Publications

Below is the list of papers that are part of the Human Cell Atlas.

These have been approved by the HCA Publication Committee (composed of HCA Organising Committee members). The HCA Publication Committee reviews submitted publications to check if they fit within HCA technical scope. This review by the HCA Publication Committee does not serve as peer review.

We encourage you to submit your paper for inclusion within the Human Cell Atlas publications, which can help your paper gain more visibility. Please see here for the Publication Review process.

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Peer reviewed

Cell type ontologies of the Human Cell Atlas

Massive single-cell profiling efforts have accelerated our discovery of the cellular composition of the human body while at the same time raising the need to formalize this new knowledge. Here, we discuss current efforts to harmonize and integrate different sources of annotations of cell types and states into a reference cell ontology. We illustrate with examples how a unified ontology can consolidate and advance our understanding of cell types across scientific communities and biological domains. In this Perspective, Teichmann and colleagues present ongoing efforts from consortia of the Human Cell Atlas to harmonize and integrate data sources into a reference cell ontology and the contributions of cell ontologies to discovery.

Osumi-Sutherland, David; Xu, Chuan; Keays, Maria; Levine, Adam P.; Kharchenko, Peter V.; Regev, Aviv; Lein, Ed; Teichmann, Sarah A.

Nature Cell Biology 2021;23;11

Peer reviewed
Networks
Heart, Immune, Kidney, Liver, Lung, Skin
Topics
Human Subjects, Healthy Donors

Anatomical structures, cell types and biomarkers of the Human Reference Atlas

The Human Reference Atlas (HRA) aims to map all of the cells of the human body to advance biomedical research and clinical practice. This Perspective presents collaborative work by members of 16 international consortia on two essential and interlinked parts of the HRA: (1) three-dimensional representations of anatomy that are linked to (2) tables that name and interlink major anatomical structures, cell types, plus biomarkers (ASCT+B). We discuss four examples that demonstrate the practical utility of the HRA. In this Perspective, Börner et al. discuss initiatives by 16 consortia to construct a Human Reference Atlas (HRA) comprising reference organs linked to tables that name major anatomical structures, cell types, plus biomarkers (ASCT+B) and present examples of HRA usage.

Börner, Katy; Teichmann, Sarah A.; Quardokus, Ellen M.; Gee, James C.; Browne, Kristen; Osumi-Sutherland, David; Herr, Bruce W.; Bueckle, Andreas; Paul, Hrishikesh; Haniffa, Muzlifah et al

Nature Cell Biology 2021;23;11

Peer reviewed
Topics
Computational Methods

DUBStepR is a scalable correlation-based feature selection method for accurately clustering single-cell data

Feature selection (marker gene selection) is widely believed to improve clustering accuracy, and is thus a key component of single cell clustering pipelines. Existing feature selection methods perform inconsistently across datasets, occasionally even resulting in poorer clustering accuracy than without feature selection. Moreover, existing methods ignore information contained in gene-gene correlations. Here, we introduce DUBStepR (Determining the Underlying Basis using Stepwise Regression), a feature selection algorithm that leverages gene-gene correlations with a novel measure of inhomogeneity in feature space, termed the Density Index (DI). Despite selecting a relatively small number of genes, DUBStepR substantially outperformed existing single-cell feature selection methods across diverse clustering benchmarks. Additionally, DUBStepR was the only method to robustly deconvolve T and NK heterogeneity by identifying disease-associated common and rare cell types and subtypes in PBMCs from rheumatoid arthritis patients. DUBStepR is scalable to over a million cells, and can be straightforwardly applied to other data types such as single-cell ATAC-seq. We propose DUBStepR as a general-purpose feature selection solution for accurately clustering single-cell data. Cell-type-specific genes are often strongly correlated in expression - an informative yet underexplored property of single-cell data. Here, the authors leverage gene expression correlations to develop DUBStepR, a feature selection method for accurately clustering single-cell data.

Ranjan, Bobby; Sun, Wenjie; Park, Jinyu; Mishra, Kunal; Schmidt, Florian; Xie, Ronald; Alipour, Fatemeh; Singhal, Vipul; Joanito, Ignasius; Honardoost, Mohammad Amin et al

Nature Communications 2021;12;1

Peer reviewed

Blood and immune development in human fetal bone marrow and Down syndrome

Haematopoiesis in the bone marrow (BM) maintains blood and immune cell production throughout postnatal life. Haematopoiesis first emerges in human BM at 11–12 weeks after conception1,2, yet almost nothing is known about how fetal BM (FBM) evolves to meet the highly specialized needs of the fetus and newborn. Here we detail the development of FBM, including stroma, using multi-omic assessment of mRNA and multiplexed protein epitope expression. We find that the full blood and immune cell repertoire is established in FBM in a short time window of 6–7 weeks early in the second trimester. FBM promotes rapid and extensive diversification of myeloid cells, with granulocytes, eosinophils and dendritic cell subsets emerging for the first time. The substantial expansion of B lymphocytes in FBM contrasts with fetal liver at the same gestational age. Haematopoietic progenitors from fetal liver, FBM and cord blood exhibit transcriptional and functional differences that contribute to tissue-specific identity and cellular diversification. Endothelial cell types form distinct vascular structures that we show are regionally compartmentalized within FBM. Finally, we reveal selective disruption of B lymphocyte, erythroid and myeloid development owing to a cell-intrinsic differentiation bias as well as extrinsic regulation through an altered microenvironment in Down syndrome (trisomy 21). A single-cell atlas of human fetal bone marrow in healthy fetuses and fetuses with Down syndrome provides insight into developmental haematopoiesis in humans and the transcription and functional differences that occur in Down syndrome.

Jardine, Laura; Webb, Simone; Goh, Issac; Quiroga Londoño, Mariana; Reynolds, Gary; Mather, Michael; Olabi, Bayanne; Stephenson, Emily; Botting, Rachel A.; Horsfall, Dave et al

Nature 2021

Press release

Peer reviewed
Topics
Human Subjects, Healthy Donors, Disease Donors, Open Access Data

Cells of the human intestinal tract mapped across space and time

The cellular landscape of the human intestinal tract is dynamic throughout life, developing in utero and changing in response to functional requirements and environmental exposures. Here, to comprehensively map cell lineages, we use single-cell RNA sequencing and antigen receptor analysis of almost half a million cells from up to 5 anatomical regions in the developing and up to 11 distinct anatomical regions in the healthy paediatric and adult human gut. This reveals the existence of transcriptionally distinct BEST4 epithelial cells throughout the human intestinal tract. Furthermore, we implicate IgG sensing as a function of intestinal tuft cells. We describe neural cell populations in the developing enteric nervous system, and predict cell-type-specific expression of genes associated with Hirschsprung’s disease. Finally, using a systems approach, we identify key cell players that drive the formation of secondary lymphoid tissue in early human development. We show that these programs are adopted in inflammatory bowel disease to recruit and retain immune cells at the site of inflammation. This catalogue of intestinal cells will provide new insights into cellular programs in development, homeostasis and disease. Cells from embryonic, fetal, paediatric and adult human intestinal tissue are analysed at different locations along the intestinal tract to construct a single-cell atlas of the developing and adult human intestinal tract, encompassing all cell lineages.

Elmentaite, Rasa; Kumasaka, Natsuhiko; Roberts, Kenny; Fleming, Aaron; Dann, Emma; King, Hamish W.; Kleshchevnikov, Vitalii; Dabrowska, Monika; Pritchard, Sophie; Bolt, Liam et al

Nature 2021;597;7875;250-255

Press release

Peer reviewed
Networks
Development

A roadmap for the Human Developmental Cell Atlas

The Human Developmental Cell Atlas (HDCA) initiative, which is part of the Human Cell Atlas, aims to create a comprehensive reference map of cells during development. This will be critical to understanding normal organogenesis, the effect of mutations, environmental factors and infectious agents on human development, congenital and childhood disorders, and the cellular basis of ageing, cancer and regenerative medicine. Here we outline the HDCA initiative and the challenges of mapping and modelling human development using state-of-the-art technologies to create a reference atlas across gestation. Similar to the Human Genome Project, the HDCA will integrate the output from a growing community of scientists who are mapping human development into a unified atlas. We describe the early milestones that have been achieved and the use of human stem-cell-derived cultures, organoids and animal models to inform the HDCA, especially for prenatal tissues that are hard to acquire. Finally, we provide a roadmap towards a complete atlas of human development. This Perspective outlines the Human Developmental Cell Atlas initiative, which uses state-of-the-art technologies to map and model human development across gestation, and discusses the early milestones that have been achieved.

Haniffa, Muzlifah; Taylor, Deanne; Linnarsson, Sten; Aronow, Bruce J.; Bader, Gary D.; Barker, Roger A.; Camara, Pablo G.; Camp, J. Gray; Chédotal, Alain; Copp, Andrew et al

Nature 2021;597;7875;196-205

Press release

Peer reviewed

RCA2: a scalable supervised clustering algorithm that reduces batch effects in scRNA-seq data.

The transcriptomic diversity of cell types in the human body can be analysed in unprecedented detail using single cell (SC) technologies. Unsupervised clustering of SC transcriptomes, which is the default technique for defining cell types, is prone to group cells by technical, rather than biological, variation. Compared to de-novo (unsupervised) clustering, we demonstrate using multiple benchmarks that supervised clustering, which uses reference transcriptomes as a guide, is robust to batch effects and data quality artifacts. Here, we present RCA2, the first algorithm to combine reference projection (batch effect robustness) with graph-based clustering (scalability). In addition, RCA2 provides a user-friendly framework incorporating multiple commonly used downstream analysis modules. RCA2 also provides new reference panels for human and mouse and supports generation of custom panels. Furthermore, RCA2 facilitates cell type-specific QC, which is essential for accurate clustering of data from heterogeneous tissues. We demonstrate the advantages of RCA2 on SC data from human bone marrow, healthy PBMCs and PBMCs from COVID-19 patients. Scalable supervised clustering methods such as RCA2 will facilitate unified analysis of cohort-scale SC datasets.

Schmidt F; Ranjan B; Lin QXX; Krishnan V; Joanito I; Honardoost MA; Nawaz Z; Venkatesh PN; Tan J; Rayan NA et al

Nucleic acids research 2021;49;15;8505-8519

Peer reviewed
Topics
Human Subjects, Healthy Donors, Disease Donors

Pre-activated antiviral innate immunity in the upper airways controls early SARS-CoV-2 infection in children

Children have reduced severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection rates and a substantially lower risk for developing severe coronavirus disease 2019 compared with adults. However, the molecular mechanisms underlying protection in younger age groups remain unknown. Here we characterize the single-cell transcriptional landscape in the upper airways of SARS-CoV-2-negative (n = 18) and age-matched SARS-CoV-2-positive (n = 24) children and corresponding samples from adults (n = 44), covering an age range of 4 weeks to 77 years. Children displayed higher basal expression of relevant pattern recognition receptors such as MDA5 (IFIH1) and RIG-I (DDX58) in upper airway epithelial cells, macrophages and dendritic cells, resulting in stronger innate antiviral responses upon SARS-CoV-2 infection than in adults. We further detected distinct immune cell subpopulations including KLRC1 (NKG2A)+ cytotoxic T cells and a CD8+ T cell population with a memory phenotype occurring predominantly in children. Our study provides evidence that the airway immune cells of children are primed for virus sensing, resulting in a stronger early innate antiviral response to SARS-CoV-2 infection than in adults. Single-cell sequencing reveals pre-activated immunity as important for milder COVID-19 symptoms in children.

Loske, J.; Röhmel, J.; Lukassen, S.; Stricker, S.; Magalhães, V. G.; Liebig, J.; Chua, R. L.; Thürmann, L.; Messingschlager, M.; Seegebarth, A. et al

Nature Biotechnology 2021

Topics
Human Subjects, Healthy Donors, Open Access Data

Spatial and cell type transcriptional landscape of human cerebellar development.

The human neonatal cerebellum is one-fourth of its adult size yet contains the blueprint required to integrate environmental cues with developing motor, cognitive and emotional skills into adulthood. Although mature cerebellar neuroanatomy is well studied, understanding of its developmental origins is limited. In this study, we systematically mapped the molecular, cellular and spatial composition of human fetal cerebellum by combining laser capture microscopy and SPLiT-seq single-nucleus transcriptomics. We profiled functionally distinct regions and gene expression dynamics within cell types and across development. The resulting cell atlas demonstrates that the molecular organization of the cerebellar anlage recapitulates cytoarchitecturally distinct regions and developmentally transient cell types that are distinct from the mouse cerebellum. By mapping genes dominant for pediatric and adult neurological disorders onto our dataset, we identify relevant cell types underlying disease mechanisms. These data provide a resource for probing the cellular basis of human cerebellar development and disease.

Aldinger KA; Thomson Z; Phelps IG; Haldipur P; Deng M; Timms AE; Hirano M; Santpere G; Roco C; Rosenberg AB et al

 2021;24;8

Pre-print
Topics
Human Subjects, Healthy Donors, Open Access Data, Experimental Methods, Computational Methods

Single-nucleus cross-tissue molecular reference maps to decipher disease gene function

bioRxiv - the preprint server for biology, operated by Cold Spring Harbor Laboratory, a research and educational institution

Gokcen Eraslan; Eugene Drokhlyansky; Shankara Anand; Ayshwarya Subramanian; Evgenij Fiskin; Michal Slyper; Jiali Wang; Nicholas Van Wittenberghe; John M. Rouhana; Julia Waldman et al

bioRxiv 2021;2021.07.19.452954

Peer reviewed
Networks
Lung
Topics
Healthy Donors, Disease Donors

Chronic lung diseases are associated with gene expression programs favoring SARS-CoV-2 entry and severity.

