Single-cell RNA sequencing (scRNA-seq) has enabled researchers to study gene expression at a cellular resolution. However, noise due to amplification and dropout may obstruct analyses, so scalable ...denoising methods for increasingly large but sparse scRNA-seq data are needed. We propose a deep count autoencoder network (DCA) to denoise scRNA-seq datasets. DCA takes the count distribution, overdispersion and sparsity of the data into account using a negative binomial noise model with or without zero-inflation, and nonlinear gene-gene dependencies are captured. Our method scales linearly with the number of cells and can, therefore, be applied to datasets of millions of cells. We demonstrate that DCA denoising improves a diverse set of typical scRNA-seq data analyses using simulated and real datasets. DCA outperforms existing methods for data imputation in quality and speed, enhancing biological discovery.
Human lungs enable efficient gas exchange and form an interface with the environment, which depends on mucosal immunity for protection against infectious agents. Tightly controlled interactions ...between structural and immune cells are required to maintain lung homeostasis. Here, we use single-cell transcriptomics to chart the cellular landscape of upper and lower airways and lung parenchyma in healthy lungs, and lower airways in asthmatic lungs. We report location-dependent airway epithelial cell states and a novel subset of tissue-resident memory T cells. In the lower airways of patients with asthma, mucous cell hyperplasia is shown to stem from a novel mucous ciliated cell state, as well as goblet cell hyperplasia. We report the presence of pathogenic effector type 2 helper T cells (T
2) in asthmatic lungs and find evidence for type 2 cytokines in maintaining the altered epithelial cell states. Unbiased analysis of cell-cell interactions identifies a shift from airway structural cell communication in healthy lungs to a T
2-dominated interactome in asthmatic lungs.
Aging promotes lung function decline and susceptibility to chronic lung diseases, which are the third leading cause of death worldwide. Here, we use single cell transcriptomics and mass ...spectrometry-based proteomics to quantify changes in cellular activity states across 30 cell types and chart the lung proteome of young and old mice. We show that aging leads to increased transcriptional noise, indicating deregulated epigenetic control. We observe cell type-specific effects of aging, uncovering increased cholesterol biosynthesis in type-2 pneumocytes and lipofibroblasts and altered relative frequency of airway epithelial cells as hallmarks of lung aging. Proteomic profiling reveals extracellular matrix remodeling in old mice, including increased collagen IV and XVI and decreased Fraser syndrome complex proteins and collagen XIV. Computational integration of the aging proteome with the single cell transcriptomes predicts the cellular source of regulated proteins and creates an unbiased reference map of the aging lung.
The cell type specific sequences of transcriptional programs during lung regeneration have remained elusive. Using time-series single cell RNA-seq of the bleomycin lung injury model, we resolved ...transcriptional dynamics for 28 cell types. Trajectory modeling together with lineage tracing revealed that airway and alveolar stem cells converge on a unique Krt8 + transitional stem cell state during alveolar regeneration. These cells have squamous morphology, feature p53 and NFkB activation and display transcriptional features of cellular senescence. The Krt8+ state appears in several independent models of lung injury and persists in human lung fibrosis, creating a distinct cell-cell communication network with mesenchyme and macrophages during repair. We generated a model of gene regulatory programs leading to Krt8+ transitional cells and their terminal differentiation to alveolar type-1 cells. We propose that in lung fibrosis, perturbed molecular checkpoints on the way to terminal differentiation can cause aberrant persistence of regenerative intermediate stem cell states.
Differential analysis of MS-data to identify biomarkers or to understand biology is a cornerstone in proteomics. DEqMS is a robust method for analysis of both labelled and label-free MS-data. The ...method takes into account the inherent dependence of protein variance on the number of PSMs or peptides used for quantification, thereby providing a more accurate variance estimation. Compared to current methods, DEqMS achieves better accuracy and statistical power in quantitative proteomics. The tool is available as user-friendly R package.
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Highlights
•DEqMS is a method for statistical analysis of quantitative MS-data.•Variance estimates based on the actual MS-data structure.•Improved statistical power and accuracy in protein differential analysis.•DEqMS is available as a user-friendly R package in Bioconductor.
Quantitative proteomics by mass spectrometry is widely used in biomarker research and basic biology research for investigation of phenotype level cellular events. Despite the wide application, the methodology for statistical analysis of differentially expressed proteins has not been unified. Various methods such as t test, linear model and mixed effect models are used to define changes in proteomics experiments. However, none of these methods consider the specific structure of MS-data. Choices between methods, often originally developed for other types of data, are based on compromises between features such as statistical power, general applicability and user friendliness. Furthermore, whether to include proteins identified with one peptide in statistical analysis of differential protein expression varies between studies. Here we present DEqMS, a robust statistical method developed specifically for differential protein expression analysis in mass spectrometry data. In all data sets investigated there is a clear dependence of variance on the number of PSMs or peptides used for protein quantification. DEqMS takes this feature into account when assessing differential protein expression. This allows for a more accurate data-dependent estimation of protein variance and inclusion of single peptide identifications without increasing false discoveries. The method was tested in several data sets including E. coli proteome spike-in data, using both label-free and TMT-labeled quantification. Compared with previous statistical methods used in quantitative proteomics, DEqMS showed consistently better accuracy in detecting altered protein levels compared with other statistical methods in both label-free and labeled quantitative proteomics data. DEqMS is available as an R package in Bioconductor.
