cell death and its spatial architecture is linked to tumor molecular heterogeneity using single-cell in situ hybridization analysis.
Micro-organisms play key roles in various ecosystems, but many of their functions and interactions remain undefined. To investigate the ecological relevance of microbial communities, new molecular tools are being developed. Among them, single-cell omics assessing genetic diversity at the population and community levels and linking each individual cell to its functions is gaining interest in microbial ecology. By giving access to a wider range of ecological scales (from individual to community) than culture-based approaches and meta-omics, single-cell omics can contribute not only to micro-organisms' genomic and functional identification but also to the testing of concepts in ecology. Here, we discuss the contribution of single-cell omics to possible breakthroughs in concepts and knowledge on microbial ecosystems and ecoevolutionary processes.
Quantitative optical microscopy—an emerging, transformative approach to single-cell biology—has seen dramatic methodological advancements over the past few years. However, its impact has been hampered by challenges in the areas of data generation, management, and analysis. Here we outline these technical and cultural challenges and provide our perspective on the trajectory of this field, ushering in a new era of quantitative, data-driven microscopy. We also contrast it to the three decades of enormous advances in the field of genomics that have significantly enhanced the reproducibility and wider adoption of a plethora of genomic approaches.
Antimicrobial resistance is a global threat that if left unchecked could lead to 10 million annual mortalities by 2050. One factor contributing to the rise of multi-drug-resistant (MDR) pathogens is the reliance on traditional culture-based pathogen identification (ID) and antimicrobial susceptibility testing (AST) that typically takes several days. This delay of objective pathogen ID and AST information to inform clinical decision making results in clinicians treating patients empirically often using first-line, broad-spectrum antibiotics, contributing to the misuse/overuse of antibiotics. To combat the rise in MDR pathogens, there is a critical demand for rapid ID and AST technologies. Among the advances in ID and AST technologies in the past decade, single-cell diagnostic technologies powered by droplet microfluidics offer great promise due to their potential for high-sensitivity detection and rapid turnaround time. Our laboratory has been at the forefront of developing such technologies and applying them to diagnosing urinary tract infections (UTIs), one of the most common infections and a frequent reason for the prescription of antimicrobials. For pathogen ID, we first demonstrated the highly sensitive, amplification-free detection of single bacterial cells by confining them in picoliter-scale droplets and detection with fluorogenic peptide nucleic acid (PNA) probes that target their 16S rRNA (rRNA), a well-characterized marker for phylogenic classification. We subsequently improved the PNA probe design and enhanced detection sensitivity. For single-cell AST, we first employed a growth indicator dye and engineered an integrated device that allows us to detect growth from single bacterial cells under antibiotic exposure within 1 h, equivalent to two to three bacterial replications. To expand beyond testing a single antibiotic condition per device, a common limitation for droplet microfluidics, we developed an integrated programmable droplet microfluidic device for scalable single-cell AST. Using the scalable single-cell AST platform, we demonstrated the generation of up to 32 droplet groups in a single device with custom antibiotic titers and the capacity to scale up single-cell AST, and providing reliable pathogen categories beyond a binary call embodies a critical advance. Finally, we developed an integrated ID and AST platform. To this end, we developed a PNA probe panel that can identify nearly 90% of uropathogens and showed the quantitative detection of 16S rRNA from single bacterial cells in droplet-enabled AST after as little as 10 min of antibiotic exposure. This platform achieved both ID and AST from minimally processed urine samples in 30 min, representing one of the fastest turnaround times to date. In addition to tracing the development of our technologies, we compare them with contemporary research advances and offer our perspectives for future development, with the vision that single-cell ID and AST technologies powered by droplet microfluidics can indeed become a useful diagnostic tool for combating antimicrobial resistance.
The adenoma-carcinoma sequence is a well-accepted roadmap for the development of sporadic colorectal cancer. However, cellular heterogeneity in aberrant epithelial cells limits our understanding of carcinogenesis in colorectal tissues. Here, we performed a single-cell RNA sequencing survey of 54,788 cells from patient-matched tissue samples, including blood, normal tissue, para-cancer, polyp, and colorectal cancer. At each stage of carcinogenesis, we characterized cell types, transcriptional signatures, and differentially expressed genes of distinct cell populations. The molecular signatures of epithelial cells at normal, benign, and malignant stages were defined at the single-cell scale. Adenoma and carcinoma precursor cell populations were identified and characterized followed by validation with large cohort biopsies. Protein tyrosine kinases (PTKs) BMX and HCK were identified as potential drivers of adenoma initiation. Specific BMX and HCK upregulations were observed in adenoma precursor cell populations from normal and adenoma biopsies. Overexpression of BMX and HCK significantly promoted colorectal epithelial cell proliferation. Importantly, in the organoid culture system, BMX and HCK upregulations resulted in the formation of multilayered polyp-like buds protruding towards the organoid lumen, mimicking the pathological polyp morphology often observed in colorectal cancer. Molecular mechanism analysis revealed that upregulation of BMX or HCK activated the JAK-STAT pathway. In conclusion, our work improved the current knowledge regarding colorectal epithelial evolution during carcinogenesis at the single-cell resolution. These findings may lead to improvements in colorectal cancer diagnosis and treatment.