Patients with chronic lung disease (CLD) have an increased risk for severe coronavirus disease-19 (COVID-19) and poor outcomes. Here, we analyze the transcriptomes of 611,398 single cells isolated from healthy and CLD lungs to identify molecular characteristics of lung cells that may account for worse COVID-19 outcomes in patients with chronic lung diseases. We observe a similar cellular distribution and relative expression of SARS-CoV-2 entry factors in control and CLD lungs. CLD AT2 cells express higher levels of genes linked directly to the efficiency of viral replication and the innate immune response. Additionally, we identify basal differences in inflammatory gene expression programs that highlight how CLD alters the inflammatory microenvironment encountered upon viral exposure to the peripheral lung. Our study indicates that CLD is accompanied by changes in cell-type-specific gene expression programs that prime the lung epithelium for and influence the innate and adaptive immune responses to SARS-CoV-2 infection.

Bui LT; Winters NI; Chung MI; Joseph C; Gutierrez AJ; Habermann AC; Adams TS; Schupp JC; Poli S; Peter LM et al

Nature Communications 2021;12;1;4314

Topics
Human Subjects, Healthy Donors, Disease Donors, Open Access Data, Experimental Methods

A single cell atlas of human cornea that defines its development, limbal progenitor cells and their interactions with the immune cells.

Single cell (sc) analyses of key embryonic, fetal and adult stages were performed to generate a comprehensive single cell atlas of all the corneal and adjacent conjunctival cell types from development to adulthood.

Collin J; Queen R; Zerti D; Bojic S; Dorgau B; Moyse N; Molina MM; Yang C; Dey S; Reynolds G et al

 2021;21

Peer reviewed

Towards a Human Cell Atlas: Taking Notes from the Past.

Comprehensively characterizing the cellular composition and organization of tissues has been a long-term scientific challenge that has limited our ability to study fundamental and clinical aspects of human physiology. The Human Cell Atlas (HCA) is a global collaborative effort to create a reference map of all human cells as a basis for both understanding human health and diagnosing, monitoring, and treating disease. Many aspects of the HCA are analogous to the Human Genome Project (HGP), whose completion presents a major milestone in modern biology. To commemorate the HGP's 20-year anniversary of completion, we discuss the launch of the HCA in light of the HGP, and highlight recent progress by the HCA consortium.

Lindeboom RGH; Regev A; Teichmann SA

Trends in genetics 2021;37;7;625-630

Peer reviewed
Topics
Model Organism Samples, Healthy Donors, Computational Methods

Cell segmentation-free inference of cell types from in situ transcriptomics data.

Multiplexed fluorescence in situ hybridization techniques have enabled cell-type identification, linking transcriptional heterogeneity with spatial heterogeneity of cells. However, inaccurate cell segmentation reduces the efficacy of cell-type identification and tissue characterization. Here, we present a method called Spot-based Spatial cell-type Analysis by Multidimensional mRNA density estimation (SSAM), a robust cell segmentation-free computational framework for identifying cell-types and tissue domains in 2D and 3D. SSAM is applicable to a variety of in situ transcriptomics techniques and capable of integrating prior knowledge of cell types. We apply SSAM to three mouse brain tissue images: the somatosensory cortex imaged by osmFISH, the hypothalamic preoptic region by MERFISH, and the visual cortex by multiplexed smFISH. Here, we show that SSAM detects regions occupied by known cell types that were previously missed and discovers new cell types.

Park J; Choi W; Tiesmeyer S; Long B; Borm LE; Garren E; Nguyen TN; Tasic B; Codeluppi S; Graf T et al

Nature Communications 2021;12;1;3545

Peer reviewed
Topics
Computational Methods

Tutorial: guidelines for annotating single-cell transcriptomic maps using automated and manual methods

Single-cell transcriptomics can profile thousands of cells in a single experiment and identify novel cell types, states and dynamics in a wide variety of tissues and organisms. Standard experimental protocols and analysis workflows have been developed to create single-cell transcriptomic maps from tissues. This tutorial focuses on how to interpret these data to identify cell types, states and other biologically relevant patterns with the objective of creating an annotated map of cells. We recommend a three-step workflow including automatic cell annotation (wherever possible), manual cell annotation and verification. Frequently encountered challenges are discussed, as well as strategies to address them. Guiding principles and specific recommendations for software tools and resources that can be used for each step are covered, and an R notebook is included to help run the recommended workflow. Basic familiarity with computer software is assumed, and basic knowledge of programming (e.g., in the R language) is recommended. This tutorial provides guidelines for interpreting single-cell transcriptomic maps to identify cell types, states and other biologically relevant patterns.

Clarke, Zoe A.; Andrews, Tallulah S.; Atif, Jawairia; Pouyabahar, Delaram; Innes, Brendan T.; MacParland, Sonya A.; Bader, Gary D.

Nature Protocols 2021;16;6;2749-2764

Topics
Computational Methods

Deep generative model embedding of single-cell RNA-Seq profiles on hyperspheres and hyperbolic spaces.

Single-cell RNA-Seq (scRNA-seq) is invaluable for studying biological systems. Dimensionality reduction is a crucial step in interpreting the relation between cells in scRNA-seq data. However, current dimensionality reduction methods are often confounded by multiple simultaneous technical and biological variability, result in "crowding" of cells in the center of the latent space, or inadequately capture temporal relationships. Here, we introduce scPhere, a scalable deep generative model to embed cells into low-dimensional hyperspherical or hyperbolic spaces to accurately represent scRNA-seq data. ScPhere addresses multi-level, complex batch factors, facilitates the interactive visualization of large datasets, resolves cell crowding, and uncovers temporal trajectories. We demonstrate scPhere on nine large datasets in complex tissue from human patients or animal development. Our results show how scPhere facilitates the interpretation of scRNA-seq data by generating batch-invariant embeddings to map data from new individuals, identifies cell types affected by biological variables, infers cells' spatial positions in pre-defined biological specimens, and highlights complex cellular relations.

Ding J; Regev A

 2021;12;1

Peer reviewed
Topics
COVID-19

Single-cell multi-omics analysis of the immune response in COVID-19.

Analysis of human blood immune cells provides insights into the coordinated response to viral infections such as severe acute respiratory syndrome coronavirus 2, which causes coronavirus disease 2019 (COVID-19). We performed single-cell transcriptome, surface proteome and T and B lymphocyte antigen receptor analyses of over 780,000 peripheral blood mononuclear cells from a cross-sectional cohort of 130 patients with varying severities of COVID-19. We identified expansion of nonclassical monocytes expressing complement transcripts (CD16C1QA/B/C) that sequester platelets and were predicted to replenish the alveolar macrophage pool in COVID-19. Early, uncommitted CD34 hematopoietic stem/progenitor cells were primed toward megakaryopoiesis, accompanied by expanded megakaryocyte-committed progenitors and increased platelet activation. Clonally expanded CD8 T cells and an increased ratio of CD8 effector T cells to effector memory T cells characterized severe disease, while circulating follicular helper T cells accompanied mild disease. We observed a relative loss of IgA2 in symptomatic disease despite an overall expansion of plasmablasts and plasma cells. Our study highlights the coordinated immune response that contributes to COVID-19 pathogenesis and reveals discrete cellular components that can be targeted for therapy.

Stephenson E; Reynolds G; Botting RA; Calero-Nieto FJ; Morgan MD; Tuong ZK; Bach K; Sungnak W; Worlock KB; Yoshida M et al

Nature Medicine 2021;27;5;904-916

Peer reviewed
Topics
COVID-19

SARS-CoV-2 infection of the oral cavity and saliva.

Despite signs of infection-including taste loss, dry mouth and mucosal lesions such as ulcerations, enanthema and macules-the involvement of the oral cavity in coronavirus disease 2019 (COVID-19) is poorly understood. To address this, we generated and analyzed two single-cell RNA sequencing datasets of the human minor salivary glands and gingiva (9 samples, 13,824 cells), identifying 50 cell clusters. Using integrated cell normalization and annotation, we classified 34 unique cell subpopulations between glands and gingiva. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) viral entry factors such as ACE2 and TMPRSS members were broadly enriched in epithelial cells of the glands and oral mucosae. Using orthogonal RNA and protein expression assessments, we confirmed SARS-CoV-2 infection in the glands and mucosae. Saliva from SARS-CoV-2-infected individuals harbored epithelial cells exhibiting ACE2 and TMPRSS expression and sustained SARS-CoV-2 infection. Acellular and cellular salivary fractions from asymptomatic individuals were found to transmit SARS-CoV-2 ex vivo. Matched nasopharyngeal and saliva samples displayed distinct viral shedding dynamics, and salivary viral burden correlated with COVID-19 symptoms, including taste loss. Upon recovery, this asymptomatic cohort exhibited sustained salivary IgG antibodies against SARS-CoV-2. Collectively, these data show that the oral cavity is an important site for SARS-CoV-2 infection and implicate saliva as a potential route of SARS-CoV-2 transmission.

Huang N; Pérez P; Kato T; Mikami Y; Okuda K; Gilmore RC; Conde CD; Gasmi B; Stein S; Beach M et al

Nature Medicine 2021;27;5;892-903

Peer reviewed

A molecular single-cell lung atlas of lethal COVID-19

Respiratory failure is the leading cause of death in patients with severe SARS-CoV-2 infection1,2, but the host response at the lung tissue level is poorly understood. Here we performed single-nucleus RNA sequencing of about 116,000 nuclei from the lungs of nineteen individuals who died of COVID-19 and underwent rapid autopsy and seven control individuals. Integrated analyses identified substantial alterations in cellular composition, transcriptional cell states, and cell-to-cell interactions, thereby providing insight into the biology of lethal COVID-19. The lungs from individuals with COVID-19 were highly inflamed, with dense infiltration of aberrantly activated monocyte-derived macrophages and alveolar macrophages, but had impaired T cell responses. Monocyte/macrophage-derived interleukin-1β and epithelial cell-derived interleukin-6 were unique features of SARS-CoV-2 infection compared to other viral and bacterial causes of pneumonia. Alveolar type 2 cells adopted an inflammation-associated transient progenitor cell state and failed to undergo full transition into alveolar type 1 cells, resulting in impaired lung regeneration. Furthermore, we identified expansion of recently described CTHRC1+ pathological fibroblasts3 contributing to rapidly ensuing pulmonary fibrosis in COVID-19. Inference of protein activity and ligand–receptor interactions identified putative drug targets to disrupt deleterious circuits. This atlas enables the dissection of lethal COVID-19, may inform our understanding of long-term complications of COVID-19 survivors, and provides an important resource for therapeutic development. Lung samples collected soon after death from COVID-19 are used to provide a single-cell atlas of SARS-CoV-2 infection and the ensuing molecular changes.

Melms, Johannes C.; Biermann, Jana; Huang, Huachao; Wang, Yiping; Nair, Ajay; Tagore, Somnath; Katsyv, Igor; Rendeiro, André F.; Amin, Amit Dipak; Schapiro, Denis et al

Nature 2021;595;7865;114-119

Peer reviewed
Topics
Human Subjects, Disease Donors, Experimental Methods, Computational Methods, COVID-19

COVID-19 tissue atlases reveal SARS-CoV-2 pathology and cellular targets

COVID-19, which is caused by SARS-CoV-2, can result in acute respiratory distress syndrome and multiple organ failure1–4, but little is known about its pathophysiology. Here we generated single-cell atlases of 24 lung, 16 kidney, 16 liver and 19 heart autopsy tissue samples and spatial atlases of 14 lung samples from donors who died of COVID-19. Integrated computational analysis uncovered substantial remodelling in the lung epithelial, immune and stromal compartments, with evidence of multiple paths of failed tissue regeneration, including defective alveolar type 2 differentiation and expansion of fibroblasts and putative TP63+ intrapulmonary basal-like progenitor cells. Viral RNAs were enriched in mononuclear phagocytic and endothelial lung cells, which induced specific host programs. Spatial analysis in lung distinguished inflammatory host responses in lung regions with and without viral RNA. Analysis of the other tissue atlases showed transcriptional alterations in multiple cell types in heart tissue from donors with COVID-19, and mapped cell types and genes implicated with disease severity based on COVID-19 genome-wide association studies. Our foundational dataset elucidates the biological effect of severe SARS-CoV-2 infection across the body, a key step towards new treatments. Single-cell analysis of lung, heart, kidney and liver autopsy samples shows the molecular and cellular changes and immune response resulting from severe COVID-19 infection.

