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A spatiotemporally resolved single-cell atlas of the Plasmodium liver stage.
Malaria infection involves an obligatory, yet clinically silent liver stage1,2. Hepatocytes operate in repeating units termed lobules, exhibiting heterogeneous gene expression patterns along the lobule axis3, but the effects of hepatocyte zonation on parasite development at the molecular level remain unknown. Here we combine single-cell RNA sequencing4 and single-molecule transcript imaging5 to characterize the host and parasite temporal expression programmes in a zonally controlled manner for the rodent malaria parasite Plasmodium berghei ANKA. We identify differences in parasite gene expression in distinct zones, including potentially co-adaptive programmes related to iron and fatty acid metabolism. We find that parasites develop more rapidly in the pericentral lobule zones and identify a subpopulation of periportally biased hepatocytes that harbour abortive infections, reduced levels of Plasmodium transcripts and parasitophorous vacuole breakdown. These 'abortive hepatocytes', which appear predominantly with high parasite inoculum, upregulate immune recruitment and key signalling programmes. Our study provides a resource for understanding the liver stage of Plasmodium infection at high spatial resolution and highlights the heterogeneous behaviour of both the parasite and the host hepatocyte.
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A sensitive method for profiling cell-type-specific secretomes of rare cells from complex tissues.
Very rare cells often have outsized physiologic functions. However, their low abundance presents a technical challenge for studying their function. Here, we generate a murine model, which enables the profiling of secreted proteomes (secretomes) from physiologically relevant low-abundance cells in complex tissues, without the use of viral vectors. We then deploy this model to profile the secretomes of two rare innate immune cell types: Kupffer macrophages from whole liver and the rare airway microfold (M) cells in cultures of differentiated airway epithelia. The method we have developed is characterized by remarkable sensitivity, capturing cell-specific proteins that were not captured in single-cell RNA sequencing (scRNA-seq) atlases. We have made this genetic secretome mouse model available to the community to empower future studies of cell-to-cell communication, secreted protein function, and biomarker discovery for any given cell type in vitro or in vivo.
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Decoding the Cell Atlas and Inflammatory Features of Human Intracranial Aneurysm Wall by Single-Cell RNA Sequencing.
BACKGROUND: Intracranial aneurysm (IA) is common and occasionally results in life-threatening hemorrhagic strokes. However, the cell architecture and inflammation in the IA dome remain less understood. METHODS AND RESULTS: Single-cell RNA sequencing was performed on ruptured and unruptured human IA domes for delineating the cell atlas, gene expression perturbations, and inflammation features. Two external bulk mRNA sequencing-based data sets and serological results of 126 patients were collected for validation. As a result, a total of 21 332 qualified cells were captured. Vascular cells, including endothelial cells, smooth muscle cells, fibroblasts, and pericytes, were assigned in extremely sparse numbers (4.84%), and were confirmed by immunofluorescence staining. Pericytes, characterized by ABCC9 and HIGD1B, were identified in the IA dome for the first time. Abundant immune cells were identified, with the proportion of monocytes/macrophages and neutrophils being remarkably higher in ruptured IA. The lymphocyte compartment was also thoroughly categorized. By leveraging external data sets and machine learning algorithms, macrophages were robustly associated with IA rupture, irrespective of their polarization status. The single nucleotide polymorphism rs2280543, which is identified in East Asian populations, was associated with macrophage metabolic reprogramming through regulating TALDO1 expression. CONCLUSIONS: This study provides insights into the cellular architecture and inflammatory features in the IA dome and may enlighten novel therapeutics for unruptured IA.
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Comprehensive landscape of the IPAF inflammasomes in pan-cancer: A bulk omics research and single-cell sequencing validation.
BACKGROUND: IPAF (ICE-protease Activating Factor) is a nucleotide-binding/leucine-rich repeat (NLR) protein known as the cysteine-associated recruitment domain 12 (CARD12). Previous studies only discuss the role of IPAF inflammasomes in specific tumors. The role of IPAF inflammasomes in pan-cancer is still unclear. Therefore, we performed a comprehensive analysis of IPAF inflammasome in 33 tumors. METHODS: We used databases like The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) from the UCSC XENA (http://xena.ucsc.edu/) to retrieve and analyze gene expression. The influence of IPAF inflammasome on the prognosis of tumor patients was analyzed using univariate Cox regression analysis and Kaplan-Meier survival analysis. Furthermore, we conducted the following analysis: Single-sample gene set enrichment analysis, single-cell level functional state analysis, single-cell sequencing, immune cell infiltration analysis, and tumor immune dysfunction and exclusion (TIDE) score. RESULTS: First, the differential expression of IPAF inflammasome-related genes (IPAF-RGs) in 33 tumors were analyzed. The results revealed that IPAF-RGs were significantly and differentially expressed in eight tumors. The prognostic significance of IPAF inflammasome scores was different in different tumors. A positive correlation was observed between IPAF inflammasomes scores and CD8+ T cells in most tumors. Further analysis revealed that IPAF inflammasome might affect tumor immunity mainly by mediating effector T cell recruitment via the expression of chemokines such as CXCL9, CXCL10, and CCL5. The analysis of TIDE and IPAF inflammasome scores revealed a significant negative correlation between IPAF inflammasome and TIDE scores in 11 tumors. CONCLUSION: A pan-cancer analysis of IPAF inflammasome in various tumors was performed. The results highlight the potential value of IPAF inflammasome in response to immunotherapy in patients and provide a new direction for future immunotherapy.
