April 2024
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9 Reads
Journal of Hepatology
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April 2024
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9 Reads
Journal of Hepatology
February 2024
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108 Reads
Spatial omics holds great potential to elucidate tissue architecture by dissecting underlying cell niches and cellular interactions. However, we lack an end-to-end computational framework that can effectively integrate different spatial omics tissue samples, quantitatively characterize cell niches based on biological knowledge of cell-cell communication and transcriptional regulation pathways, and discover spatial molecular programs of cells. We present NicheCompass, a graph deep learning method designed based on the principles of cellular communication. It utilizes existing knowledge of inter- and intracellular interaction pathways to learn an interpretable latent space of cells across multiple tissue samples, enabling the construction and querying of spatial reference atlases. NicheCompass learns the activity of an interaction pathway by modeling the process through the lens of cells receiving and processing signals from their tissue microenvironment, using a variety of mechanisms involving metabolic interactions, ligand-receptor interactions including downstream regulation, and regulons. In addition to leveraging existing knowledge, NicheCompass can learn novel spatially variable gene programs to model variation in the tissue. We showcase a comprehensive workflow encompassing data integration, niche identification, and functional interpretation, and demonstrate that NicheCompass outperforms existing approaches. NicheCompass is broadly applicable to spatial transcriptomics data, which we illustrate by mapping the architecture of diverse tissues during mouse embryonic development, and delineating basal (KRT14) and luminal (KRT8) tumor cell niches in human breast cancer. Moreover, we introduce fine-tuning-based spatial reference mapping, revealing an SPP1+ macrophage-dominated tumor microenvironment in non-small cell lung cancer patients. We further extend NicheCompass to multimodal spatial profiling of gene expression and chromatin accessibility, identifying distinct white matter niches in the mouse brain. Finally, we apply NicheCompass to a whole mouse brain spatial atlas with 8.4 million cells across 239 tissue sections from four mice, demonstrating its ability to build foundational, interpretable spatial representations for entire organs. Overall, NicheCompass provides a novel end-to-end workflow for analyzing large-scale spatial omics data.
November 2023
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6 Reads
Clinical Pharmacology & Therapeutics
External controls (eControls) leverage historical data to create non‐randomized control arms. The lack of randomization can result in confounding between the experimental and eControl cohorts. To balance potentially confounding variables between the cohorts, one of the proposed methods is to match on prognostic scores. Still, the performance of prognostic scores to construct eControls in oncology has not been analyzed yet. Using an electronic health record (EHR)‐derived de‐identified database, we constructed eControls using one of three methods: ROPRO, a state‐of‐the‐art prognostic score, or either a propensity score composed of five (5Vars) or 27 covariates (ROPROvars). We compared the performance of these methods in estimating the overall survival (OS) hazard ratio (HR) of 11 recent advanced non‐small‐cell lung cancer. The ROPRO eControls had a lower OS HR error (median absolute deviation [MAD] [confidence interval {CI}] 0.072 [0.036, 0.185]), than the 5Vars (MAD [CI] 0.081 [0.025, 0.283]) and ROPROvars eControls (MAD [CI] 0.087 [0.054, 0.383]). Notably, the OS HR errors for all methods were even lower in the phase III studies. Moreover, the ROPRO eControl cohorts included, on average, more patients than the 5Vars (6.54%) and ROPROvars cohorts (11.7%). eControls matched with the prognostic score reproduced the controls more reliably than propensity scores composed of the underlying variables. Additionally, prognostic scores could allow eControls to be built on many prognostic variables without a significant increase in the variability of the propensity score, which would decrease the number of matched patients.
February 2023
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204 Reads
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43 Citations
Nature Cell Biology
The increasing availability of large-scale single-cell atlases has enabled the detailed description of cell states. In parallel, advances in deep learning allow rapid analysis of newly generated query datasets by mapping them into reference atlases. However, existing data transformations learned to map query data are not easily explainable using biologically known concepts such as genes or pathways. Here we propose expiMap, a biologically informed deep-learning architecture that enables single-cell reference mapping. ExpiMap learns to map cells into biologically understandable components representing known ‘gene programs’. The activity of each cell for a gene program is learned while simultaneously refining them and learning de novo programs. We show that expiMap compares favourably to existing methods while bringing an additional layer of interpretability to integrative single-cell analysis. Furthermore, we demonstrate its applicability to analyse single-cell perturbation responses in different tissues and species and resolve responses of patients who have coronavirus disease 2019 to different treatments across cell types.