Delorey, Toni M.; Ziegler, Carly G. K.; Heimberg, Graham; Normand, Rachelly; Yang, Yiming; Segerstolpe, Åsa; Abbondanza, Domenic; Fleming, Stephen J.; Subramanian, Ayshwarya; Montoro, Daniel T. et al

Nature 2021;595;7865;107-113

Pre-print
Topics
Human Subjects, Healthy Donors, Open Access Data, Computational Methods

Profiling of transcribed cis-regulatory elements in single cells

bioRxiv - the preprint server for biology, operated by Cold Spring Harbor Laboratory, a research and educational institution

Jonathan Moody; Tsukasa Kouno; Akari Suzuki; Youtaro Shibayama; Chikashi Terao; Jen-Chien Chang; Fernando López-Redondo; Chi Wai Yip; Jessica Severin; Hiroyuki Suetsugu et al

bioRxiv 2021;2021.04.04.438388

Pre-print
Topics
Human Subjects, Healthy Donors

The local and systemic response to SARS-CoV-2 infection in children and adults

medRxiv - The Preprint Server for Health Sciences

Masahiro Yoshida; Kaylee B. Worlock; Ni Huang; Rik G.H. Lindeboom; Colin R. Butler; Natsuhiko Kumasaka; Cecilia Dominguez Conde; Lira Mamanova; Liam Bolt; Laura Richardson et al

medRxiv 2021;2021.03.09.21253012

Peer reviewed
Networks
Musculoskeletal
Topics
Healthy Donors, Open Access Data, Experimental Methods, Computational Methods

Mapping the musculoskeletal system one cell at a time

The Human Cell Atlas (HCA) project aims to map tissues and organs during development, maturation and pathology at single cell resolution. The musculoskeletal HCA network is a community for fostering collaboration and shared expertise to help develop the therapeutic approaches needed to address the high global burden of musculoskeletal disorders.

Baldwin, Mathew J.; Cribbs, Adam P.; Guilak, Farshid; Snelling, Sarah J. B.

Nature Reviews Rheumatology 2021;17;5;247-248

Peer reviewed
Topics
Human Subjects, Healthy Donors, Disease Donors, Open Access Data, Experimental Methods, Computational Methods, COVID-19

Shotgun transcriptome, spatial omics, and isothermal profiling of SARS-CoV-2 infection reveals unique host responses, viral diversification, and drug interactions.

In less than nine months, the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) killed over a million people, including >25,000 in New York City (NYC) alone. The COVID-19 pandemic caused by SARS-CoV-2 highlights clinical needs to detect infection, track strain evolution, and identify biomarkers of disease course. To address these challenges, we designed a fast (30-minute) colorimetric test (LAMP) for SARS-CoV-2 infection from naso/oropharyngeal swabs and a large-scale shotgun metatranscriptomics platform (total-RNA-seq) for host, viral, and microbial profiling. We applied these methods to clinical specimens gathered from 669 patients in New York City during the first two months of the outbreak, yielding a broad molecular portrait of the emerging COVID-19 disease. We find significant enrichment of a NYC-distinctive clade of the virus (20C), as well as host responses in interferon, ACE, hematological, and olfaction pathways. In addition, we use 50,821 patient records to find that renin-angiotensin-aldosterone system inhibitors have a protective effect for severe COVID-19 outcomes, unlike similar drugs. Finally, spatial transcriptomic data from COVID-19 patient autopsy tissues reveal distinct ACE2 expression loci, with macrophage and neutrophil infiltration in the lungs. These findings can inform public health and may help develop and drive SARS-CoV-2 diagnostic, prevention, and treatment strategies.

Butler D; Mozsary C; Meydan C; Foox J; Rosiene J; Shaiber A; Danko D; Afshinnekoo E; MacKay M; Sedlazeck FJ et al

Nature Communications 2021;12;1;1660

Peer reviewed
Networks
Lung
Topics
COVID-19

Single-cell meta-analysis of SARS-CoV-2 entry genes across tissues and demographics

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. An integrated analysis of over 100 single-cell and single-nucleus transcriptomics studies illustrates severe acute respiratory syndrome coronavirus 2 viral entry gene coexpression patterns across different human tissues, and shows association of age, smoking status and sex with viral entry gene expression in respiratory cell populations.

Muus, Christoph; Luecken, Malte D.; Eraslan, Gökcen; Sikkema, Lisa; Waghray, Avinash; Heimberg, Graham; Kobayashi, Yoshihiko; Vaishnav, Eeshit Dhaval; Subramanian, Ayshwarya; Smillie, Christopher et al

Nature Medicine 2021;27;3;546-559

Peer reviewed
Topics
Human Subjects, Healthy Donors

Single-Nucleus and In Situ RNA-Sequencing Reveal Cell Topographies in the Human Pancreas.

Molecular evidence of cellular heterogeneity in the human exocrine pancreas has not been yet established because of the local concentration and cascade of hydrolytic enzymes that can rapidly degrade cells and RNA upon pancreatic resection. We sought to better understand the heterogeneity and cellular composition of the pancreas in neonates and adults in healthy and diseased conditions using single-cell sequencing approaches.

Tosti L; Hang Y; Debnath O; Tiesmeyer S; Trefzer T; Steiger K; Ten FW; Lukassen S; Ballke S; Kühl AA et al

Gastroenterology 2021;160;4;1330-1344.e11

Peer reviewed
Topics
Human Subjects, Open Access Data

Spatiotemporal analysis of human intestinal development at single-cell resolution.

Development of the human intestine is not well understood. Here, we link single-cell RNA sequencing and spatial transcriptomics to characterize intestinal morphogenesis through time. We identify 101 cell states including epithelial and mesenchymal progenitor populations and programs linked to key morphogenetic milestones. We describe principles of crypt-villus axis formation; neural, vascular, mesenchymal morphogenesis, and immune population of the developing gut. We identify the differentiation hierarchies of developing fibroblast and myofibroblast subtypes and describe diverse functions for these including as vascular niche cells. We pinpoint the origins of Peyer's patches and gut-associated lymphoid tissue (GALT) and describe location-specific immune programs. We use our resource to present an unbiased analysis of morphogen gradients that direct sequential waves of cellular differentiation and define cells and locations linked to rare developmental intestinal disorders. We compile a publicly available online resource, spatio-temporal analysis resource of fetal intestinal development (STAR-FINDer), to facilitate further work.

Fawkner-Corbett D; Antanaviciute A; Parikh K; Jagielowicz M; Gerós AS; Gupta T; Ashley N; Khamis D; Fowler D; Morrissey E et al

Cell 2021;184;3;810-826.e23

Peer reviewed
Topics
Human Subjects, Healthy Donors, Disease Donors, Experimental Methods

Building a high-quality Human Cell Atlas

Rozenblatt-Rosen, Orit; Shin, Jay W.; Rood, Jennifer E.; Hupalowska, Anna; Regev, Aviv; Heyn, Holger

Nature Biotechnology 2021;39;2;149-153

Peer reviewed
Topics
Human Subjects, Healthy Donors, Disease Donors, Open Access Data, Experimental Methods

Developmental cell programs are co-opted in inflammatory skin disease.

The skin confers biophysical and immunological protection through a complex cellular network established early in embryonic development. We profiled the transcriptomes of more than 500,000 single cells from developing human fetal skin, healthy adult skin, and adult skin with atopic dermatitis and psoriasis. We leveraged these datasets to compare cell states across development, homeostasis, and disease. Our analysis revealed an enrichment of innate immune cells in skin during the first trimester and clonal expansion of disease-associated lymphocytes in atopic dermatitis and psoriasis. We uncovered and validated in situ a reemergence of prenatal vascular endothelial cell and macrophage cellular programs in atopic dermatitis and psoriasis lesional skin. These data illustrate the dynamism of cutaneous immunity and provide opportunities for targeting pathological developmental programs in inflammatory skin diseases.

Reynolds G; Vegh P; Fletcher J; Poyner EFM; Stephenson E; Goh I; Botting RA; Huang N; Olabi B; Dubois A et al

Science 2021;371;6527

Pre-print
Topics
Human Subjects, Healthy Donors, Open Access Data

Mapping the temporal and spatial dynamics of the human endometrium in vivo and in vitro

bioRxiv - the preprint server for biology, operated by Cold Spring Harbor Laboratory, a research and educational institution

Luz Garcia-Alonso; Louis-François Handfield; Kenny Roberts; Konstantina Nikolakopoulou; Ridma C. Fernando; Lucy Gardner; Ben Woodhams; Anna Arutyunyan; Krzysztof Polanski; Regina Hoo et al

bioRxiv 2021;2021.01.02.425073

Peer reviewed
Networks
Organoid
Topics
Human Subjects, Model Organism Samples, Healthy Donors, Disease Donors, Open Access Data, Experimental Methods, Computational Methods

The Organoid Cell Atlas.

Bock C; Boutros M; Camp JG; Clarke L; Clevers H; Knoblich JA; Liberali P; Regev A; Rios AC; Stegle O et al

Nature Biotechnology 2021;39;1;13-17

Topics
Human Subjects, Healthy Donors, Disease Donors

Human oral mucosa cell atlas reveals a stromal-neutrophil axis regulating tissue immunity.

The oral mucosa remains an understudied barrier tissue. This is a site of rich exposure to antigens and commensals, and a tissue susceptible to one of the most prevalent human inflammatory diseases, periodontitis. To aid in understanding tissue-specific pathophysiology, we compile a single-cell transcriptome atlas of human oral mucosa in healthy individuals and patients with periodontitis. We uncover the complex cellular landscape of oral mucosal tissues and identify epithelial and stromal cell populations with inflammatory signatures that promote antimicrobial defenses and neutrophil recruitment. Our findings link exaggerated stromal cell responsiveness with enhanced neutrophil and leukocyte infiltration in periodontitis. Our work provides a resource characterizing the role of tissue stroma in regulating mucosal tissue homeostasis and disease pathogenesis.

Williams DW; Greenwell-Wild T; Brenchley L; Dutzan N; Overmiller A; Sawaya AP; Webb S; Martin D; ; Hajishengallis G et al

 2021;184;15

Networks
Development, Lung
Topics
Human Subjects, Healthy Donors, Disease Donors, Open Access Data, Computational Methods

Implicating Gene and Cell Networks Responsible for Differential COVID-19 Host Responses via an Interactive Single Cell Web Portal.

Numerous studies have provided single-cell transcriptome profiles of host responses to SARS-CoV-2 infection. Critically lacking however is a datamine that allows users to compare and explore cell profiles to gain insights and develop new hypotheses. To accomplish this, we harmonized datasets from COVID-19 and other control condition blood, bronchoalveolar lavage, and tissue samples, and derived a compendium of gene signature modules per cell type, subtype, clinical condition, and compartment. We demonstrate approaches to probe these via a new interactive web portal (http://toppcell.cchmc.org/COVID-19). As examples, we develop three hypotheses: (1) a multicellular signaling cascade among alternatively differentiated monocyte-derived macrophages whose tasks include T cell recruitment and activation; (2) novel platelet subtypes with drastically modulated expression of genes responsible for adhesion, coagulation and thrombosis; and (3) a multilineage cell activator network able to drive extrafollicular B maturation via an ensemble of genes strongly associated with risk for developing post-viral autoimmunity.

Jin K; Bardes EE; Mitelpunkt A; Wang JY; Bhatnagar S; Sengupta S; Krummel DP; Rothenberg ME; Aronow BJ

 2021

Peer reviewed
Topics
Open Access Data, Computational Methods

scConsensus: combining supervised and unsupervised clustering for cell type identification in single-cell RNA sequencing data.

Clustering is a crucial step in the analysis of single-cell data. Clusters identified in an unsupervised manner are typically annotated to cell types based on differentially expressed genes. In contrast, supervised methods use a reference panel of labelled transcriptomes to guide both clustering and cell type identification. Supervised and unsupervised clustering approaches have their distinct advantages and limitations. Therefore, they can lead to different but often complementary clustering results. Hence, a consensus approach leveraging the merits of both clustering paradigms could result in a more accurate clustering and a more precise cell type annotation.

Ranjan B; Schmidt F; Sun W; Park J; Honardoost MA; Tan J; Arul Rayan N; Prabhakar S

BMC bioinformatics 2021;22;1;186

Topics
Human Subjects, Healthy Donors, Disease Donors, Experimental Methods, Computational Methods

An integrated taxonomy for monogenic inflammatory bowel disease.

Monogenic forms of inflammatory bowel disease (IBD) illustrate the essential roles of individual genes in pathways and networks safeguarding immune tolerance and gut homeostasis.

Bolton C; Smillie CS; Pandey S; Elmentaite R; Wei G; Argmann C; Aschenbrenner D; James KR; McGovern DPB; Macchi M et al

 2021

Peer reviewed

Integrative analysis of cell state changes in lung fibrosis with peripheral protein biomarkers.

The correspondence of cell state changes in diseased organs to peripheral protein signatures is currently unknown. Here, we generated and integrated single-cell transcriptomic and proteomic data from multiple large pulmonary fibrosis patient cohorts. Integration of 233,638 single-cell transcriptomes (n = 61) across three independent cohorts enabled us to derive shifts in cell type proportions and a robust core set of genes altered in lung fibrosis for 45 cell types. Mass spectrometry analysis of lung lavage fluid (n = 124) and plasma (n = 141) proteomes identified distinct protein signatures correlated with diagnosis, lung function, and injury status. A novel SSTR2+ pericyte state correlated with disease severity and was reflected in lavage fluid by increased levels of the complement regulatory factor CFHR1. We further discovered CRTAC1 as a biomarker of alveolar type-2 epithelial cell health status in lavage fluid and plasma. Using cross-modal analysis and machine learning, we identified the cellular source of biomarkers and demonstrated that information transfer between modalities correctly predicts disease status, suggesting feasibility of clinical cell state monitoring through longitudinal sampling of body fluid proteomes.

