Single-Cell Profiling of Ebola Virus Disease In Vivo Reveals Viral and Host Dynamics.

Ebola virus (EBOV) causes epidemics with high mortality yet remains understudied due to the challenge of experimentation in high-containment and outbreak settings. Here, we used single-cell transcriptomics and CyTOF-based single-cell protein quantification to characterize peripheral immune cells during EBOV infection in rhesus monkeys. We obtained 100,000 transcriptomes and 15,000,000 protein profiles, finding that immature, proliferative monocyte-lineage cells with reduced antigen-presentation capacity replace conventional monocyte subsets, while lymphocytes upregulate apoptosis genes and decline in abundance. By quantifying intracellular viral RNA, we identify molecular determinants of tropism among circulating immune cells and examine temporal dynamics in viral and host gene expression. Within infected cells, EBOV downregulates STAT1 mRNA and interferon signaling, and it upregulates putative pro-viral genes (e.g., DYNLL1 and HSPA5), nominating pathways the virus manipulates for its replication. This study sheds light on EBOV tropism, replication dynamics, and elicited immune response and provides a framework for characterizing host-virus interactions under maximum containment.

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.

Single-Cell RNA-Seq Reveals AML Hierarchies Relevant to Disease Progression and Immunity.

Acute myeloid leukemia (AML) is a heterogeneous disease that resides within a complex microenvironment, complicating efforts to understand how different cell types contribute to disease progression. We combined single-cell RNA sequencing and genotyping to profile 38,410 cells from 40 bone marrow aspirates, including 16 AML patients and five healthy donors. We then applied a machine learning classifier to distinguish a spectrum of malignant cell types whose abundances varied between patients and between subclones in the same tumor. Cell type compositions correlated with prototypic genetic lesions, including an association of FLT3-ITD with abundant progenitor-like cells. Primitive AML cells exhibited dysregulated transcriptional programs with co-expression of stemness and myeloid priming genes and had prognostic significance. Differentiated monocyte-like AML cells expressed diverse immunomodulatory genes and suppressed T cell activity in vitro. In conclusion, we provide single-cell technologies and an atlas of AML cell states, regulators, and markers with implications for precision medicine and immune therapies. VIDEO ABSTRACT.

The cellular architecture of the antimicrobial response network in human leprosy granulomas.

Granulomas are complex cellular structures composed predominantly of macrophages and lymphocytes that function to contain and kill invading pathogens. Here, we investigated the single-cell phenotypes associated with antimicrobial responses in human leprosy granulomas by applying single-cell and spatial sequencing to leprosy biopsy specimens. We focused on reversal reactions (RRs), a dynamic process whereby some patients with disseminated lepromatous leprosy (L-lep) transition toward self-limiting tuberculoid leprosy (T-lep), mounting effective antimicrobial responses. We identified a set of genes encoding proteins involved in antimicrobial responses that are differentially expressed in RR versus L-lep lesions and regulated by interferon-γ and interleukin-1ß. By integrating the spatial coordinates of the key cell types and antimicrobial gene expression in RR and T-lep lesions, we constructed a map revealing the organized architecture of granulomas depicting compositional and functional layers by which macrophages, T cells, keratinocytes and fibroblasts can each contribute to the antimicrobial response.

Multimodal profiling of lung granulomas in macaques reveals cellular correlates of tuberculosis control.

Mycobacterium tuberculosis lung infection results in a complex multicellular structure: the granuloma. In some granulomas, immune activity promotes bacterial clearance, but in others, bacteria persist and grow. We identified correlates of bacterial control in cynomolgus macaque lung granulomas by co-registering longitudinal positron emission tomography and computed tomography imaging, single-cell RNA sequencing, and measures of bacterial clearance. Bacterial persistence occurred in granulomas enriched for mast, endothelial, fibroblast, and plasma cells, signaling amongst themselves via type 2 immunity and wound-healing pathways. Granulomas that drove bacterial control were characterized by cellular ecosystems enriched for type 1-type 17, stem-like, and cytotoxic T cells engaged in pro-inflammatory signaling networks involving diverse cell populations. Granulomas that arose later in infection displayed functional characteristics of restrictive granulomas and were more capable of killing Mtb. Our results define the complex multicellular ecosystems underlying (lack of) granuloma resolution and highlight host immune targets that can be leveraged to develop new vaccine and therapeutic strategies for TB.