February 2023
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200 Reads
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2 Citations
A cell's function is defined by its intrinsic characteristics and its niche: the tissue microenvironment in which it dwells. Here, we combine single-cell and spatial transcriptomic data to discover cellular niches within eight regions of the human heart. We map cells to micro-anatomic locations and integrate knowledge-based and unsupervised structural annotations. For the first time, we profile the cells of the human cardiac conduction system, revealing their distinctive repertoire of ion channels, G-protein coupled receptors, and cell interactions using a custom CellPhoneDB.org module. We show that the sinoatrial node is compartmentalised, with a core of pacemaker cells, fibroblasts and glial cells supporting paracrine glutamatergic signalling. We introduce a druggable target prediction tool, drug2cell, which leverages single-cell profiles and drug-target interactions, providing unexpected mechanistic insights into the chronotropic effects of drugs, including GLP-1 analogues. In the epicardium, we show enrichment of both IgG+ and IgA+ plasma cells forming immune niches which may contribute to infection defence. We define a ventricular myocardial-stress niche enriched for activated fibroblasts and stressed cardiomyocytes, cell states that are expanded in cardiomyopathies. Overall, we provide new clarity to cardiac electro-anatomy and immunology, and our suite of computational approaches can be deployed to other tissues and organs.
December 2022
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13 Reads
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3 Citations
Journal of Visualized Experiments
December 2022
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3 Reads
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2 Citations
Journal of Visualized Experiments
March 2021
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415 Reads
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257 Citations
Nature Medicine
Angiotensin-converting enzyme 2 (ACE2) and accessory proteases (TMPRSS2 and CTSL) are needed for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) cellular entry, and their expression may shed light on viral tropism and impact across the body. We assessed the cell-type-specific expression of ACE2, TMPRSS2 and CTSL across 107 single-cell RNA-sequencing studies from different tissues. ACE2, TMPRSS2 and CTSL are coexpressed in specific subsets of respiratory epithelial cells in the nasal passages, airways and alveoli, and in cells from other organs associated with coronavirus disease 2019 (COVID-19) transmission or pathology. We performed a meta-analysis of 31 lung single-cell RNA-sequencing studies with 1,320,896 cells from 377 nasal, airway and lung parenchyma samples from 228 individuals. This revealed cell-type-specific associations of age, sex and smoking with expression levels of ACE2, TMPRSS2 and CTSL. Expression of entry factors increased with age and in males, including in airway secretory cells and alveolar type 2 cells. Expression programs shared by ACE2⁺TMPRSS2⁺ cells in nasal, lung and gut tissues included genes that may mediate viral entry, key immune functions and epithelial–macrophage cross-talk, such as genes involved in the interleukin-6, interleukin-1, tumor necrosis factor and complement pathways. Cell-type-specific expression patterns may contribute to the pathogenesis of COVID-19, and our work highlights putative molecular pathways for therapeutic intervention.
March 2021
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94 Reads
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126 Citations
Nature Medicine
Angiotensin-converting enzyme 2 (ACE2) and accessory proteases (TMPRSS2 and CTSL) are needed for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) cellular entry, and their expression may shed light on viral tropism and impact across the body. We assessed the cell-type-specific expression of ACE2, TMPRSS2 and CTSL across 107 single-cell RNA-sequencing studies from different tissues. ACE2, TMPRSS2 and CTSL are coexpressed in specific subsets of respiratory epithelial cells in the nasal passages, airways and alveoli, and in cells from other organs associated with coronavirus disease 2019 (COVID-19) transmission or pathology. We performed a meta-analysis of 31 lung single-cell RNA-sequencing studies with 1,320,896 cells from 377 nasal, airway and lung parenchyma samples from 228 individuals. This revealed cell-type-specific associations of age, sex and smoking with expression levels of ACE2, TMPRSS2 and CTSL. Expression of entry factors increased with age and in males, including in airway secretory cells and alveolar type 2 cells. Expression programs shared by ACE2+TMPRSS2+ cells in nasal, lung and gut tissues included genes that may mediate viral entry, key immune functions and epithelial–macrophage cross-talk, such as genes involved in the interleukin-6, interleukin-1, tumor necrosis factor and complement pathways. Cell-type-specific expression patterns may contribute to the pathogenesis of COVID-19, and our work highlights putative molecular pathways for therapeutic intervention.