Single-cell whole-genome haplotyping allows simultaneous detection of haplotypes associated with monogenic diseases, chromosome copy-numbering and subsequently, has revealed mosaicism in embryos and embryonic stem cells. Methods, such as karyomapping and haplarithmisis, were deployed as a generic and genome-wide approach for preimplantation genetic testing (PGT) and are replacing traditional PGT methods. While current methods primarily rely on single-nucleotide polymorphism (SNP) array, we envision sequencing-based methods to become more accessible and cost-efficient. Here, we developed a novel sequencing-based methodology to haplotype and copy-number profile single cells. Following DNA amplification, genomic size and complexity is reduced through restriction enzyme digestion and DNA is genotyped through sequencing. This single-cell genotyping-by-sequencing (scGBS) is the input for haplarithmisis, an algorithm we previously developed for SNP array-based single-cell haplotyping. We established technical parameters and developed an analysis pipeline enabling accurate concurrent haplotyping and copy-number profiling of single cells. We demonstrate its value in human blastomere and trophectoderm samples as application for PGT for monogenic disorders. Furthermore, we demonstrate the method to work in other species through analyzing blastomeres of bovine embryos. Our scGBS method opens up the path for single-cell haplotyping of any species with diploid genomes and could make its way into the clinic as a PGT application.
Inhibitors of the programmed cell death-1 (PD-1/PD-L1) signaling axis are approved to treat non-small cell lung cancer (NSCLC) patients, based on their significant overall survival (OS) benefit. Using transcriptomic analysis of 891 NSCLC tumors from patients treated with either the PD-L1 inhibitor atezolizumab or chemotherapy from two large randomized clinical trials, we find a significant B cell association with extended OS with PD-L1 blockade, independent of CD8+ T cell signals. We then derive gene signatures corresponding to the dominant B cell subsets present in NSCLC from single-cell RNA sequencing (RNA-seq) data. Importantly, we find increased plasma cell signatures to be predictive of OS in patients treated with atezolizumab, but not chemotherapy. B and plasma cells are also associated with the presence of tertiary lymphoid structures and organized lymphoid aggregates. Our results suggest an important contribution of B and plasma cells to the efficacy of PD-L1 blockade in NSCLC.
The mammalian brain contains many specialized cells that develop from a thin sheet of neuroepithelial progenitor cells. Single-cell transcriptomics revealed hundreds of molecularly diverse cell types in the nervous system, but the lineage relationships between mature cell types and progenitor cells are not well understood. Here we show in vivo barcoding of early progenitors to simultaneously profile cell phenotypes and clonal relations in the mouse brain using single-cell and spatial transcriptomics. By reconstructing thousands of clones, we discovered fate-restricted progenitor cells in the mouse hippocampal neuroepithelium and show that microglia are derived from few primitive myeloid precursors that massively expand to generate widely dispersed progeny. We combined spatial transcriptomics with clonal barcoding and disentangled migration patterns of clonally related cells in densely labeled tissue sections. Our approach enables high-throughput dense reconstruction of cell phenotypes and clonal relations at the single-cell and tissue level in individual animals and provides an integrated approach for understanding tissue architecture.
Tumor-associated macrophages have emerged as crucial factors for metastases. Microglia are indispensable components of the brain microenvironment and play vital roles in brain metastasis (BM). However, the underlying mechanism of how activated microglia promote brain metastasis of non-small cell lung cancer (NSCLC) remains elusive. Here, we purified cell lines with brain-metastatic tropism and employed a co-culture system to reveal their communication with microglia. By single-cell RNA-sequencing and transcriptome difference analysis, we identified IL6 as the key regulator in brain-metastatic cells (A549-F3) to induce anti-inflammatory microglia via JAK2/STAT3 signaling, which in turn promoted the colonization process in metastatic A549-F3 cells. In our clinical samples, patients with higher levels of IL6 in serum showed higher propensity for brain metastasis. Additionally, the TCGA (The Cancer Genome Atlas) data revealed that NSCLC patients with a lower level of IL6 had a longer overall survival time compared to those with a higher level of IL6. Overall, our data indicate that the targeting of IL6/JAK2/STAT3 signaling in activated microglia may be a promising new approach for inhibiting brain metastasis in NSCLC patients.