Second-Strand Synthesis-Based Massively Parallel scRNA-Seq Reveals Cellular States and Molecular Features of Human Inflammatory Skin Pathologies.

High-throughput single-cell RNA-sequencing (scRNA-seq) methodologies enable characterization of complex biological samples by increasing the number of cells that can be profiled contemporaneously. Nevertheless, these approaches recover less information per cell than low-throughput strategies. To accurately report the expression of key phenotypic features of cells, scRNA-seq platforms are needed that are both high fidelity and high throughput. To address this need, we created Seq-Well S3 ("Second-Strand Synthesis"), a massively parallel scRNA-seq protocol that uses a randomly primed second-strand synthesis to recover complementary DNA (cDNA) molecules that were successfully reverse transcribed but to which a second oligonucleotide handle, necessary for subsequent whole transcriptome amplification, was not appended due to inefficient template switching. Seq-Well S3 increased the efficiency of transcript capture and gene detection compared with that of previous iterations by up to 10- and 5-fold, respectively. We used Seq-Well S3 to chart the transcriptional landscape of five human inflammatory skin diseases, thus providing a resource for the further study of human skin inflammation.

Prevention of tuberculosis in macaques after intravenous BCG immunization.

Mycobacterium tuberculosis (Mtb) is the leading cause of death from infection worldwide1. The only available vaccine, BCG (Bacillus Calmette-Guérin), is given intradermally and has variable efficacy against pulmonary tuberculosis, the major cause of mortality and disease transmission1,2. Here we show that intravenous administration of BCG profoundly alters the protective outcome of Mtb challenge in non-human primates (Macaca mulatta). Compared with intradermal or aerosol delivery, intravenous immunization induced substantially more antigen-responsive CD4 and CD8 T cell responses in blood, spleen, bronchoalveolar lavage and lung lymph nodes. Moreover, intravenous immunization induced a high frequency of antigen-responsive T cells across all lung parenchymal tissues. Six months after BCG vaccination, macaques were challenged with virulent Mtb. Notably, nine out of ten macaques that received intravenous BCG vaccination were highly protected, with six macaques showing no detectable levels of infection, as determined by positron emission tomography-computed tomography imaging, mycobacterial growth, pathology and granuloma formation. The finding that intravenous BCG prevents or substantially limits Mtb infection in highly susceptible rhesus macaques has important implications for vaccine delivery and clinical development, and provides a model for defining immune correlates and mechanisms of vaccine-elicited protection against tuberculosis.

Single-Cell RNA Sequencing Reveals That Adaptation of Human Aortic Endothelial Cells to Antiproliferative Therapies Is Modulated by Flow-Induced Shear Stress.

BACKGROUND: Endothelial cells (ECs) are capable of quickly responding in a coordinated manner to a wide array of stresses to maintain vascular homeostasis. Loss of EC cellular adaptation may be a potential marker for cardiovascular disease and a predictor of poor response to endovascular pharmacological interventions such as drug-eluting stents. Here, we report single-cell transcriptional profiling of ECs exposed to multiple stimulus classes to evaluate EC adaptation. METHODS: Human aortic ECs were costimulated with both pathophysiological flows mimicking shear stress levels found in the human aorta (laminar and turbulent, ranging from 2.5 to 30 dynes/cm2) and clinically relevant antiproliferative drugs, namely paclitaxel and rapamycin. EC state in response to these stimuli was defined using single-cell RNA sequencing. RESULTS: We identified differentially expressed genes and inferred the TF (transcription factor) landscape modulated by flow shear stress using single-cell RNA sequencing. These flow-sensitive markers differentiated previously identified spatially distinct subpopulations of ECs in the murine aorta. Moreover, distinct transcriptional modules defined flow- and drug-responsive EC adaptation singly and in combination. Flow shear stress was the dominant driver of EC state, altering their response to pharmacological therapies. CONCLUSIONS: We showed that flow shear stress modulates the cellular capacity of ECs to respond to paclitaxel and rapamycin administration, suggesting that while responding to different flow patterns, ECs experience an impairment in their transcriptional adaptation to other stimuli.