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Rapid single cell evaluation of human disease and disorder targets using REVEAL: SingleCell™.
BACKGROUND: Single-cell (sc) sequencing performs unbiased profiling of individual cells and enables evaluation of less prevalent cellular populations, often missed using bulk sequencing. However, the scale and the complexity of the sc datasets poses a great challenge in its utility and this problem is further exacerbated when working with larger datasets typically generated by consortium efforts. As the scale of single cell datasets continues to increase exponentially, there is an unmet technological need to develop database platforms that can evaluate key biological hypotheses by querying extensive single-cell datasets. Large single-cell datasets like Human Cell Atlas and COVID-19 cell atlas (collection of annotated sc datasets from various human organs) are excellent resources for profiling target genes involved in human diseases and disorders ranging from oncology, auto-immunity, as well as infectious diseases like COVID-19 caused by SARS-CoV-2 virus. SARS-CoV-2 infections have led to a worldwide pandemic with massive loss of lives, infections exceeding 7 million cases. The virus uses ACE2 and TMPRSS2 as key viral entry associated proteins expressed in human cells for infections. Evaluating the expression profile of key genes in large single-cell datasets can facilitate testing for diagnostics, therapeutics, and vaccine targets, as the world struggles to cope with the on-going spread of COVID-19 infections. MAIN BODY: In this manuscript we describe REVEAL: SingleCell, which enables storage, retrieval, and rapid query of single-cell datasets inclusive of millions of cells. The array native database described here enables selecting and analyzing cells across multiple studies. Cells can be selected using individual metadata tags, more complex hierarchical ontology filtering, and gene expression threshold ranges, including co-expression of multiple genes. The tags on selected cells can be further evaluated for testing biological hypotheses. One such example includes identifying the most prevalent cell type annotation tag on returned cells. We used REVEAL: SingleCell to evaluate the expression of key SARS-CoV-2 entry associated genes, and queried the current database (2.2 Million cells, 32 projects) to obtain the results in < 60 s. We highlighted cells expressing COVID-19 associated genes are expressed on multiple tissue types, thus in part explains the multi-organ involvement in infected patients observed worldwide during the on-going COVID-19 pandemic. CONCLUSION: In this paper, we introduce the REVEAL: SingleCell database that addresses immediate needs for SARS-CoV-2 research and has the potential to be used more broadly for many precision medicine applications. We used the REVEAL: SingleCell database as a reference to ask questions relevant to drug development and precision medicine regarding cell type and co-expression for genes that encode proteins necessary for SARS-CoV-2 to enter and reproduce in cells.
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Cellular diversity of the developing chick trigeminal ganglion at single-cell resolution.
BACKGROUND: The trigeminal ganglion (TG) is a structure of the peripheral nervous system, composed of neuronal and non-neuronal cell types, that integrates sensory input from the face and jaw. The developing TG is derived from two embryonic cell populations: neural crest and cranial placode. Both populations play critical roles in TG development and must interact to coordinate changes in gene expression that regulate specification, differentiation, and organization. However, the molecular characteristics of the heterogeneous cell populations within the developing TG remain poorly defined. RESULTS: We performed single-cell RNA-sequencing (scRNA-seq) on TG from developing chick embryos at HH17. Our high-resolution dataset (14 clusters, ~87000 cells) provides insight into cellular diversity within the developing TG. As expected, we identified placode-derived neurons as well as neural crest cells prior to neuronal differentiation. In addition to classic markers, we identified novel transcripts with unknown roles in TG development, including several long non-coding RNAs (lncRNAs). CONCLUSIONS: We generated a single-cell atlas of the developing chick trigeminal ganglion during early axonogenesis and defined the transcriptomic states of its diverse cell populations. Our results provide a useful resource for better understanding the cell populations contributing to TG development and gene expression that drives cell identity and differentiation.
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The Physcomitrella patens gene atlas project: large-scale RNA-seq based expression data.