Deciphering the cellular composition in genome-wide spatially resolved transcriptomic data is a critical task to clarify the spatial context of cells in a tissue. In this study, we developed a method, CellDART, which estimates the spatial distribution of cells defined by single-cell level data using domain adaptation of neural networks and applied it to the spatial mapping of human lung tissue. The neural network that predicts the cell proportion in a pseudospot, a virtual mixture of cells from single-cell data, is translated to decompose the cell types in each spatial barcoded region. First, CellDART was applied to mouse brain and human dorsolateral prefrontal cortex tissue to identify cell types with a layer-specific spatial distribution. Overall, the suggested approach was competent to the other computational methods in predicting the spatial localization of excitatory neurons. Besides, CellDART was capable of decomposing cellular proportion in mouse hippocampus Slide-seq data. Furthermore, CellDART elucidated the cell type predominance defined by the human lung cell atlas across the lung tissue compartments and it corresponded to the known prevalent cell types. CellDART is expected to help to elucidate the spatial heterogeneity of cells and their close interactions in various tissues.
Extracellular vesicles (EVs) are potent signalling mediators. Although interest in EV translation is ever-increasing, development efforts are hampered by the inability to reliably assess the uptake of EVs and their RNA cargo. Here, we establish a novel qPCR-based method for the detection of unmodified EVs using an RNA Tracer (DUST). In this proof-of-concept study we use a human-specific Y RNA-derived small RNA (YsRNA) we dub “NT4” that is enriched in cardiosphere-derived cell small EVs (CDC-sEVs). The assay is robust, sensitive, and reproducible. Intravenously administered CDC-sEVs accumulated primarily in the heart on a per mg basis. Cardiac injury enhanced EV uptake in the heart, liver, and brain. Inhibition of EV docking by heparin suppressed uptake variably, while inhibition of endocytosis attenuated uptake in all organs. In vitro, EVs were uptaken more efficiently by macrophages, endothelial cells, and cardiac fibroblasts compared to cardiomyocytes. These findings demonstrate the utility of DUST to assess uptake of EVs in vivo and in vitro.
During neurogenesis, mitotic progenitor cells lining the ventricles of the embryonic mouse brain undergo their final rounds of cell division, giving rise to a wide spectrum of postmitotic neurons and glia1,2. The link between developmental lineage and cell-type diversity remains an open question. Here we used massively parallel tagging of progenitors to track clonal relationships and transcriptomic signatures during mouse forebrain development. We quantified clonal divergence and convergence across all major cell classes postnatally, and found diverse types of GABAergic neuron that share a common lineage. Divergence of GABAergic clones occurred during embryogenesis upon cell-cycle exit, suggesting that differentiation into subtypes is initiated as a lineage-dependent process at the progenitor cell level.
The emergence of SARS-CoV-2 variants is jeopardizing the effectiveness of current vaccines and limiting the application of monoclonal antibody-based therapy for COVID-19 (refs. 1,2). Here we analysed the memory B cells of five naive and five convalescent people vaccinated with the BNT162b2 mRNA vaccine to investigate the nature of the B cell and antibody response at the single-cell level. Almost 6,000 cells were sorted, over 3,000 cells produced monoclonal antibodies against the spike protein and more than 400 cells neutralized the original SARS-CoV-2 virus first identified in Wuhan, China. The B.1.351 (Beta) and B.1.1.248 (Gamma) variants escaped almost 70% of these antibodies, while a much smaller portion was impacted by the B.1.1.7 (Alpha) and B.1.617.2 (Delta) variants. The overall loss of neutralization was always significantly higher in the antibodies from naive people. In part, this was due to the IGHV2-5;IGHJ4-1 germline, which was found only in people who were convalescent and generated potent and broadly neutralizing antibodies. Our data suggest that people who are seropositive following infection or primary vaccination will produce antibodies with increased potency and breadth and will be able to better control emerging SARS-CoV-2 variants.
SARS-CoV-2 is a single-stranded RNA virus that causes COVID-19. Given its acute and often self-limiting course, it is likely that components of the innate immune system play a central part in controlling virus replication and determining clinical outcome. Natural killer (NK) cells are innate lymphocytes with notable activity against a broad range of viruses, including RNA viruses1,2. NK cell function may be altered during COVID-19 despite increased representation of NK cells with an activated and adaptive phenotype3,4. Here we show that a decline in viral load in COVID-19 correlates with NK cell status and that NK cells can control SARS-CoV-2 replication by recognizing infected target cells. In severe COVID-19, NK cells show defects in virus control, cytokine production and cell-mediated cytotoxicity despite high expression of cytotoxic effector molecules. Single-cell RNA sequencing of NK cells over the time course of the COVID-19 disease spectrum reveals a distinct gene expression signature. Transcriptional networks of interferon-driven NK cell activation are superimposed by a dominant transforming growth factor-β (TGFβ) response signature, with reduced expression of genes related to cell–cell adhesion, granule exocytosis and cell-mediated cytotoxicity. In severe COVID-19, serum levels of TGFβ peak during the first two weeks of infection, and serum obtained from these patients severely inhibits NK cell function in a TGFβ-dependent manner. Our data reveal that an untimely production of TGFβ is a hallmark of severe COVID-19 and may inhibit NK cell function and early control of the virus.