Allergic inflammatory memory in human respiratory epithelial progenitor cells.

Barrier tissue dysfunction is a fundamental feature of chronic human inflammatory diseases1. Specialized subsets of epithelial cells-including secretory and ciliated cells-differentiate from basal stem cells to collectively protect the upper airway2-4. Allergic inflammation can develop from persistent activation5 of type 2 immunity6 in the upper airway, resulting in chronic rhinosinusitis, which ranges in severity from rhinitis to severe nasal polyps7. Basal cell hyperplasia is a hallmark of severe disease7-9, but it is not known how these progenitor cells2,10,11 contribute to clinical presentation and barrier tissue dysfunction in humans. Here we profile primary human surgical chronic rhinosinusitis samples (18,036 cells, n = 12) that span the disease spectrum using Seq-Well for massively parallel single-cell RNA sequencing12, report transcriptomes for human respiratory epithelial, immune and stromal cell types and subsets from a type 2 inflammatory disease, and map key mediators. By comparison with nasal scrapings (18,704 cells, n = 9), we define signatures of core, healthy, inflamed and polyp secretory cells. We reveal marked differences between the epithelial compartments of the non-polyp and polyp cellular ecosystems, identifying and validating a global reduction in cellular diversity of polyps characterized by basal cell hyperplasia, concomitant decreases in glandular cells, and phenotypic shifts in secretory cell antimicrobial expression. We detect an aberrant basal progenitor differentiation trajectory in polyps, and propose cell-intrinsic13, epigenetic14,15 and extrinsic factors11,16,17 that lock polyp basal cells into this uncommitted state. Finally, we functionally demonstrate that ex vivo cultured basal cells retain intrinsic memory of IL-4/IL-13 exposure, and test the potential for clinical blockade of the IL-4 receptor α-subunit to modify basal and secretory cell states in vivo. Overall, we find that reduced epithelial diversity stemming from functional shifts in basal cells is a key characteristic of type 2 immune-mediated barrier tissue dysfunction. Our results demonstrate that epithelial stem cells may contribute to the persistence of human disease by serving as repositories for allergic memories.

Seq-Well: portable, low-cost RNA sequencing of single cells at high throughput.

Single-cell RNA-seq can precisely resolve cellular states, but applying this method to low-input samples is challenging. Here, we present Seq-Well, a portable, low-cost platform for massively parallel single-cell RNA-seq. Barcoded mRNA capture beads and single cells are sealed in an array of subnanoliter wells using a semipermeable membrane, enabling efficient cell lysis and transcript capture. We use Seq-Well to profile thousands of primary human macrophages exposed to Mycobacterium tuberculosis.

Harnessing single-cell genomics to improve the physiological fidelity of organoid-derived cell types.

BACKGROUND: Single-cell genomic methods now provide unprecedented resolution for characterizing the component cell types and states of tissues such as the epithelial subsets of the gastrointestinal tract. Nevertheless, functional studies of these subsets at scale require faithful in vitro models of identified in vivo biology. While intestinal organoids have been invaluable in providing mechanistic insights in vitro, the extent to which organoid-derived cell types recapitulate their in vivo counterparts remains formally untested, with no systematic approach for improving model fidelity. RESULTS: Here, we present a generally applicable framework that utilizes massively parallel single-cell RNA-seq to compare cell types and states found in vivo to those of in vitro models such as organoids. Furthermore, we leverage identified discrepancies to improve model fidelity. Using the Paneth cell (PC), which supports the stem cell niche and produces the largest diversity of antimicrobials in the small intestine, as an exemplar, we uncover fundamental gene expression differences in lineage-defining genes between in vivo PCs and those of the current in vitro organoid model. With this information, we nominate a molecular intervention to rationally improve the physiological fidelity of our in vitro PCs. We then perform transcriptomic, cytometric, morphologic and proteomic characterization, and demonstrate functional (antimicrobial activity, niche support) improvements in PC physiology. CONCLUSIONS: Our systematic approach provides a simple workflow for identifying the limitations of in vitro models and enhancing their physiological fidelity. Using adult stem cell-derived PCs within intestinal organoids as a model system, we successfully benchmark organoid representation, relative to that in vivo, of a specialized cell type and use this comparison to generate a functionally improved in vitro PC population. We predict that the generation of rationally improved cellular models will facilitate mechanistic exploration of specific disease-associated genes in their respective cell types.