Lung disease accounts for every sixth death globally. Profiling the molecular state of all lung cell types in health and disease is currently revolutionizing the identification of disease mechanisms ...and will aid the design of novel diagnostic and personalized therapeutic regimens. Recent progress in high-throughput techniques for single-cell genomic and transcriptomic analyses has opened up new possibilities to study individual cells within a tissue, classify these into cell types, and characterize variations in their molecular profiles as a function of genetics, environment, cell-cell interactions, developmental processes, aging, or disease. Integration of these cell state definitions with spatial information allows the in-depth molecular description of cellular neighborhoods and tissue microenvironments, including the tissue resident structural and immune cells, the tissue matrix, and the microbiome. The Human Cell Atlas consortium aims to characterize all cells in the healthy human body and has prioritized lung tissue as one of the flagship projects. Here, we present the rationale, the approach, and the expected impact of a Human Lung Cell Atlas.
Recent fate-mapping studies concluded that EMT is not required for metastasis of carcinomas. Here we challenge this conclusion by showing that these studies failed to account for possible crosstalk ...between EMT and non-EMT cells that promotes dissemination of non-EMT cells. In breast cancer models, EMT cells induce increased metastasis of weakly metastatic, non-EMT tumour cells in a paracrine manner, in part by non-cell autonomous activation of the GLI transcription factor. Treatment with GANT61, a GLI1/2 inhibitor, but not with IPI 926, a Smoothened inhibitor, blocks this effect and inhibits growth in PDX models. In human breast tumours, the EMT-transcription factors strongly correlate with activated Hedgehog/GLI signalling but not with the Hh ligands. Our findings indicate that EMT contributes to metastasis via non-cell autonomous effects that activate the Hh pathway. Although all Hh inhibitors may act against tumours with canonical Hh/GLI signalling, only GLI inhibitors would act against non-canonical EMT-induced GLI activation.
MYC (also known as c-MYC) overexpression or hyperactivation is one of the most common drivers of human cancer. Despite intensive study, the MYC oncogene remains recalcitrant to therapeutic ...inhibition. MYC is a transcription factor, and many of its pro-tumorigenic functions have been attributed to its ability to regulate gene expression programs. Notably, oncogenic MYC activation has also been shown to increase total RNA and protein production in many tissue and disease contexts. While such increases in RNA and protein production may endow cancer cells with pro-tumour hallmarks, this increase in synthesis may also generate new or heightened burden on MYC-driven cancer cells to process these macromolecules properly. Here we discover that the spliceosome is a new target of oncogenic stress in MYC-driven cancers. We identify BUD31 as a MYC-synthetic lethal gene in human mammary epithelial cells, and demonstrate that BUD31 is a component of the core spliceosome required for its assembly and catalytic activity. Core spliceosomal factors (such as SF3B1 and U2AF1) associated with BUD31 are also required to tolerate oncogenic MYC. Notably, MYC hyperactivation induces an increase in total precursor messenger RNA synthesis, suggesting an increased burden on the core spliceosome to process pre-mRNA. In contrast to normal cells, partial inhibition of the spliceosome in MYC-hyperactivated cells leads to global intron retention, widespread defects in pre-mRNA maturation, and deregulation of many essential cell processes. Notably, genetic or pharmacological inhibition of the spliceosome in vivo impairs survival, tumorigenicity and metastatic proclivity of MYC-dependent breast cancers. Collectively, these data suggest that oncogenic MYC confers a collateral stress on splicing, and that components of the spliceosome may be therapeutic entry points for aggressive MYC-driven cancers.
A cobalt-catalyzed photochemical synthesis of allylic trifluoromethanes from styrene derivatives using 2,2,2-trifluoroethyl iodide is described. The method complements existing approaches, providing ...an alternative bond construction strategy to access these compounds. The process may be conducted in continuous mode in a novel photochemical flow reactor, resulting in a notable productivity increase.
The intestinal epithelium can limit enteric pathogens by producing antiviral cytokines, such as IFNs. Type I IFN (IFN-α/β) and type III IFN (IFN-λ) function at the epithelial level, and their ...respective efficacies depend on the specific pathogen and site of infection. However, the roles of type I and type III IFN in restricting human enteric viruses are poorly characterized as a result of the difficulties in cultivating these viruses in vitro and directly obtaining control and infected small intestinal human tissue. We infected nontransformed human intestinal enteroid cultures frommultiple individuals with human rotavirus (HRV) and assessed the host epithelial response by using RNA-sequencing and functional assays. The dominant transcriptional pathway induced by HRV infection is a type III IFN-regulated response. Early after HRV infection, low levels of type III IFN protein activate IFN-stimulated genes. However, this endogenous response does not restrict HRV replication because replication-competent HRV antagonizes the type III IFN response at pre- and posttranscriptional levels. In contrast, exogenous IFN treatment restricts HRV replication, with type I IFN being more potent than type III IFN, suggesting that extraepithelial sources of type I IFN may be the critical IFN for limiting enteric virus replication in the human intestine.
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