Gaining a better understanding of the immune cell subsets and molecular factors associated with protective or pathological immunity against severe acute respiratory syndrome coronavirus (SARS-CoV)-2 could aid the development of vaccines and therapeutics for coronavirus disease 2019 (COVID-19). Single-cell technologies, such as flow cytometry, mass cytometry, single-cell transcriptomics and single-cell multi-omic profiling, offer considerable promise in dissecting the heterogeneity of immune responses among individual cells and uncovering the molecular mechanisms of COVID-19 pathogenesis. Single-cell immune-profiling studies reported to date have identified innate and adaptive immune cell subsets that correlate with COVID-19 disease severity, as well as immunological factors and pathways of potential relevance to the development of vaccines and treatments for COVID-19. For facilitation of integrative studies and meta-analyses into the immunology of SARS-CoV-2 infection, we provide standardized, download-ready versions of 21 published single-cell sequencing datasets (over 3.2 million cells in total) as well as an interactive visualization portal for data exploration.
Prognostically relevant RNA expression states exist in pancreatic ductal adenocarcinoma (PDAC), but our understanding of their drivers, stability, and relationship to therapeutic response is limited. To examine these attributes systematically, we profiled metastatic biopsies and matched organoid models at single-cell resolution. In vivo, we identify a new intermediate PDAC transcriptional cell state and uncover distinct site- and state-specific tumor microenvironments (TMEs). Benchmarking models against this reference map, we reveal strong culture-specific biases in cancer cell transcriptional state representation driven by altered TME signals. We restore expression state heterogeneity by adding back in vivo-relevant factors and show plasticity in culture models. Further, we prove that non-genetic modulation of cell state can strongly influence drug responses, uncovering state-specific vulnerabilities. This work provides a broadly applicable framework for aligning cell states across in vivo and ex vivo settings, identifying drivers of transcriptional plasticity and manipulating cell state to target associated vulnerabilities.
Severe COVID-19 is linked to both dysfunctional immune response and unrestrained immunopathology, and it remains unclear whether T cells contribute to disease pathology. Here, we combined single-cell transcriptomics and single-cell proteomics with mechanistic studies to assess pathogenic T cell functions and inducing signals. We identified highly activated CD16+ T cells with increased cytotoxic functions in severe COVID-19. CD16 expression enabled immune-complex-mediated, T cell receptor-independent degranulation and cytotoxicity not found in other diseases. CD16+ T cells from COVID-19 patients promoted microvascular endothelial cell injury and release of neutrophil and monocyte chemoattractants. CD16+ T cell clones persisted beyond acute disease maintaining their cytotoxic phenotype. Increased generation of C3a in severe COVID-19 induced activated CD16+ cytotoxic T cells. Proportions of activated CD16+ T cells and plasma levels of complement proteins upstream of C3a were associated with fatal outcome of COVID-19, supporting a pathological role of exacerbated cytotoxicity and complement activation in COVID-19.
The lung is the primary organ targeted by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), making respiratory failure a leading coronavirus disease 2019 (COVID-19)-related mortality. However, our cellular and molecular understanding of how SARS-CoV-2 infection drives lung pathology is limited. Here we constructed multi-omics and single-nucleus transcriptomic atlases of the lungs of patients with COVID-19, which integrate histological, transcriptomic and proteomic analyses. Our work reveals the molecular basis of pathological hallmarks associated with SARS-CoV-2 infection in different lung and infiltrating immune cell populations. We report molecular fingerprints of hyperinflammation, alveolar epithelial cell exhaustion, vascular changes and fibrosis, and identify parenchymal lung senescence as a molecular state of COVID-19 pathology. Moreover, our data suggest that FOXO3A suppression is a potential mechanism underlying the fibroblast-to-myofibroblast transition associated with COVID-19 pulmonary fibrosis. Our work depicts a comprehensive cellular and molecular atlas of the lungs of patients with COVID-19 and provides insights into SARS-CoV-2-related pulmonary injury, facilitating the identification of biomarkers and development of symptomatic treatments.