Mayr CH; Simon LM; Leuschner G; Ansari M; Schniering J; Geyer PE; Angelidis I; Strunz M; Singh P; Kneidinger N et al

EMBO molecular medicine 2021;13;4;e12871

Pre-print
Topics
Human Subjects, Healthy Donors, Disease Donors, Experimental Methods, Computational Methods, COVID-19

Systemic Tissue and Cellular Disruption from SARS-CoV-2 Infection revealed in COVID-19 Autopsies and Spatial Omics Tissue Maps.

The Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) virus has infected over 115 million people and caused over 2.5 million deaths worldwide. Yet, the molecular mechanisms underlying the clinical manifestations of COVID-19, as well as what distinguishes them from common seasonal influenza virus and other lung injury states such as Acute Respiratory Distress Syndrome (ARDS), remains poorly understood. To address these challenges, we combined transcriptional profiling of 646 clinical nasopharyngeal swabs and 39 patient autopsy tissues, matched with spatial protein and expression profiling (GeoMx) across 357 tissue sections. These results define both body-wide and tissue-specific (heart, liver, lung, kidney, and lymph nodes) damage wrought by the SARS-CoV-2 infection, evident as a function of varying viral load (high vs. low) during the course of infection and specific, transcriptional dysregulation in splicing isoforms, T cell receptor expression, and cellular expression states. In particular, cardiac and lung tissues revealed the largest degree of splicing isoform switching and cell expression state loss. Overall, these findings reveal a systemic disruption of cellular and transcriptional pathways from COVID-19 across all tissues, which can inform subsequent studies to combat the mortality of COVID-19, as well to better understand the molecular dynamics of lethal SARS-CoV-2 infection and other viruses.

Park J; Foox J; Hether T; Danko D; Warren S; Kim Y; Reeves J; Butler DJ; Mozsary C; Rosiene J et al

bioRxiv 2021

Peer reviewed
Topics
Human Subjects, Disease Donors, Experimental Methods

Dissecting the Transcriptional and Chromatin Accessibility Heterogeneity of Proliferating Cone Precursors in Human Retinoblastoma Tumors by Single Cell Sequencing-Opening Pathways to New Therapeutic Strategies?

Retinoblastoma (Rb) is a malignant neoplasm arising during retinal development from mutations in the RB1 gene. Loss or inactivation of both copies of RB1 results in initiation of retinoblastoma tumors; however, additional genetic changes are needed for the continued growth and spread of the tumor. Ex vivo research has shown that in humans, retinoblastoma may initiate from RB1-depleted cone precursors. Notwithstanding, it has not been possible to assess the full spectrum of clonal types within the tumor itself in vivo and the molecular changes occurring at the cells of origin, enabling their malignant conversion. To overcome these challenges, we have performed the first single cell (sc) RNA- and ATAC-Seq analyses of primary tumor tissues, enabling us to dissect the transcriptional and chromatin accessibility heterogeneity of proliferating cone precursors in human Rb tumors.

Collin J; Queen R; Zerti D; Steel DH; Bowen C; Parulekar M; Lako M

Investigative ophthalmology & visual science 2021;62;6;18

Topics
Computational Methods

Deep learning and alignment of spatially resolved single-cell transcriptomes with Tangram.

Charting an organs' biological atlas requires us to spatially resolve the entire single-cell transcriptome, and to relate such cellular features to the anatomical scale. Single-cell and single-nucleus RNA-seq (sc/snRNA-seq) can profile cells comprehensively, but lose spatial information. Spatial transcriptomics allows for spatial measurements, but at lower resolution and with limited sensitivity. Targeted in situ technologies solve both issues, but are limited in gene throughput. To overcome these limitations we present Tangram, a method that aligns sc/snRNA-seq data to various forms of spatial data collected from the same region, including MERFISH, STARmap, smFISH, Spatial Transcriptomics (Visium) and histological images. Tangram can map any type of sc/snRNA-seq data, including multimodal data such as those from SHARE-seq, which we used to reveal spatial patterns of chromatin accessibility. We demonstrate Tangram on healthy mouse brain tissue, by reconstructing a genome-wide anatomically integrated spatial map at single-cell resolution of the visual and somatomotor areas.

Biancalani T; Scalia G; Buffoni L; Avasthi R; Lu Z; Sanger A; Tokcan N; Vanderburg CR; Segerstolpe Å; Zhang M et al

 2021;18;11

Topics
Open Access Data, Computational Methods

Besca, a single-cell transcriptomics analysis toolkit to accelerate translational research.

Single-cell RNA sequencing (scRNA-seq) revolutionized our understanding of disease biology. The promise it presents to also transform translational research requires highly standardized and robust software workflows. Here, we present the toolkit , which streamlines scRNA-seq analyses and their use to deconvolute bulk RNA-seq data according to current best practices. Beyond a standard workflow covering quality control, filtering, and clustering, two complementary modules, utilizing hierarchical cell signatures and supervised machine learning, automate cell annotation and provide harmonized nomenclatures. Subsequently, the gene expression profiles can be employed to estimate cell type proportions in bulk transcriptomics data. Using multiple, diverse scRNA-seq datasets, some stemming from highly heterogeneous tumor tissue, we show how aids acceleration, interoperability, reusability and interpretability of scRNA-seq data analyses, meeting crucial demands in translational research and beyond.

Mädler SC; Julien-Laferriere A; Wyss L; Phan M; Sonrel A; Kang ASW; Ulrich E; Schmucki R; Zhang JD; Ebeling M et al

 2021;3;4

Peer reviewed
Topics
Human Subjects, Healthy Donors, Disease Donors, COVID-19

Hypertension delays viral clearance and exacerbates airway hyperinflammation in patients with COVID-19

In coronavirus disease 2019 (COVID-19), hypertension and cardiovascular diseases are major risk factors for critical disease progression. However, the underlying causes and the effects of the main anti-hypertensive therapies—angiotensin-converting enzyme inhibitors (ACEIs) and angiotensin receptor blockers (ARBs)—remain unclear. Combining clinical data (n = 144) and single-cell sequencing data of airway samples (n = 48) with in vitro experiments, we observed a distinct inflammatory predisposition of immune cells in patients with hypertension that correlated with critical COVID-19 progression. ACEI treatment was associated with dampened COVID-19-related hyperinflammation and with increased cell intrinsic antiviral responses, whereas ARB treatment related to enhanced epithelial–immune cell interactions. Macrophages and neutrophils of patients with hypertension, in particular under ARB treatment, exhibited higher expression of the pro-inflammatory cytokines CCL3 and CCL4 and the chemokine receptor CCR1. Although the limited size of our cohort does not allow us to establish clinical efficacy, our data suggest that the clinical benefits of ACEI treatment in patients with COVID-19 who have hypertension warrant further investigation. Single-cell analysis reveals how anti-hypertensive drugs affect the risk of severe disease in patients with COVID-19 who have hypertension.

Trump, Saskia; Lukassen, Soeren; Anker, Markus S.; Chua, Robert Lorenz; Liebig, Johannes; Thürmann, Loreen; Corman, Victor Max; Binder, Marco; Loske, Jennifer; Klasa, Christina et al

Nature Biotechnology 2020;39;6;705-716

Peer reviewed
Topics
Human Subjects, Healthy Donors, Disease Donors, Open Access Data

Single-Cell Sequencing of Developing Human Gut Reveals Transcriptional Links to Childhood Crohn's Disease.

Human gut development requires the orchestrated interaction of differentiating cell types. Here, we generate an in-depth single-cell map of the developing human intestine at 6-10 weeks post-conception. Our analysis reveals the transcriptional profile of cycling epithelial precursor cells; distinct from LGR5-expressing cells. We propose that these cells may contribute to differentiated cell subsets via the generation of LGR5-expressing stem cells and receive signals from surrounding mesenchymal cells. Furthermore, we draw parallels between the transcriptomes of ex vivo tissues and in vitro fetal organoids, revealing the maturation of organoid cultures in a dish. Lastly, we compare scRNA-seq profiles from pediatric Crohn's disease epithelium alongside matched healthy controls to reveal disease-associated changes in the epithelial composition. Contrasting these with the fetal profiles reveals the re-activation of fetal transcription factors in Crohn's disease. Our study provides a resource available at www.gutcellatlas.org, and underscores the importance of unraveling fetal development in understanding disease.

Elmentaite R; Ross ADB; Roberts K; James KR; Ortmann D; Gomes T; Nayak K; Tuck L; Pritchard S; Bayraktar OA et al

Developmental cell 2020;55;6;771-783.e5

Peer reviewed
Topics
Human Subjects, Healthy Donors, Disease Donors, COVID-19

Longitudinal Multi-omics Analyses Identify Responses of Megakaryocytes, Erythroid Cells, and Plasmablasts as Hallmarks of Severe COVID-19.

Temporal resolution of cellular features associated with a severe COVID-19 disease trajectory is needed for understanding skewed immune responses and defining predictors of outcome. Here, we performed a longitudinal multi-omics study using a two-center cohort of 14 patients. We analyzed the bulk transcriptome, bulk DNA methylome, and single-cell transcriptome (>358,000 cells, including BCR profiles) of peripheral blood samples harvested from up to 5 time points. Validation was performed in two independent cohorts of COVID-19 patients. Severe COVID-19 was characterized by an increase of proliferating, metabolically hyperactive plasmablasts. Coinciding with critical illness, we also identified an expansion of interferon-activated circulating megakaryocytes and increased erythropoiesis with features of hypoxic signaling. Megakaryocyte- and erythroid-cell-derived co-expression modules were predictive of fatal disease outcome. The study demonstrates broad cellular effects of SARS-CoV-2 infection beyond adaptive immune cells and provides an entry point toward developing biomarkers and targeted treatments of patients with COVID-19.

Bernardes JP; Mishra N; Tran F; Bahmer T; Best L; Blase JI; Bordoni D; Franzenburg J; Geisen U; Josephs-Spaulding J et al

Immunity 2020;53;6;1296-1314.e9

Peer reviewed
Topics
Human Subjects

A Single-Cell Atlas of the Human Healthy Airways.

The respiratory tract constitutes an elaborate line of defense that is based on a unique cellular ecosystem. We aimed to investigate cell population distributions and transcriptional changes along the airways by using single-cell RNA profiling. We have explored the cellular heterogeneity of the human airway epithelium in 10 healthy living volunteers by single-cell RNA profiling. A total of 77,969 cells were collected at 35 distinct locations, from the nose to the 12th division of the airway tree. The resulting atlas is composed of a high percentage of epithelial cells (89.1%) but also immune (6.2%) and stromal (4.7%) cells with distinct cellular proportions in different regions of the airways. It reveals differential gene expression between identical cell types (suprabasal, secretory, and multiciliated cells) from the nose (, , ) and tracheobronchial (, ) airways. By contrast, cell-type-specific gene expression is stable across all tracheobronchial samples. Our atlas improves the description of ionocytes, pulmonary neuroendocrine cells, and brush cells and identifies a related population of -positive cells. We also report the association of with dividing cells that are reminiscent of previously described mouse "hillock" cells and with squamous cells expressing and . Robust characterization of a single-cell cohort in healthy airways establishes a valuable resource for future investigations. The precise description of the continuum existing from the nasal epithelium to successive divisions of the airways and the stable gene expression profile of these regions better defines conditions under which relevant tracheobronchial proxies of human respiratory diseases can be developed.

Deprez M; Zaragosi LE; Truchi M; Becavin C; Ruiz García S; Arguel MJ; Plaisant M; Magnone V; Lebrigand K; Abelanet S et al

American journal of respiratory and critical care medicine 2020;202;12;1636-1645

Peer reviewed
Topics
Computational Methods

Gene set inference from single-cell sequencing data using a hybrid of matrix factorization and variational autoencoders

Recent advances in single-cell RNA sequencing have driven the simultaneous measurement of the expression of thousands of genes in thousands of single cells. These growing datasets allow us to model gene sets in biological networks at an unprecedented level of detail, in spite of heterogeneous cell populations. Here, we propose a deep neural network model that is a hybrid of matrix factorization and variational autoencoders, which we call restricted latent variational autoencoder (resVAE). The model uses weights as factorized matrices to obtain gene sets, while class-specific inputs to the latent variable space facilitate a plausible identification of cell types. This artificial neural network model seamlessly integrates functional gene set inference, experimental covariate effect isolation, and static gene identification, which we conceptually demonstrate here for four single-cell RNA sequencing datasets. The wealth of data generated by single-cell RNA sequencing can be used to identify gene sets across cells, as well as to identify specific cells. Lukassen and colleagues propose a method combining matrix factorization and variational auto encoders that can capture both cross-cell and cell-specific information.

Lukassen, Soeren; Ten, Foo Wei; Adam, Lukas; Eils, Roland; Conrad, Christian

Nature Machine Intelligence 2020;2;12

Peer reviewed
Topics
Human Subjects, Healthy Donors, Open Access Data, Experimental Methods, Computational Methods

Cells of the adult human heart.