Protective intravenous BCG vaccination induces enhanced immune signaling in the airways.

Intradermal (ID) Bacillus Calmette-Guérin (BCG) is the most widely administered vaccine in the world. However, ID-BCG fails to achieve the level of protection needed in adults to alter the course of the tuberculosis epidemic. Recent studies in non-human primates have demonstrated high levels of protection against Mycobacterium tuberculosis ( Mtb ) following intravenous (IV) administration of BCG. However, the protective immune features that emerge following IV BCG vaccination remain incompletely defined. Here we used single-cell RNA-sequencing (scRNAseq) to transcriptionally profile 157,114 unstimulated and purified protein derivative (PPD)-stimulated bronchoalveolar lavage (BAL) cells from 29 rhesus macaques immunized with BCG across routes of administration and doses to uncover cell composition-, gene expression-, and biological network-level signatures associated with IV BCG-mediated protection. Our analyses revealed that high-dose IV BCG drove an influx of polyfunctional T cells and macrophages into the airways. These macrophages exhibited a basal activation phenotype even in the absence of PPD-stimulation, defined in part by IFN and TNF-α signaling up to 6 months following BCG immunization. Furthermore, intercellular immune signaling pathways between key myeloid and T cell subsets were enhanced following PPD-stimulation in high-dose IV BCG-vaccinated macaques. High-dose IV BCG also engendered quantitatively and qualitatively stronger transcriptional responses to PPD-stimulation, with a robust Th1-Th17 transcriptional phenotype in T cells, and augmented transcriptional signatures of reactive oxygen species production, hypoxia, and IFN-γ response within alveolar macrophages. Collectively, this work supports that IV BCG immunization creates a unique cellular ecosystem in the airways, which primes and enables local myeloid cells to effectively clear Mtb upon challenge.

Continuous genomic diversification of long polynucleotide fragments drives the emergence of new SARS-CoV-2 variants of concern.

Highly transmissible or immuno-evasive SARS-CoV-2 variants have intermittently emerged, resulting in repeated COVID-19 surges. With over 6 million SARS-CoV-2 genomes sequenced, there is unprecedented data to decipher the evolution of fitter SARS-CoV-2 variants. Much attention has been directed to studying the functional importance of specific mutations in the Spike protein, but there is limited knowledge of genomic signatures shared by dominant variants. Here, we introduce a method to quantify the genome-wide distinctiveness of polynucleotide fragments (3- to 240-mers) that constitute SARS-CoV-2 sequences. Compared to standard phylogenetic metrics and mutational load, the new metric provides improved separation between Variants of Concern (VOCs; Reference = 89, IQR: 65-108; Alpha = 166, IQR: 149-181; Beta 131, IQR: 114-149; Gamma = 164, IQR: 150-178; Delta = 235, IQR: 217-255; and Omicron = 459, IQR: 395-521). Omicron's high genomic distinctiveness may confer an advantage over prior VOCs and the recently emerged and highly mutated B.1.640.2 (IHU) lineage. Evaluation of 883 lineages highlights that genomic distinctiveness has increased over time (R 2 = 0.37) and that VOCs score significantly higher than contemporary non-VOC lineages, with Omicron among the most distinctive lineages observed. This study demonstrates the value of characterizing SARS-CoV-2 variants by genome-wide polynucleotide distinctiveness and emphasizes the need to go beyond a narrow set of mutations at known sites on the Spike protein. The consistently higher distinctiveness of each emerging VOC compared to prior VOCs suggests that monitoring of genomic distinctiveness would facilitate rapid assessment of viral fitness.