High-throughput RNA sequencing (RNA-seq) has recently become the method of choice to define and analyze transcriptomes. For the model moss Physcomitrella patens, although this method has been used to help analyze specific perturbations, no overall reference dataset has yet been established. In the framework of the Gene Atlas project, the Joint Genome Institute selected P. patens as a flagship genome, opening the way to generate the first comprehensive transcriptome dataset for this moss. The first round of sequencing described here is composed of 99 independent libraries spanning 34 different developmental stages and conditions. Upon dataset quality control and processing through read mapping, 28 509 of the 34 361 v3.3 gene models (83%) were detected to be expressed across the samples. Differentially expressed genes (DEGs) were calculated across the dataset to permit perturbation comparisons between conditions. The analysis of the three most distinct and abundant P. patens growth stages - protonema, gametophore and sporophyte - allowed us to define both general transcriptional patterns and stage-specific transcripts. As an example of variation of physico-chemical growth conditions, we detail here the impact of ammonium supplementation under standard growth conditions on the protonemal transcriptome. Finally, the cooperative nature of this project allowed us to analyze inter-laboratory variation, as 13 different laboratories around the world provided samples. We compare differences in the replication of experiments in a single laboratory and between different laboratories.
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Characterizing the tumor microenvironment at the single-cell level reveals a novel immune evasion mechanism in osteosarcoma.
The immune microenvironment extensively participates in tumorigenesis as well as progression in osteosarcoma (OS). However, the landscape and dynamics of immune cells in OS are poorly characterized. By analyzing single-cell RNA sequencing (scRNA-seq) data, which characterize the transcription state at single-cell resolution, we produced an atlas of the immune microenvironment in OS. The results suggested that a cluster of regulatory dendritic cells (DCs) might shape the immunosuppressive microenvironment in OS by recruiting regulatory T cells. We also found that major histocompatibility complex class I (MHC-I) molecules were downregulated in cancer cells. The findings indicated a reduction in tumor immunogenicity in OS, which can be a potential mechanism of tumor immune escape. Of note, CD24 was identified as a novel "don't eat me" signal that contributed to the immune evasion of OS cells. Altogether, our findings provide insights into the immune landscape of OS, suggesting that myeloid-targeted immunotherapy could be a promising approach to treat OS.
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Deciphering craniopharyngioma subtypes: Single-cell analysis of tumor microenvironment and immune networks.
Craniopharyngiomas, including adamantinomatous (ACP) and squamous papillary (PCP) types, are challenging to treat because of their proximity to crucial pituitary structures. This study aimed to characterize the cellular composition, tumor tissue diversity, and cell-cell interactions in ACPs and PCPs using single-cell RNA sequencing. Single-cell clustering revealed diverse cell types, further classified into developing epithelial, calcification, and immune response for ACP and developing epithelial, cell cycle, and immune response for PCP, based on gene expression patterns. Subclustering revealed the enrichment of classical M1 and M2 macrophages in ACP and PCP, respectively, with high expression of pro-inflammatory markers in classical M1 macrophages. The classical M1 and M2 macrophage ratio significantly correlated with the occurrence of diabetes insipidus and panhypopituitarism. Cell-cell interactions, particularly involving CD44-SPP, were identified between tumor cells. Thus, we developed a comprehensive cell atlas that elucidated the molecular characteristics and immune cell inter-networking in ACP and PCP tumor microenvironments.
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Single-cell analyses unravel ecosystem dynamics and intercellular crosstalk during gallbladder cancer malignant transformation.
BACKGROUND: Gallbladder cancer (GBC) is a rare but aggressive malignancy, often detected late due to early asymptomatic stages. Understanding cellular and molecular changes from normal tissue to high-grade intraepithelial neoplasia (HGIN) and invasive GBC is vital for identifying early biomarkers and therapeutic targets. METHODS: We performed single-cell RNA sequencing on 98,113 cells derived from 2 normal adjacent tissues (NAT), 2 HGIN, and 6 GBC samples. The cellular diversity and heterogeneity, particularly within epithelial and immune cell populations in NAT-HGIN-GBC, were investigated utilizing single-cell RNA sequencing, bulk RNA sequencing (bulk RNA-seq), and 10 machine learning methodologies. Furthermore, the intercellular crosstalk between epithelial cells and tumor immune microenvironment cells was examined and validated through multiplex immunofluorescence staining. RESULTS: The constructed cell atlas elucidated alterations in the immune landscape across various states of NAT-HGIN-GBC, highlighting a more pronounced inhibitory immune microenvironment in GBC. The epithelial subtype TOP2A+ Epi is markedly elevated in GBC and is correlated with a poor prognosis. Key genes associated with this subtype may include GMNN, CYTOR, KLK6, and BIRC5. Similarly, immunosuppressive macrophages, identified as TOP2A+ Macro, also increase along the NAT-HGIN-GBC sequence and are linked to reduced patient survival. Furthermore, TOP2A+ Macro and CD8+ exhausted T cells (CD8+ Tex) engage in intercellular communication with epithelial TOP2A+Epi cells via the TWEAK/FN14 signaling pathway, thereby promoting tumor progression and immune evasion in GBC. The findings were further corroborated through multiplex immunofluorescence staining conducted on specimens from patients. CONCLUSIONS: This study elucidates significant alteration in the cellular ecosystems and intercellular signaling within the tumor immune microenvironment across the NAT-HGIN-GBC sequence. It identifies TOP2A, TWEAK, and FN14 as potential biomarkers and therapeutic targets for GBC.