Cardiovascular disease is the leading cause of death worldwide. Advanced insights into disease mechanisms and therapeutic strategies require a deeper understanding of the molecular processes involved in the healthy heart. Knowledge of the full repertoire of cardiac cells and their gene expression profiles is a fundamental first step in this endeavour. Here, using state-of-the-art analyses of large-scale single-cell and single-nucleus transcriptomes, we characterize six anatomical adult heart regions. Our results highlight the cellular heterogeneity of cardiomyocytes, pericytes and fibroblasts, and reveal distinct atrial and ventricular subsets of cells with diverse developmental origins and specialized properties. We define the complexity of the cardiac vasculature and its changes along the arterio-venous axis. In the immune compartment, we identify cardiac-resident macrophages with inflammatory and protective transcriptional signatures. Furthermore, analyses of cell-to-cell interactions highlight different networks of macrophages, fibroblasts and cardiomyocytes between atria and ventricles that are distinct from those of skeletal muscle. Our human cardiac cell atlas improves our understanding of the human heart and provides a valuable reference for future studies.

Litviňuková M; Talavera-López C; Maatz H; Reichart D; Worth CL; Lindberg EL; Kanda M; Polanski K; Heinig M; Lee M et al

Nature 2020;588;7838;466-472

Peer reviewed
Topics
Human Subjects, Healthy Donors, Disease Donors

SARS-CoV-2 receptor networks in diabetic and COVID-19-associated kidney disease.

COVID-19 morbidity and mortality are increased via unknown mechanisms in patients with diabetes and kidney disease. SARS-CoV-2 uses angiotensin-converting enzyme 2 (ACE2) for entry into host cells. Because ACE2 is a susceptibility factor for infection, we investigated how diabetic kidney disease and medications alter ACE2 receptor expression in kidneys. Single cell RNA profiling of kidney biopsies from healthy living donors and patients with diabetic kidney disease revealed ACE2 expression primarily in proximal tubular epithelial cells. This cell-specific localization was confirmed by in situ hybridization. ACE2 expression levels were unaltered by exposures to renin-angiotensin-aldosterone system inhibitors in diabetic kidney disease. Bayesian integrative analysis of a large compendium of public -omics datasets identified molecular network modules induced in ACE2-expressing proximal tubular epithelial cells in diabetic kidney disease (searchable at hb.flatironinstitute.org/covid-kidney) that were linked to viral entry, immune activation, endomembrane reorganization, and RNA processing. The diabetic kidney disease ACE2-positive proximal tubular epithelial cell module overlapped with expression patterns seen in SARS-CoV-2-infected cells. Similar cellular programs were seen in ACE2-positive proximal tubular epithelial cells obtained from urine samples of 13 hospitalized patients with COVID-19, suggesting a consistent ACE2-coregulated proximal tubular epithelial cell expression program that may interact with the SARS-CoV-2 infection processes. Thus SARS-CoV-2 receptor networks can seed further research into risk stratification and therapeutic strategies for COVID-19-related kidney damage.

Menon R; Otto EA; Sealfon R; Nair V; Wong AK; Theesfeld CL; Chen X; Wang Y; Boppana AS; Luo J et al

Kidney international 2020;98;6;1502-1518

Peer reviewed
Topics
Human Subjects, Healthy Donors, Experimental Methods, Computational Methods

A human cell atlas of fetal chromatin accessibility.

The chromatin landscape underlying the specification of human cell types is of fundamental interest. We generated human cell atlases of chromatin accessibility and gene expression in fetal tissues. For chromatin accessibility, we devised a three-level combinatorial indexing assay and applied it to 53 samples representing 15 organs, profiling ~800,000 single cells. We leveraged cell types defined by gene expression to annotate these data and cataloged hundreds of thousands of candidate regulatory elements that exhibit cell type-specific chromatin accessibility. We investigated the properties of lineage-specific transcription factors (such as POU2F1 in neurons), organ-specific specializations of broadly distributed cell types (such as blood and endothelial), and cell type-specific enrichments of complex trait heritability. These data represent a rich resource for the exploration of in vivo human gene regulation in diverse tissues and cell types.

Domcke S; Hill AJ; Daza RM; Cao J; O'Day DR; Pliner HA; Aldinger KA; Pokholok D; Zhang F; Milbank JH et al

Science 2020;370;6518

Peer reviewed
Topics
Human Subjects, Healthy Donors, Experimental Methods, Computational Methods

A human cell atlas of fetal gene expression.

The gene expression program underlying the specification of human cell types is of fundamental interest. We generated human cell atlases of gene expression and chromatin accessibility in fetal tissues. For gene expression, we applied three-level combinatorial indexing to >110 samples representing 15 organs, ultimately profiling ~4 million single cells. We leveraged the literature and other atlases to identify and annotate hundreds of cell types and subtypes, both within and across tissues. Our analyses focused on organ-specific specializations of broadly distributed cell types (such as blood, endothelial, and epithelial), sites of fetal erythropoiesis (which notably included the adrenal gland), and integration with mouse developmental atlases (such as conserved specification of blood cells). These data represent a rich resource for the exploration of in vivo human gene expression in diverse tissues and cell types.

Cao J; O'Day DR; Pliner HA; Kingsley PD; Deng M; Daza RM; Zager MA; Aldinger KA; Blecher-Gonen R; Zhang F et al

Science 2020;370;6518

Pre-print

Poised cell circuits in human skin are activated in disease

bioRxiv - the preprint server for biology, operated by Cold Spring Harbor Laboratory, a research and educational institution

Gary Reynolds; Peter Vegh; James Fletcher; Elizabeth F.M. Poyner; Emily Stephenson; Issac Goh; Rachel A. Botting; Ni Huang; Bayanne Olabi; Anna Dubois et al

bioRxiv 2020;2020.11.05.369363

Pre-print
Topics
Human Subjects, Model Organism Samples, Healthy Donors, Open Access Data

Integrated Single Cell Atlas of Endothelial Cells of the Human Lung

bioRxiv - the preprint server for biology, operated by Cold Spring Harbor Laboratory, a research and educational institution

Jonas C. Schupp; Taylor S. Adams; Carlos Cosme; Micha Sam Brickman Raredon; Norihito Omote; Sergio Poli De Frias; Kadi-Ann Rose; Edward Manning; Maor Sauler; Giuseppe DeIuliis et al

bioRxiv 2020;2020.10.21.347914

Peer reviewed

The Human Cell Atlas and equity: lessons learned

The Human Cell Atlas has been undergoing a massive effort to support global scientific equity. The co-leaders of its Equity Working Group share some lessons learned in the process.

Majumder, Partha P.; Mhlanga, Musa M.; Shalek, Alex K.

Nature Medicine 2020;26;10;1509-1511

Topics
Human Subjects, Model Organism Samples, Healthy Donors, Open Access Data, Experimental Methods, Computational Methods

The Human and Mouse Enteric Nervous System at Single-Cell Resolution.

The enteric nervous system (ENS) coordinates diverse functions in the intestine but has eluded comprehensive molecular characterization because of the rarity and diversity of cells. Here we develop two methods to profile the ENS of adult mice and humans at single-cell resolution: RAISIN RNA-seq for profiling intact nuclei with ribosome-bound mRNA and MIRACL-seq for label-free enrichment of rare cell types by droplet-based profiling. The 1,187,535 nuclei in our mouse atlas include 5,068 neurons from the ileum and colon, revealing extraordinary neuron diversity. We highlight circadian expression changes in enteric neurons, show that disease-related genes are dysregulated with aging, and identify differences between the ileum and proximal/distal colon. In humans, we profile 436,202 nuclei, recovering 1,445 neurons, and identify conserved and species-specific transcriptional programs and putative neuro-epithelial, neuro-stromal, and neuro-immune interactions. The human ENS expresses risk genes for neuropathic, inflammatory, and extra-intestinal diseases, suggesting neuronal contributions to disease.

Drokhlyansky E; Smillie CS; Van Wittenberghe N; Ericsson M; Griffin GK; Eraslan G; Dionne D; Cuoco MS; Goder-Reiser MN; Sharova T et al

 2020;182;6

Peer reviewed

An era of single-cell genomics consortia.

The human body consists of 37 trillion single cells represented by over 50 organs that are stitched together to make us who we are, yet we still have very little understanding about the basic units of our body: what cell types and states make up our organs both compositionally and spatially. Previous efforts to profile a wide range of human cell types have been attempted by the FANTOM and GTEx consortia. Now, with the advancement in genomic technologies, profiling the human body at single-cell resolution is possible and will generate an unprecedented wealth of data that will accelerate basic and clinical research with tangible applications to future medicine. To date, several major organs have been profiled, but the challenges lie in ways to integrate single-cell genomics data in a meaningful way. In recent years, several consortia have begun to introduce harmonization and equity in data collection and analysis. Herein, we introduce existing and nascent single-cell genomics consortia, and present benefits to necessitate single-cell genomic consortia in a regional environment to achieve the universal human cell reference dataset.

Ando Y; Kwon AT; Shin JW

Experimental & molecular medicine 2020;52;9;1409-1418

Peer reviewed
Networks
Lung
Topics
Human Subjects, Healthy Donors, Disease Donors

Myocyte-Specific Upregulation of in Cardiovascular Disease: Implications for SARS-CoV-2-Mediated Myocarditis.

Tucker NR; Chaffin M; Bedi KC; Papangeli I; Akkad AD; Arduini A; Hayat S; Eraslan G; Muus C; Bhattacharyya RP et al

Circulation 2020;142;7;708-710

Peer reviewed
Topics
Experimental Methods, Computational Methods

High throughput error corrected Nanopore single cell transcriptome sequencing.

Droplet-based high throughput single cell sequencing techniques tremendously advanced our insight into cell-to-cell heterogeneity. However, those approaches only allow analysis of one extremity of the transcript after short read sequencing. In consequence, information on splicing and sequence heterogeneity is lost. To overcome this limitation, several approaches that use long-read sequencing were introduced recently. Yet, those techniques are limited by low sequencing depth and/or lacking or inaccurate assignment of unique molecular identifiers (UMIs), which are critical for elimination of PCR bias and artifacts. We introduce ScNaUmi-seq, an approach that combines the high throughput of Oxford Nanopore sequencing with an accurate cell barcode and UMI assignment strategy. UMI guided error correction allows to generate high accuracy full length sequence information with the 10x Genomics single cell isolation system at high sequencing depths. We analyzed transcript isoform diversity in embryonic mouse brain and show that ScNaUmi-seq allows defining splicing and SNVs (RNA editing) at a single cell level.

Lebrigand K; Magnone V; Barbry P; Waldmann R

Nature Communications 2020;11;1;4025

Peer reviewed
Topics
Human Subjects, Healthy Donors, Disease Donors, COVID-19

COVID-19 severity correlates with airway epithelium–immune cell interactions identified by single-cell analysis

To investigate the immune response and mechanisms associated with severe coronavirus disease 2019 (COVID-19), we performed single-cell RNA sequencing on nasopharyngeal and bronchial samples from 19 clinically well-characterized patients with moderate or critical disease and from five healthy controls. We identified airway epithelial cell types and states vulnerable to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. In patients with COVID-19, epithelial cells showed an average three-fold increase in expression of the SARS-CoV-2 entry receptor ACE2, which correlated with interferon signals by immune cells. Compared to moderate cases, critical cases exhibited stronger interactions between epithelial and immune cells, as indicated by ligand–receptor expression profiles, and activated immune cells, including inflammatory macrophages expressing CCL2, CCL3, CCL20, CXCL1, CXCL3, CXCL10, IL8, IL1B and TNF. The transcriptional differences in critical cases compared to moderate cases likely contribute to clinical observations of heightened inflammatory tissue damage, lung injury and respiratory failure. Our data suggest that pharmacologic inhibition of the CCR1 and/or CCR5 pathways might suppress immune hyperactivation in critical COVID-19. Single-cell analysis of COVID-19 patient samples identifies activated immune pathways that correlate with severe disease.

Chua, Robert Lorenz; Lukassen, Soeren; Trump, Saskia; Hennig, Bianca P.; Wendisch, Daniel; Pott, Fabian; Debnath, Olivia; Thürmann, Loreen; Kurth, Florian; Völker, Maria Theresa et al

Nature Biotechnology 2020;38;8;970-979

Topics
Healthy Donors, Experimental Methods, Computational Methods, Benchmarking

Systematic comparison of single-cell and single-nucleus RNA-sequencing methods.

The scale and capabilities of single-cell RNA-sequencing methods have expanded rapidly in recent years, enabling major discoveries and large-scale cell mapping efforts. However, these methods have not been systematically and comprehensively benchmarked. Here, we directly compare seven methods for single-cell and/or single-nucleus profiling-selecting representative methods based on their usage and our expertise and resources to prepare libraries-including two low-throughput and five high-throughput methods. We tested the methods on three types of samples: cell lines, peripheral blood mononuclear cells and brain tissue, generating 36 libraries in six separate experiments in a single center. To directly compare the methods and avoid processing differences introduced by the existing pipelines, we developed scumi, a flexible computational pipeline that can be used with any single-cell RNA-sequencing method. We evaluated the methods for both basic performance, such as the structure and alignment of reads, sensitivity and extent of multiplets, and for their ability to recover known biological information in the samples.

