The functions of epithelial tissues are dictated by the types, abundance and distribution of the differentiated cells they contain. Attempts to restore tissue function after damage require knowledge ...of how physiological tasks are distributed among cell types, and how cell states vary between homeostasis, injury-repair and disease. In the conducting airway, a heterogeneous basal cell population gives rise to specialized luminal cells that perform mucociliary clearance
. Here we perform single-cell profiling of human bronchial epithelial cells and mouse tracheal epithelial cells to obtain a comprehensive census of cell types in the conducting airway and their behaviour in homeostasis and regeneration. Our analysis reveals cell states that represent known and novel cell populations, delineates their heterogeneity and identifies distinct differentiation trajectories during homeostasis and tissue repair. Finally, we identified a novel, rare cell type that we call the 'pulmonary ionocyte', which co-expresses FOXI1, multiple subunits of the vacuolar-type H
-ATPase (V-ATPase) and CFTR, the gene that is mutated in cystic fibrosis. Using immunofluorescence, modulation of signalling pathways and electrophysiology, we show that Notch signalling is necessary and FOXI1 expression is sufficient to drive the production of the pulmonary ionocyte, and that the pulmonary ionocyte is a major source of CFTR activity in the conducting airway epithelium.
Tumor-infiltrating myeloid cells (TIMs) comprise monocytes, macrophages, dendritic cells, and neutrophils, and have emerged as key regulators of cancer growth. These cells can diversify into ...a spectrum of states, which might promote or limit tumor outgrowth but remain poorly understood. Here, we used single-cell RNA sequencing (scRNA-seq) to map TIMs in non-small-cell lung cancer patients. We uncovered 25 TIM states, most of which were reproducibly found across patients. To facilitate translational research of these populations, we also profiled TIMs in mice. In comparing TIMs across species, we identified a near-complete congruence of population structures among dendritic cells and monocytes; conserved neutrophil subsets; and species differences among macrophages. By contrast, myeloid cell population structures in patients’ blood showed limited overlap with those of TIMs. This study determines the lung TIM landscape and sets the stage for future investigations into the potential of TIMs as immunotherapy targets.
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•Human dendritic cell and monocyte subsets show one-to-one equivalence in mouse•Neutrophils exhibit tumor-associated phenotypes that are conserved across species•Myeloid subsets in patient blood only partially overlap with those in their tumors•Unique markers define myeloid cell subsets and associate with clinical prognosis
Tumor-infiltrating myeloid cells (TIMs) have emerged as key cancer regulators and potential next-generation immunotherapy targets, yet they remain incompletely understood. Using scRNA-seq, Zilionis et al. map the TIM landscape in human and murine lung tumors and systematically compare cell states, revealing conserved myeloid populations across individuals and species.
► Information structure interacts with dative structures in self-paced reading. ► Word-to-word contingency statistics cannot account for this interaction. ► These results show that syntactic ...representations can include discourse constraints.
Although sentences are thought to be generally easier to process when given information precedes new information, closer examination reveals that these preferences only manifest within some syntactic structures. Here, we examine the consequences of the relative ordering of given and new information (information structure) for the on-line comprehension of prepositional-object (PO) and double-object (DO) dative sentences. Experiment 1 demonstrated using self-paced reading that the on-line comprehension of DO structures, but not PO structures, is more difficult with new-before-given information structure. Experiment 2 assessed the comprehension of dative sentences with animate themes to evaluate two potential sources of this interaction: information-structural constraints encoded within syntactic representations (argument structure hypothesis) vs. word-to-word contingency statistics (linear position hypothesis). Despite experiment-wise differences in word-to-word contingency statistics, the interaction between syntactic structure and information structure persisted in Experiment 2. Taken together, these results suggest that syntactic representations can include information-structural constraints on their arguments.
Single-cell RNA sequencing (scRNA-seq) experiments provide opportunities to peer into complex tissues at single-cell resolution. However, insightful biological interpretation of scRNA-seq data relies ...upon precise identification of cell types. The ability to identify the origin of a cell quickly and accurately will greatly improve downstream analyses. We present Sargent, a transformation-free, cluster-free, single-cell annotation algorithm for rapidly identifying the cell types of origin based on cell type-specific markers. We demonstrate Sargent's high accuracy by annotating simulated datasets. Further, we compare Sargent performance against expert-annotated scRNA-seq data from human organs including PBMC, heart, kidney, and lung. We demonstrate that Sargent retains both the flexibility and biological interpretability of cluster-based manual annotation. Additionally, the automation eliminates the labor intensive and potentially biased user annotation, producing robust, reproducible, and scalable outputs.•Sargent is a transformation-free, cluster-free, single-cell annotation algorithm for rapidly identifying the cell types of origin based on cell type-specific markers.•Sargent retains both the flexibility and biological interpretability of cluster-based manual annotation.•Automation eliminates the labor intensive and potentially biased user annotation, producing robust, reproducible, and scalable outputs.
Sargent official logo. Sargent is a transformation- and cluster-free cell-type annotation method that operates at individual cell resolution by applying a scoring system to scRNA-seq data based on sets of marker genes associated with cell types.