March 2021
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161 Reads
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30 Citations
Nature Methods
... While there are studies that have been able to separate and study organelles other than the peroxisome from frozen samples, such as the nucleus [22] and mitochondria [23][24][25], little is known about the separation of the peroxisome from frozen samples, which may have discouraged researchers from experimenting on this important organelle. This led us to think about the possibility of separating the peroxisome from frozen rat liver samples, based on the research by Alvarez et al. [21] who were able to separate the peroxisome, but from frozen human biopsy of liver samples. ...
December 2022
Journal of Visualized Experiments
... The analysis was done on an updated version of CellPhoneDB-database (v4.1) which includes novel intercellular interactions from refs. 64,65 . Only bona fide manually curated interactions were considered in the analysis. ...
February 2023
... A similar insensitivity to supervising information applies to deep learning variants of unsupervised latent factor models, such as variational autoencoders 12 . While some variants do anchor the non-linear embedding to biological pathway information to enhance interpretability 13,14 , this latent space is still not extracted conditioning on a provided disease phenotype. Machine learning models whose estimation takes into account known disease status, but lack latent factor extraction, have been applied to snRNA-seq data 15 . ...
February 2023
Nature Cell Biology
... To overcome this limitation, stored frozen tissues can be used for single nuclear RNA sequencing (snRNA-seq), which may show less variation among investigators, but still needs proper optimization of nuclear preparation. 140,141 scRNA-seq is good for analyzing nonparenchymal cell populations, especially immune cell populations, but is not suitable for HSCs, LSECs, hepatocytes, and cholangiocytes. 142 In contrast, snRNA-seq has the advantage of analyzing HSCs, LSECs, hepatocytes, and cholangiocytes. ...
December 2022
Journal of Visualized Experiments
... In the acute phase, SARS-CoV-2 enters the central nervous system via haematogenous transmission or transport along the olfactory or vagus nerve 27 , the damage to which may lead to autonomic or cerebral dysregulation and brain hypoxia 28 . Additionally, the SARS-CoV-2-induced cytokine storm impairs the blood-brain barrier, allowing infected leukocytes to penetrate the central nervous system and triggering an apoptotic cascade and demyelination. ...
March 2021
Nature Medicine
... These include the integration of host cell molecular signatures with mucosa-associated microbial profiles, mapping of data sets to specific anatomical locations along the craniocaudal axis of the gut, and alignment of healthy gut-derived data sets with disease state and intestinal organoid models. With the rapid development of single-cell RNA-seq technology, numerous computational tools and pipelines have been developed to analyse single-cell data [42][43][44] . These include programmes and/or packages enabling pre-processing of data such as quality control checks, normalization and batch correction, sequence alignment, and detection and removal of cell doublets [45][46][47] . ...
Reference:
A Roadmap for the Human Gut Cell Atlas
March 2021
Nature Methods
... The lack of TMPRSS2 implies that placental cells may be protected from SARS-CoV-2 infection. However, blocking TMPRSS2 activity only partially inhibits SARS-CoV-2 infection 18 , suggesting a potential role for other proteases such as furin 52 and cathepsin L 18 in aiding viral transmission 53 ; both are expressed by placental cells [54][55][56] . ...
March 2021
Nature Medicine
... COVID-19 patients with positive faecal SARS-CoV-2 test resultshave reported gastrointestinal discomfort, indicating the virus's impact on intestinal cells.96 Furthermore, single-cell RNA sequencing analyses from samples of healthy individuals have revealed elevated expressions of ACE2 and TMPRSS2 in the intestinal epithelium following infection by SARS-CoV-2.97 These findings suggested that viruses may disrupt the intestinal barrier, triggering an immuneinflammatory response and exacerbating local inflammation. ...
April 2020
... For nuclei extraction, the tissue was homogenized using a GentleMACS dissociator (Miltenyi Biotec, Germany) applying the program for single-nuclei extraction 1a. The tissue was placed into a homogenization buffer containing 10% Triton X-100, as previously described [31]. Homogenized tissue was filtered through 70 µm and 40 µm Flowmi tip filters (Merck; Germany). ...
December 2020
Nature
... ACE2 and TMPRSS2 are expressed in human ocular tissues and in other species, including mice and pigs 33,34 . More specifically, ACE2 expression has been reported in human retinas 35,36 . Following infection of K18-hACE2 mice with ancestral virus, SARS-CoV-2 was detected in the eye globes 23 . ...
May 2020
Nature Medicine