Ding J; Adiconis X; Simmons SK; Kowalczyk MS; Hession CC; Marjanovic ND; Hughes TK; Wadsworth MH; Burks T; Nguyen LT et al

 2020;38;6

Networks
Lung
Topics
Human Subjects, Model Organism Samples, Healthy Donors, Disease Donors, Open Access Data, COVID-19

SARS-CoV-2 Receptor ACE2 Is an Interferon-Stimulated Gene in Human Airway Epithelial Cells and Is Detected in Specific Cell Subsets across Tissues.

There is pressing urgency to understand the pathogenesis of the severe acute respiratory syndrome coronavirus clade 2 (SARS-CoV-2), which causes the disease COVID-19. SARS-CoV-2 spike (S) protein binds angiotensin-converting enzyme 2 (ACE2), and in concert with host proteases, principally transmembrane serine protease 2 (TMPRSS2), promotes cellular entry. The cell subsets targeted by SARS-CoV-2 in host tissues and the factors that regulate ACE2 expression remain unknown. Here, we leverage human, non-human primate, and mouse single-cell RNA-sequencing (scRNA-seq) datasets across health and disease to uncover putative targets of SARS-CoV-2 among tissue-resident cell subsets. We identify ACE2 and TMPRSS2 co-expressing cells within lung type II pneumocytes, ileal absorptive enterocytes, and nasal goblet secretory cells. Strikingly, we discovered that ACE2 is a human interferon-stimulated gene (ISG) in vitro using airway epithelial cells and extend our findings to in vivo viral infections. Our data suggest that SARS-CoV-2 could exploit species-specific interferon-driven upregulation of ACE2, a tissue-protective mediator during lung injury, to enhance infection.

Ziegler CGK; Allon SJ; Nyquist SK; Mbano IM; Miao VN; Tzouanas CN; Cao Y; Yousif AS; Bals J; Hauser BM et al

 2020;181;5

Peer reviewed
Topics
Human Subjects, Healthy Donors, Disease Donors, COVID-19

SARS-CoV-2 receptor ACE2 and TMPRSS2 are primarily expressed in bronchial transient secretory cells.

The SARS-CoV-2 pandemic affecting the human respiratory system severely challenges public health and urgently demands for increasing our understanding of COVID-19 pathogenesis, especially host factors facilitating virus infection and replication. SARS-CoV-2 was reported to enter cells via binding to ACE2, followed by its priming by TMPRSS2. Here, we investigate ACE2 and TMPRSS2 expression levels and their distribution across cell types in lung tissue (twelve donors, 39,778 cells) and in cells derived from subsegmental bronchial branches (four donors, 17,521 cells) by single nuclei and single cell RNA sequencing, respectively. While TMPRSS2 is strongly expressed in both tissues, in the subsegmental bronchial branches ACE2 is predominantly expressed in a transient secretory cell type. Interestingly, these transiently differentiating cells show an enrichment for pathways related to RHO GTPase function and viral processes suggesting increased vulnerability for SARS-CoV-2 infection. Our data provide a rich resource for future investigations of COVID-19 infection and pathogenesis.

Lukassen S; Chua RL; Trefzer T; Kahn NC; Schneider MA; Muley T; Winter H; Meister M; Veith C; Boots AW et al

The EMBO journal 2020;39;10;e105114

Topics
Human Subjects, Healthy Donors, Disease Donors, Open Access Data, Experimental Methods

Sampling time-dependent artifacts in single-cell genomics studies.

Robust protocols and automation now enable large-scale single-cell RNA and ATAC sequencing experiments and their application on biobank and clinical cohorts. However, technical biases introduced during sample acquisition can hinder solid, reproducible results, and a systematic benchmarking is required before entering large-scale data production. Here, we report the existence and extent of gene expression and chromatin accessibility artifacts introduced during sampling and identify experimental and computational solutions for their prevention.

Massoni-Badosa R; Iacono G; Moutinho C; Kulis M; Palau N; Marchese D; Rodríguez-Ubreva J; Ballestar E; Rodriguez-Esteban G; Marsal S et al

 2020;21;1

Peer reviewed
Topics
Human Subjects, Disease Donors, Experimental Methods, Computational Methods

A single-cell and single-nucleus RNA-Seq toolbox for fresh and frozen human tumors.

Single-cell genomics is essential to chart tumor ecosystems. Although single-cell RNA-Seq (scRNA-Seq) profiles RNA from cells dissociated from fresh tumors, single-nucleus RNA-Seq (snRNA-Seq) is needed to profile frozen or hard-to-dissociate tumors. Each requires customization to different tissue and tumor types, posing a barrier to adoption. Here, we have developed a systematic toolbox for profiling fresh and frozen clinical tumor samples using scRNA-Seq and snRNA-Seq, respectively. We analyzed 216,490 cells and nuclei from 40 samples across 23 specimens spanning eight tumor types of varying tissue and sample characteristics. We evaluated protocols by cell and nucleus quality, recovery rate and cellular composition. scRNA-Seq and snRNA-Seq from matched samples recovered the same cell types, but at different proportions. Our work provides guidance for studies in a broad range of tumors, including criteria for testing and selecting methods from the toolbox for other tumors, thus paving the way for charting tumor atlases.

Slyper M; Porter CBM; Ashenberg O; Waldman J; Drokhlyansky E; Wakiro I; Smillie C; Smith-Rosario G; Wu J; Dionne D et al

Nature Medicine 2020;26;5;792-802

Pre-print
Topics
Model Organism Samples, Healthy Donors, COVID-19

Single-cell atlas of a non-human primate reveals new pathogenic mechanisms of COVID-19

bioRxiv - the preprint server for biology, operated by Cold Spring Harbor Laboratory, a research and educational institution

Lei Han; Xiaoyu Wei; Chuanyu Liu; Giacomo Volpe; Zhifeng Wang; Taotao Pan; Yue Yuan; Ying Lei; Yiwei Lai; Carl Ward et al

bioRxiv 2020;2020.04.10.022103

Peer reviewed
Networks
Lung

SARS-CoV-2 entry factors are highly expressed in nasal epithelial cells together with innate immune genes

We investigated SARS-CoV-2 potential tropism by surveying expression of viral entry-associated genes in single-cell RNA-sequencing data from multiple tissues from healthy human donors. We co-detected these transcripts in specific respiratory, corneal and intestinal epithelial cells, potentially explaining the high efficiency of SARS-CoV-2 transmission. These genes are co-expressed in nasal epithelial cells with genes involved in innate immunity, highlighting the cells’ potential role in initial viral infection, spread and clearance. The study offers a useful resource for further lines of inquiry with valuable clinical samples from COVID-19 patients and we provide our data in a comprehensive, open and user-friendly fashion at www.covid19cellatlas.org. An analysis of single-cell transcriptomics datasets from different tissues shows that ACE2 and TMPRSS2 are co-expressed in respiratory, corneal and intestinal epithelial cell populations, and that respiratory expression of ACE2 is associated with genes involved in innate immunity.

Sungnak, Waradon; Huang, Ni; Bécavin, Christophe; Berg, Marijn; Queen, Rachel; Litvinukova, Monika; Talavera-López, Carlos; Maatz, Henrike; Reichart, Daniel; Sampaziotis, Fotios et al

Nature Medicine 2020;26;5;681-687

Pre-print
Topics
Human Subjects, Healthy Donors, Open Access Data

Single cell profiling of immature human postnatal thymocytes resolves the complexity of intra-thymic lineage differentiation and thymus seeding precursors

bioRxiv - the preprint server for biology, operated by Cold Spring Harbor Laboratory, a research and educational institution

Marieke Lavaert; Kai Ling Liang; Niels Vandamme; Jong-Eun Park; Juliette Roels; Monica S. Kowalczyk; Bo Li; Orr Ashenberg; Marcin Tabaka; Danielle Dionne et al

bioRxiv 2020;2020.04.07.007237

Peer reviewed
Topics
Open Access Data, Experimental Methods, Benchmarking

Benchmarking single-cell RNA-sequencing protocols for cell atlas projects

Single-cell RNA sequencing (scRNA-seq) is the leading technique for characterizing the transcriptomes of individual cells in a sample. The latest protocols are scalable to thousands of cells and are being used to compile cell atlases of tissues, organs and organisms. However, the protocols differ substantially with respect to their RNA capture efficiency, bias, scale and costs, and their relative advantages for different applications are unclear. In the present study, we generated benchmark datasets to systematically evaluate protocols in terms of their power to comprehensively describe cell types and states. We performed a multicenter study comparing 13 commonly used scRNA-seq and single-nucleus RNA-seq protocols applied to a heterogeneous reference sample resource. Comparative analysis revealed marked differences in protocol performance. The protocols differed in library complexity and their ability to detect cell-type markers, impacting their predictive value and suitability for integration into reference cell atlases. These results provide guidance both for individual researchers and for consortium projects such as the Human Cell Atlas. A multicenter study compares 13 commonly used single-cell RNA-seq protocols.

Mereu, Elisabetta; Lafzi, Atefeh; Moutinho, Catia; Ziegenhain, Christoph; McCarthy, Davis J.; Álvarez-Varela, Adrián; Batlle, Eduard; Sagar; Grün, Dominic; Lau, Julia K. et al

Nature Biotechnology 2020;38;6;747-755

Peer reviewed
Topics
Human Subjects, Healthy Donors, Open Access Data, Experimental Methods, Computational Methods

Construction of a human cell landscape at single-cell level

Single-cell analysis is a valuable tool for dissecting cellular heterogeneity in complex systems1. However, a comprehensive single-cell atlas has not been achieved for humans. Here we use single-cell mRNA sequencing to determine the cell-type composition of all major human organs and construct a scheme for the human cell landscape (HCL). We have uncovered a single-cell hierarchy for many tissues that have not been well characterized. We established a ‘single-cell HCL analysis’ pipeline that helps to define human cell identity. Finally, we performed a single-cell comparative analysis of landscapes from human and mouse to identify conserved genetic networks. We found that stem and progenitor cells exhibit strong transcriptomic stochasticity, whereas differentiated cells are more distinct. Our results provide a useful resource for the study of human biology. Single-cell RNA sequencing is used to generate a dataset covering all major human organs in both adult and fetal stages, enabling comparison with similar datasets for mouse tissues.

Han, Xiaoping; Zhou, Ziming; Fei, Lijiang; Sun, Huiyu; Wang, Renying; Chen, Yao; Chen, Haide; Wang, Jingjing; Tang, Huanna; Ge, Wenhao et al

Nature 2020;581;7808;303-309

Peer reviewed
Topics
Human Subjects, Healthy Donors

Re-evaluation of human BDCA-2+ DC during acute sterile skin inflammation.

Plasmacytoid dendritic cells (pDCs) produce type I interferon (IFN-I) and are traditionally defined as being BDCA-2+CD123+. pDCs are not readily detectable in healthy human skin, but have been suggested to accumulate in wounds. Here, we describe a CD1a-bearing BDCA-2+CD123int DC subset that rapidly infiltrates human skin wounds and comprises a major DC population. Using single-cell RNA sequencing, we show that these cells are largely activated DCs acquiring features compatible with lymph node homing and antigen presentation, but unexpectedly express both BDCA-2 and CD123, potentially mimicking pDCs. Furthermore, a third BDCA-2-expressing population, Axl+Siglec-6+ DCs (ASDC), was also found to infiltrate human skin during wounding. These data demonstrate early skin infiltration of a previously unrecognized CD123intBDCA-2+CD1a+ DC subset during acute sterile inflammation, and prompt a re-evaluation of previously ascribed pDC involvement in skin disease.

Chen YL; Gomes T; Hardman CS; Vieira Braga FA; Gutowska-Owsiak D; Salimi M; Gray N; Duncan DA; Reynolds G; Johnson D et al

The Journal of experimental medicine 2020;217;3

Peer reviewed
Topics
Healthy Donors, Open Access Data

Distinct microbial and immune niches of the human colon.

Gastrointestinal microbiota and immune cells interact closely and display regional specificity; however, little is known about how these communities differ with location. Here, we simultaneously assess microbiota and single immune cells across the healthy, adult human colon, with paired characterization of immune cells in the mesenteric lymph nodes, to delineate colonic immune niches at steady state. We describe distinct helper T cell activation and migration profiles along the colon and characterize the transcriptional adaptation trajectory of regulatory T cells between lymphoid tissue and colon. Finally, we show increasing B cell accumulation, clonal expansion and mutational frequency from the cecum to the sigmoid colon and link this to the increasing number of reactive bacterial species.

James KR; Gomes T; Elmentaite R; Kumar N; Gulliver EL; King HW; Stares MD; Bareham BR; Ferdinand JR; Petrova VN et al

Nature Immunology 2020;21;3;343-353

Peer reviewed
Topics
Human Subjects, Model Organism Samples, Healthy Donors, Open Access Data

A cell atlas of human thymic development defines T cell repertoire formation.

The thymus provides a nurturing environment for the differentiation and selection of T cells, a process orchestrated by their interaction with multiple thymic cell types. We used single-cell RNA sequencing to create a cell census of the human thymus across the life span and to reconstruct T cell differentiation trajectories and T cell receptor (TCR) recombination kinetics. Using this approach, we identified and located in situ CD8αα T cell populations, thymic fibroblast subtypes, and activated dendritic cell states. In addition, we reveal a bias in TCR recombination and selection, which is attributed to genomic position and the kinetics of lineage commitment. Taken together, our data provide a comprehensive atlas of the human thymus across the life span with new insights into human T cell development.