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Basal-like and luminal breast tumors have distinct clinical behavior and molecular profiles, yet the underlying mechanisms are poorly defined. To interrogate processes that determine these distinct ...phenotypes and their inheritance pattern, we generated somatic cell fusions and performed integrated genetic and epigenetic (DNA methylation and chromatin) profiling. We found that the basal-like trait is generally dominant and is largely defined by epigenetic repression of luminal transcription factors. Definition of super-enhancers highlighted a core program common in luminal cells but a high degree of heterogeneity in basal-like breast cancers that correlates with clinical outcome. We also found that protein extracts of basal-like cells are sufficient to induce a luminal-to-basal phenotypic switch, implying a trigger of basal-like autoregulatory circuits. We determined that KDM6A might be required for luminal-basal fusions, and we identified EN1, TBX18, and TCF4 as candidate transcriptional regulators of the luminal-to-basal switch. Our findings highlight the remarkable epigenetic plasticity of breast cancer cells.
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•The basal-like trait is generally dominant and defined by epigenetic mechanisms•Common core epigenetic programs in luminal tumors are defined by FOXA1 super-enhancers•Basal tumors show repression of luminal factors and high epigenetic heterogeneity•Nuclear extracts or transcription factors can reprogram breast cancer cells
Luminal and basal-like breast tumors are clinically distinct. Using somatic cell fusions, Su et al. demonstrate the general dominance of the basal-like phenotype. Epigenomic profiling of parental luminal and basal-like cells and heterofusions define common luminal programs but a high degree of heterogeneity in basal-like cancer cells.
In mammals, numerous autosomal genes are subject to mitotically stable monoallelic expression (MAE), including genes that play critical roles in a variety of human diseases. Due to challenges posed ...by the clonal nature of MAE, very little is known about its regulation; in particular, no molecular features have been specifically linked to MAE. In this study, we report an approach that distinguishes MAE genes in human cells with great accuracy: a chromatin signature consisting of chromatin marks associated with active transcription (H3K36me3) and silencing (H3K27me3) simultaneously occurring in the gene body. The MAE signature is present in ∼20% of ubiquitously expressed genes and over 30% of tissue-specific genes across cell types. Notably, it is enriched among key developmental genes that have bivalent chromatin structure in pluripotent cells. Our results open a new approach to the study of MAE that is independent of polymorphisms, and suggest that MAE is linked to cell differentiation. DOI: http://dx.doi.org/10.7554/eLife.01256.001.
Single-cell RNA sequencing has recently emerged as a powerful tool for mapping cellular heterogeneity in diseased and healthy tissues, yet high-throughput methods are needed for capturing the ...unbiased diversity of cells. Droplet microfluidics is among the most promising candidates for capturing and processing thousands of individual cells for whole-transcriptome or genomic analysis in a massively parallel manner with minimal reagent use. We recently established a method called inDrops, which has the capability to index >15,000 cells in an hour. A suspension of cells is first encapsulated into nanoliter droplets with hydrogel beads (HBs) bearing barcoding DNA primers. Cells are then lysed and mRNA is barcoded (indexed) by a reverse transcription (RT) reaction. Here we provide details for (i) establishing an inDrops platform (1 d); (ii) performing hydrogel bead synthesis (4 d); (iii) encapsulating and barcoding cells (1 d); and (iv) RNA-seq library preparation (2 d). inDrops is a robust and scalable platform, and it is unique in its ability to capture and profile >75% of cells in even very small samples, on a scale of thousands or tens of thousands of cells.
Abstract
Summary
Single-cell RNA sequencing (scRNA-seq) has revolutionized the study of gene expression at the individual cell level, unraveling unprecedented insights into cellular heterogeneity. ...However, the analysis of scRNA-seq data remains a challenging and time-consuming task, often demanding advanced computational expertise, rendering it impractical for high-volume environments and applications. We present CellBridge, an automated workflow designed to simplify the standard procedures entailed in scRNA-seq data analysis, eliminating the need for specialized computational expertise. CellBridge utilizes state-of-the-art computational methods, integrating a range of advanced functionalities, covering the entire process from raw unaligned sequencing reads to cell type annotation. Hence, CellBridge accelerates the pace of discovery by seamlessly enabling insights into vast volumes of scRNA-seq data, without compromising workflow control and reproducibility.
Availability and implementation
The source code, detailed documentation, and materials required to reproduce the results are available on GitHub and archived in Zenodo. For the CellBridge pre-processing step (v1.0.0), access the GitHub repository at https://github.com/Sanofi-Public/PMCB-ToBridge and the Zenodo archive at https://zenodo.org/records/10246161. For the CellBridge processing step (v1.0.0), visit the GitHub repository at https://github.com/Sanofi-Public/PMCB-CellBridge and the Zenodo archive at https://zenodo.org/records/10246046.
There is a striking and unexplained male predominance across many cancer types. A subset of X-chromosome genes can escape X-inactivation, which would protect females from complete functional loss by ...a single mutation. To identify putative 'escape from X-inactivation tumor-suppressor' (EXITS) genes, we examined somatic alterations from >4,100 cancers across 21 tumor types for sex bias. Six of 783 non-pseudoautosomal region (PAR) X-chromosome genes (ATRX, CNKSR2, DDX3X, KDM5C, KDM6A, and MAGEC3) harbored loss-of-function mutations more frequently in males (based on a false discovery rate < 0.1), in comparison to zero of 18,055 autosomal and PAR genes (Fisher's exact P < 0.0001). Male-biased mutations in genes that escape X-inactivation were observed in combined analysis across many cancers and in several individual tumor types, suggesting a generalized phenomenon. We conclude that biallelic expression of EXITS genes in females explains a portion of the reduced cancer incidence in females as compared to males across a variety of tumor types.
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