Park JE; Botting RA; Domínguez Conde C; Popescu DM; Lavaert M; Kunz DJ; Goh I; Stephenson E; Ragazzini R; Tuck E et al

Science 2020;367;6480

Peer reviewed
Topics
Open Access Data, Experimental Methods

Systematic Comparison of High-throughput Single-Cell and Single-Nucleus Transcriptomes during Cardiomyocyte Differentiation.

A comprehensive reference map of all cell types in the human body is necessary for improving our understanding of fundamental biological processes and in diagnosing and treating disease. High-throughput single-cell RNA sequencing techniques have emerged as powerful tools to identify and characterize cell types in complex and heterogeneous tissues. However, extracting intact cells from tissues and organs is often technically challenging or impossible, for example in heart or brain tissue. Single-nucleus RNA sequencing provides an alternative way to obtain transcriptome profiles of such tissues. To systematically assess the differences between high-throughput single-cell and single-nuclei RNA-seq approaches, we compared Drop-seq and DroNc-seq, two microfluidic-based 3' RNA capture technologies that profile total cellular and nuclear RNA, respectively, during a time course experiment of human induced pluripotent stem cells (iPSCs) differentiating into cardiomyocytes. Clustering of time-series transcriptomes from Drop-seq and DroNc-seq revealed six distinct cell types, five of which were found in both techniques. Furthermore, single-cell trajectories reconstructed from both techniques reproduced expected differentiation dynamics. We then applied DroNc-seq to postmortem heart tissue to test its performance on heterogeneous human tissue samples. Our data confirm that DroNc-seq yields similar results to Drop-seq on matched samples and can be successfully used to generate reference maps for the human cell atlas.

Selewa A; Dohn R; Eckart H; Lozano S; Xie B; Gauchat E; Elorbany R; Rhodes K; Burnett J; Gilad Y et al

Scientific reports 2020;10;1;1535

Pre-print
Networks
Oral & Craniofacial
Topics
Human Subjects, Model Organism Samples, Healthy Donors, Open Access Data, Experimental Methods, Computational Methods, COVID-19

Integrated Single-Cell Atlases Reveal an Oral SARS-CoV-2 Infection and Transmission Axis.

Despite signs of infection, the involvement of the oral cavity in COVID-19 is poorly understood. To address this, single-cell RNA sequencing data-sets were integrated from human minor salivary glands and gingiva to identify 11 epithelial, 7 mesenchymal, and 15 immune cell clusters. Analysis of SARS-CoV-2 viral entry factor expression showed enrichment in epithelia including the ducts and acini of the salivary glands and the suprabasal cells of the mucosae. COVID-19 autopsy tissues confirmed in vivo SARS-CoV-2 infection in the salivary glands and mucosa. Saliva from SARS-CoV-2-infected individuals harbored epithelial cells exhibiting expression and SARS-CoV-2 RNA. Matched nasopharyngeal and saliva samples found distinct viral shedding dynamics and viral burden in saliva correlated with COVID-19 symptoms including taste loss. Upon recovery, this cohort exhibited salivary antibodies against SARS-CoV-2 proteins. Collectively, the oral cavity represents a robust site for COVID-19 infection and implicates saliva in viral transmission.

Huang N; Perez P; Kato T; Mikami Y; Okuda K; Gilmore RC; Domínguez Conde C; Gasmi B; Stein S; Beach M et al

medRxiv 2020

Peer reviewed

Toward a Common Coordinate Framework for the Human Body.

Understanding the genetic and molecular drivers of phenotypic heterogeneity across individuals is central to biology. As new technologies enable fine-grained and spatially resolved molecular profiling, we need new computational approaches to integrate data from the same organ across different individuals into a consistent reference and to construct maps of molecular and cellular organization at histological and anatomical scales. Here, we review previous efforts and discuss challenges involved in establishing such a common coordinate framework, the underlying map of tissues and organs. We focus on strategies to handle anatomical variation across individuals and highlight the need for new technologies and analytical methods spanning multiple hierarchical scales of spatial resolution.

Rood JE; Stuart T; Ghazanfar S; Biancalani T; Fisher E; Butler A; Hupalowska A; Gaffney L; Mauck W; Eraslan G et al

Cell 2019;179;7;1455-1467

Peer reviewed
Topics
Human Subjects, Model Organism Samples, Healthy Donors, Disease Donors, Open Access Data, Experimental Methods, Computational Methods

Resolving the fibrotic niche of human liver cirrhosis at single-cell level.

Liver cirrhosis is a major cause of death worldwide and is characterized by extensive fibrosis. There are currently no effective antifibrotic therapies available. To obtain a better understanding of the cellular and molecular mechanisms involved in disease pathogenesis and enable the discovery of therapeutic targets, here we profile the transcriptomes of more than 100,000 single human cells, yielding molecular definitions for non-parenchymal cell types that are found in healthy and cirrhotic human liver. We identify a scar-associated TREM2CD9 subpopulation of macrophages, which expands in liver fibrosis, differentiates from circulating monocytes and is pro-fibrogenic. We also define ACKR1 and PLVAP endothelial cells that expand in cirrhosis, are topographically restricted to the fibrotic niche and enhance the transmigration of leucocytes. Multi-lineage modelling of ligand and receptor interactions between the scar-associated macrophages, endothelial cells and PDGFRα collagen-producing mesenchymal cells reveals intra-scar activity of several pro-fibrogenic pathways including TNFRSF12A, PDGFR and NOTCH signalling. Our work dissects unanticipated aspects of the cellular and molecular basis of human organ fibrosis at a single-cell level, and provides a conceptual framework for the discovery of rational therapeutic targets in liver cirrhosis.

Ramachandran P; Dobie R; Wilson-Kanamori JR; Dora EF; Henderson BEP; Luu NT; Portman JR; Matchett KP; Brice M; Marwick JA et al

Nature 2019;575;7783;512-518

Peer reviewed
Topics
Human Subjects, Healthy Donors, Open Access Data

Decoding human fetal liver haematopoiesis.

Definitive haematopoiesis in the fetal liver supports self-renewal and differentiation of haematopoietic stem cells and multipotent progenitors (HSC/MPPs) but remains poorly defined in humans. Here, using single-cell transcriptome profiling of approximately 140,000 liver and 74,000 skin, kidney and yolk sac cells, we identify the repertoire of human blood and immune cells during development. We infer differentiation trajectories from HSC/MPPs and evaluate the influence of the tissue microenvironment on blood and immune cell development. We reveal physiological erythropoiesis in fetal skin and the presence of mast cells, natural killer and innate lymphoid cell precursors in the yolk sac. We demonstrate a shift in the haemopoietic composition of fetal liver during gestation away from being predominantly erythroid, accompanied by a parallel change in differentiation potential of HSC/MPPs, which we functionally validate. Our integrated map of fetal liver haematopoiesis provides a blueprint for the study of paediatric blood and immune disorders, and a reference for harnessing the therapeutic potential of HSC/MPPs.

Popescu DM; Botting RA; Stephenson E; Green K; Webb S; Jardine L; Calderbank EF; Polanski K; Goh I; Efremova M et al

Nature 2019;574;7778;365-371

Peer reviewed
Topics
Human Subjects, Healthy Donors, Open Access Data

A single-cell transcriptome atlas of the adult human retina.

The retina is a specialized neural tissue that senses light and initiates image processing. Although the functional organization of specific retina cells has been well studied, the molecular profile of many cell types remains unclear in humans. To comprehensively profile the human retina, we performed single-cell RNA sequencing on 20,009 cells from three donors and compiled a reference transcriptome atlas. Using unsupervised clustering analysis, we identified 18 transcriptionally distinct cell populations representing all known neural retinal cells: rod photoreceptors, cone photoreceptors, Müller glia, bipolar cells, amacrine cells, retinal ganglion cells, horizontal cells, astrocytes, and microglia. Our data captured molecular profiles for healthy and putative early degenerating rod photoreceptors, and revealed the loss of MALAT1 expression with longer post-mortem time, which potentially suggested a novel role of MALAT1 in rod photoreceptor degeneration. We have demonstrated the use of this retina transcriptome atlas to benchmark pluripotent stem cell-derived cone photoreceptors and an adult Müller glia cell line. This work provides an important reference with unprecedented insights into the transcriptional landscape of human retinal cells, which is fundamental to understanding retinal biology and disease.

Lukowski SW; Lo CY; Sharov AA; Nguyen Q; Fang L; Hung SS; Zhu L; Zhang T; Grünert U; Nguyen T et al

The EMBO journal 2019;38;18;e100811

Topics
Healthy Donors, Experimental Methods, Computational Methods

Conserved cell types with divergent features in human versus mouse cortex.

Elucidating the cellular architecture of the human cerebral cortex is central to understanding our cognitive abilities and susceptibility to disease. Here we used single-nucleus RNA-sequencing analysis to perform a comprehensive study of cell types in the middle temporal gyrus of human cortex. We identified a highly diverse set of excitatory and inhibitory neuron types that are mostly sparse, with excitatory types being less layer-restricted than expected. Comparison to similar mouse cortex single-cell RNA-sequencing datasets revealed a surprisingly well-conserved cellular architecture that enables matching of homologous types and predictions of properties of human cell types. Despite this general conservation, we also found extensive differences between homologous human and mouse cell types, including marked alterations in proportions, laminar distributions, gene expression and morphology. These species-specific features emphasize the importance of directly studying human brain.

Hodge RD; Bakken TE; Miller JA; Smith KA; Barkan ER; Graybuck LT; Close JL; Long B; Johansen N; Penn O et al

 2019;573;7772

Pre-print
Topics
Human Subjects, Healthy Donors

Lung, spleen and oesophagus tissue remains stable for scRNAseq in cold preservation

bioRxiv - the preprint server for biology, operated by Cold Spring Harbor Laboratory, a research and educational institution

E. Madissoon; A. Wilbrey-Clark; R.J. Miragaia; K. Saeb-Parsy; K. Mahbubani; N. Georgakopoulos; P. Harding; K. Polanski; K. Nowicki-Osuch; R.C. Fitzgerald et al

bioRxiv 2019;741405

Pre-print
Topics
Human Subjects, Healthy Donors, Disease Donors, Experimental Methods, Computational Methods

Rewiring of the cellular and inter-cellular landscape of the human colon during ulcerative colitis

bioRxiv - the preprint server for biology, operated by Cold Spring Harbor Laboratory, a research and educational institution

Christopher S. Smillie; Moshe Biton; Jose Ordovas-Montanes; Keri M. Sullivan; Grace Burgin; Daniel B. Graham; Rebecca H. Herbst; Noga Rogel; Michal Slyper; Julia Waldman et al

bioRxiv 2019;455451

Pre-print
Topics
Human Subjects, Healthy Donors, Disease Donors

Single cell transcriptome atlas of immune cells in human small intestine and in celiac disease

bioRxiv - the preprint server for biology, operated by Cold Spring Harbor Laboratory, a research and educational institution

Nader Atlasy; Anna Bujko; Peter B Brazda; Eva Janssen-Megens; Espen S. Bækkevold; Jørgen Jahnsen; Frode L. Jahnsen; Hendrik G. Stunnenberg

bioRxiv 2019;721258

Peer reviewed
Topics
Human Subjects, Healthy Donors, Disease Donors, Open Access Data, Experimental Methods, Computational Methods

A human liver cell atlas reveals heterogeneity and epithelial progenitors.

The human liver is an essential multifunctional organ. The incidence of liver diseases is rising and there are limited treatment options. However, the cellular composition of the liver remains poorly understood. Here we performed single-cell RNA sequencing of about 10,000 cells from normal liver tissue from nine human donors to construct a human liver cell atlas. Our analysis identified previously unknown subtypes of endothelial cells, Kupffer cells, and hepatocytes, with transcriptome-wide zonation of some of these populations. We show that the EPCAM population is heterogeneous, comprising hepatocyte-biased and cholangiocyte populations as well as a TROP2 progenitor population with strong potential to form bipotent liver organoids. As a proof-of-principle, we used our atlas to unravel the phenotypic changes that occur in hepatocellular carcinoma cells and in human hepatocytes and liver endothelial cells engrafted into a mouse liver. Our human liver cell atlas provides a powerful resource to enable the discovery of previously unknown cell types in normal and diseased livers.

Aizarani N; Saviano A; Sagar ; Mailly L; Durand S; Herman JS; Pessaux P; Baumert TF; Grün D

Nature 2019;572;7768;199-204

Peer reviewed
Topics
Human Subjects, Experimental Methods

Nuclei multiplexing with barcoded antibodies for single-nucleus genomics.

Single-nucleus RNA-seq (snRNA-seq) enables the interrogation of cellular states in complex tissues that are challenging to dissociate or are frozen, and opens the way to human genetics studies, clinical trials, and precise cell atlases of large organs. However, such applications are currently limited by batch effects, processing, and costs. Here, we present an approach for multiplexing snRNA-seq, using sample-barcoded antibodies to uniquely label nuclei from distinct samples. Comparing human brain cortex samples profiled with or without hashing antibodies, we demonstrate that nucleus hashing does not significantly alter recovered profiles. We develop DemuxEM, a computational tool that detects inter-sample multiplets and assigns singlets to their sample of origin, and validate its accuracy using sex-specific gene expression, species-mixing and natural genetic variation. Our approach will facilitate tissue atlases of isogenic model organisms or from multiple biopsies or longitudinal samples of one donor, and large-scale perturbation screens.

Gaublomme JT; Li B; McCabe C; Knecht A; Yang Y; Drokhlyansky E; Van Wittenberghe N; Waldman J; Dionne D; Nguyen L et al

Nature Communications 2019;10;1;2907

Peer reviewed

A cellular census of human lungs identifies novel cell states in health and in asthma

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 (TH2) 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 TH2-dominated interactome in asthmatic lungs. Single-cell transcriptomics reveals immune and stromal compartment remodeling, including the enrichment of unique populations of epithelial cells and CD4+ T cells, in asthmatic lungs

Vieira Braga, Felipe A.; Kar, Gozde; Berg, Marijn; Carpaij, Orestes A.; Polanski, Krzysztof; Simon, Lukas M.; Brouwer, Sharon; Gomes, Tomás; Hesse, Laura; Jiang, Jian et al

Nature Medicine 2019;25;7;1153-1163

Peer reviewed
Topics
Human Subjects, Model Organism Samples, Healthy Donors, Disease Donors, Open Access Data

Single-Cell Transcriptomic Analysis of Human Lung Provides Insights into the Pathobiology of Pulmonary Fibrosis.

The contributions of diverse cell populations in the human lung to pulmonary fibrosis pathogenesis are poorly understood. Single-cell RNA sequencing can reveal changes within individual cell populations during pulmonary fibrosis that are important for disease pathogenesis. To determine whether single-cell RNA sequencing can reveal disease-related heterogeneity within alveolar macrophages, epithelial cells, or other cell types in lung tissue from subjects with pulmonary fibrosis compared with control subjects. We performed single-cell RNA sequencing on lung tissue obtained from eight transplant donors and eight recipients with pulmonary fibrosis and on one bronchoscopic cryobiospy sample from a patient with idiopathic pulmonary fibrosis. We validated these data using RNA hybridization, immunohistochemistry, and bulk RNA-sequencing on flow-sorted cells from 22 additional subjects. We identified a distinct, novel population of profibrotic alveolar macrophages exclusively in patients with fibrosis. Within epithelial cells, the expression of genes involved in Wnt secretion and response was restricted to nonoverlapping cells. We identified rare cell populations including airway stem cells and senescent cells emerging during pulmonary fibrosis. We developed a web-based tool to explore these data. We generated a single-cell atlas of pulmonary fibrosis. Using this atlas, we demonstrated heterogeneity within alveolar macrophages and epithelial cells from subjects with pulmonary fibrosis. These results support the feasibility of discovery-based approaches using next-generation sequencing technologies to identify signaling pathways for targeting in the development of personalized therapies for patients with pulmonary fibrosis.

Reyfman PA; Walter JM; Joshi N; Anekalla KR; McQuattie-Pimentel AC; Chiu S; Fernandez R; Akbarpour M; Chen CI; Ren Z et al

American journal of respiratory and critical care medicine 2019;199;12;1517-1536

Peer reviewed

The Pediatric Cell Atlas: Defining the Growth Phase of Human Development at Single-Cell Resolution.

Single-cell gene expression analyses of mammalian tissues have uncovered profound stage-specific molecular regulatory phenomena that have changed the understanding of unique cell types and signaling pathways critical for lineage determination, morphogenesis, and growth. We discuss here the case for a Pediatric Cell Atlas as part of the Human Cell Atlas consortium to provide single-cell profiles and spatial characterization of gene expression across human tissues and organs. Such data will complement adult and developmentally focused HCA projects to provide a rich cytogenomic framework for understanding not only pediatric health and disease but also environmental and genetic impacts across the human lifespan.

Taylor DM; Aronow BJ; Tan K; Bernt K; Salomonis N; Greene CS; Frolova A; Henrickson SE; Wells A; Pei L et al

Developmental cell 2019;49;1;10-29

Characterization of cell fate probabilities in single-cell data with Palantir.

Single-cell RNA sequencing studies of differentiating systems have raised fundamental questions regarding the discrete versus continuous nature of both differentiation and cell fate. Here we present Palantir, an algorithm that models trajectories of differentiating cells by treating cell fate as a probabilistic process and leverages entropy to measure cell plasticity along the trajectory. Palantir generates a high-resolution pseudo-time ordering of cells and, for each cell state, assigns a probability of differentiating into each terminal state. We apply our algorithm to human bone marrow single-cell RNA sequencing data and detect important landmarks of hematopoietic differentiation. Palantir's resolution enables the identification of key transcription factors that drive lineage fate choice and closely track when cells lose plasticity. We show that Palantir outperforms existing algorithms in identifying cell lineages and recapitulating gene expression trends during differentiation, is generalizable to diverse tissue types, and is well-suited to resolving less-studied differentiating systems.

Setty M; Kiseliovas V; Levine J; Gayoso A; Mazutis L; Pe'er D

 2019;37;4

Peer reviewed

Single cell dissection of plasma cell heterogeneity in symptomatic and asymptomatic myeloma.

Multiple myeloma, a plasma cell malignancy, is the second most common blood cancer. Despite extensive research, disease heterogeneity is poorly characterized, hampering efforts for early diagnosis and improved treatments. Here, we apply single cell RNA sequencing to study the heterogeneity of 40 individuals along the multiple myeloma progression spectrum, including 11 healthy controls, demonstrating high interindividual variability that can be explained by expression of known multiple myeloma drivers and additional putative factors. We identify extensive subclonal structures for 10 of 29 individuals with multiple myeloma. In asymptomatic individuals with early disease and in those with minimal residual disease post-treatment, we detect rare tumor plasma cells with molecular characteristics similar to those of active myeloma, with possible implications for personalized therapies. Single cell analysis of rare circulating tumor cells allows for accurate liquid biopsy and detection of malignant plasma cells, which reflect bone marrow disease. Our work establishes single cell RNA sequencing for dissecting blood malignancies and devising detailed molecular characterization of tumor cells in symptomatic and asymptomatic patients.

Ledergor G; Weiner A; Zada M; Wang SY; Cohen YC; Gatt ME; Snir N; Magen H; Koren-Michowitz M; Herzog-Tzarfati K et al

Nature Medicine 2018;24;12;1867-1876

Peer reviewed

Single-cell reconstruction of the early maternal–fetal interface in humans

During early human pregnancy the uterine mucosa transforms into the decidua, into which the fetal placenta implants and where placental trophoblast cells intermingle and communicate with maternal cells. Trophoblast–decidual interactions underlie common diseases of pregnancy, including pre-eclampsia and stillbirth. Here we profile the transcriptomes of about 70,000 single cells from first-trimester placentas with matched maternal blood and decidual cells. The cellular composition of human decidua reveals subsets of perivascular and stromal cells that are located in distinct decidual layers. There are three major subsets of decidual natural killer cells that have distinctive immunomodulatory and chemokine profiles. We develop a repository of ligand–receptor complexes and a statistical tool to predict the cell-type specificity of cell–cell communication via these molecular interactions. Our data identify many regulatory interactions that prevent harmful innate or adaptive immune responses in this environment. Our single-cell atlas of the maternal–fetal interface reveals the cellular organization of the decidua and placenta, and the interactions that are critical for placentation and reproductive success. Transcriptomes of about 70,000 single cells from first-trimester deciduas and placentas reveal subsets of perivascular, stromal and natural killer cells in the decidua, with distinct immunomodulatory profiles that regulate the environment necessary for successful placentation.

Vento-Tormo, Roser; Efremova, Mirjana; Botting, Rachel A.; Turco, Margherita Y.; Vento-Tormo, Miquel; Meyer, Kerstin B.; Park, Jong-Eun; Stephenson, Emily; Polański, Krzysztof; Goncalves, Angela et al

Nature 2018;563;7731

Peer reviewed

Single cell RNA sequencing of human liver reveals distinct intrahepatic macrophage populations.

The liver is the largest solid organ in the body and is critical for metabolic and immune functions. However, little is known about the cells that make up the human liver and its immune microenvironment. Here we report a map of the cellular landscape of the human liver using single-cell RNA sequencing. We provide the transcriptional profiles of 8444 parenchymal and non-parenchymal cells obtained from the fractionation of fresh hepatic tissue from five human livers. Using gene expression patterns, flow cytometry, and immunohistochemical examinations, we identify 20 discrete cell populations of hepatocytes, endothelial cells, cholangiocytes, hepatic stellate cells, B cells, conventional and non-conventional T cells, NK-like cells, and distinct intrahepatic monocyte/macrophage populations. Together, our study presents a comprehensive view of the human liver at single-cell resolution that outlines the characteristics of resident cells in the liver, and in particular provides a map of the human hepatic immune microenvironment.

MacParland SA; Liu JC; Ma XZ; Innes BT; Bartczak AM; Gage BK; Manuel J; Khuu N; Echeverri J; Linares I et al

Nature Communications 2018;9;1;4383

Pre-print

The Human Cell Atlas White Paper

The Human Cell Atlas (HCA) will be made up of comprehensive reference maps of all human cells - the fundamental units of life - as a basis for understanding fundamental human biological processes and diagnosing, monitoring, and treating disease. It will help scientists understand how genetic variants impact disease risk, define drug toxicities, discover better therapies, and advance regenerative medicine. A resource of such ambition and scale should be built in stages, increasing in size, breadth, and resolution as technologies develop and understanding deepens. We will therefore pursue Phase 1 as a suite of flagship projects in key tissues, systems, and organs. We will bring together experts in biology, medicine, genomics, technology development and computation (including data analysis, software engineering, and visualization). We will also need standardized experimental and computational methods that will allow us to compare diverse cell and tissue types - and samples across human communities - in consistent ways, ensuring that the resulting resource is truly global. This document, the first version of the HCA White Paper, was written by experts in the field with feedback and suggestions from the HCA community, gathered during recent international meetings. The White Paper, released at the close of this yearlong planning process, will be a living document that evolves as the HCA community provides additional feedback, as technological and computational advances are made, and as lessons are learned during the construction of the atlas.

Regev, Aviv; Teichmann, Sarah; Rozenblatt-Rosen, Orit; Stubbington, Michael; Ardlie, Kristin; Amit, Ido; Arlotta, Paola; Bader, Gary; Benoist, Christophe; Biton, Moshe et al

arXiv.org 2018

Peer reviewed
Topics
Model Organism Samples, Healthy Donors, Open Access Data, Computational Methods

Molecular Architecture of the Mouse Nervous System.

The mammalian nervous system executes complex behaviors controlled by specialized, precisely positioned, and interacting cell types. Here, we used RNA sequencing of half a million single cells to create a detailed census of cell types in the mouse nervous system. We mapped cell types spatially and derived a hierarchical, data-driven taxonomy. Neurons were the most diverse and were grouped by developmental anatomical units and by the expression of neurotransmitters and neuropeptides. Neuronal diversity was driven by genes encoding cell identity, synaptic connectivity, neurotransmission, and membrane conductance. We discovered seven distinct, regionally restricted astrocyte types that obeyed developmental boundaries and correlated with the spatial distribution of key glutamate and glycine neurotransmitters. In contrast, oligodendrocytes showed a loss of regional identity followed by a secondary diversification. The resource presented here lays a solid foundation for understanding the molecular architecture of the mammalian nervous system and enables genetic manipulation of specific cell types.

Zeisel A; Hochgerner H; Lönnerberg P; Johnsson A; Memic F; van der Zwan J; Häring M; Braun E; Borm LE; La Manno G et al

Cell 2018;174;4;999-1014.e22

Pre-print

Palantir characterizes cell fate continuities in human hematopoiesis

bioRxiv - the preprint server for biology, operated by Cold Spring Harbor Laboratory, a research and educational institution

Manu Setty; Vaidotas Kiseliovas; Jacob Levine; Adam Gayoso; Linas Mazutis; Dana Pe’er

bioRxiv 2018;385328

Peer reviewed

The Human Cell Atlas.

The recent advent of methods for high-throughput single-cell molecular profiling has catalyzed a growing sense in the scientific community that the time is ripe to complete the 150-year-old effort to identify all cell types in the human body. The Human Cell Atlas Project is an international collaborative effort that aims to define all human cell types in terms of distinctive molecular profiles (such as gene expression profiles) and to connect this information with classical cellular descriptions (such as location and morphology). An open comprehensive reference map of the molecular state of cells in healthy human tissues would propel the systematic study of physiological states, developmental trajectories, regulatory circuitry and interactions of cells, and also provide a framework for understanding cellular dysregulation in human disease. Here we describe the idea, its potential utility, early proofs-of-concept, and some design considerations for the Human Cell Atlas, including a commitment to open data, code, and community.

Regev A; Teichmann SA; Lander ES; Amit I; Benoist C; Birney E; Bodenmiller B; Campbell P; Carninci P; Clatworthy M et al

eLife 2017;6

Peer reviewed

The Human Cell Atlas: from vision to reality.

Rozenblatt-Rosen O; Stubbington MJT; Regev A; Teichmann SA

Nature 2017;550;7677;451-453

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