A single-cell liver atlas of Plasmodium vivax infection.

Malaria-causing Plasmodium vivax parasites can linger in the human liver for weeks to years and reactivate to cause recurrent blood-stage infection. Although they are an important target for malaria eradication, little is known about the molecular features of replicative and non-replicative intracellular liver-stage parasites and their host cell dependence. Here, we leverage a bioengineered human microliver platform to culture patient-derived P. vivax parasites for transcriptional profiling. Coupling enrichment strategies with bulk and single-cell analyses, we capture both parasite and host transcripts in individual hepatocytes throughout the course of infection. We define host- and state-dependent transcriptional signatures and identify unappreciated populations of replicative and non-replicative parasites that share features with sexual transmissive forms. We find that infection suppresses the transcription of key hepatocyte function genes and elicits an anti-parasite innate immune response. Our work provides a foundation for understanding host-parasite interactions and reveals insights into the biology of P. vivax dormancy and transmission.

Single-cell profiling of environmental enteropathy reveals signatures of epithelial remodeling and immune activation.

Environmental enteropathy (EE) is a subclinical condition of the small intestine that is highly prevalent in low- and middle-income countries. It is thought to be a key contributing factor to childhood malnutrition, growth stunting, and diminished oral vaccine responses. Although EE has been shown to be the by-product of a recurrent enteric infection, its full pathophysiology remains unclear. Here, we mapped the cellular and molecular correlates of EE by performing high-throughput, single-cell RNA-sequencing on 33 small intestinal biopsies from 11 adults with EE in Lusaka, Zambia (eight HIV-negative and three HIV-positive), six adults without EE in Boston, United States, and two adults in Durban, South Africa, which we complemented with published data from three additional individuals from the same clinical site. We analyzed previously defined bulk-transcriptomic signatures of reduced villus height and decreased microbial translocation in EE and showed that these signatures may be driven by an increased abundance of surface mucosal cells-a gastric-like subset previously implicated in epithelial repair in the gastrointestinal tract. In addition, we determined cell subsets whose fractional abundances associate with EE severity, small intestinal region, and HIV infection. Furthermore, by comparing duodenal EE samples with those from three control cohorts, we identified dysregulated WNT and MAPK signaling in the EE epithelium and increased proinflammatory cytokine gene expression in a T cell subset highly expressing a transcriptional signature of tissue-resident memory cells in the EE cohort. Together, our work elucidates epithelial and immune correlates of EE and nominates cellular and molecular targets for intervention.

Alveolar macrophages in early stage COPD show functional deviations with properties of impaired immune activation.

Despite its high prevalence, the cellular and molecular mechanisms of chronic obstructive pulmonary disease (COPD) are far from being understood. Here, we determine disease-related changes in cellular and molecular compositions within the alveolar space and peripheral blood of a cohort of COPD patients and controls. Myeloid cells were the largest cellular compartment in the alveolar space with invading monocytes and proliferating macrophages elevated in COPD. Modeling cell-to-cell communication, signaling pathway usage, and transcription factor binding predicts TGF-ß1 to be a major upstream regulator of transcriptional changes in alveolar macrophages of COPD patients. Functionally, macrophages in COPD showed reduced antigen presentation capacity, accumulation of cholesteryl ester, reduced cellular chemotaxis, and mitochondrial dysfunction, reminiscent of impaired immune activation.

A Literature-Derived Knowledge Graph Augments the Interpretation of Single Cell RNA-seq Datasets.

Technology to generate single cell RNA-sequencing (scRNA-seq) datasets and tools to annotate them have advanced rapidly in the past several years. Such tools generally rely on existing transcriptomic datasets or curated databases of cell type defining genes, while the application of scalable natural language processing (NLP) methods to enhance analysis workflows has not been adequately explored. Here we deployed an NLP framework to objectively quantify associations between a comprehensive set of over 20,000 human protein-coding genes and over 500 cell type terms across over 26 million biomedical documents. The resultant gene-cell type associations (GCAs) are significantly stronger between a curated set of matched cell type-marker pairs than the complementary set of mismatched pairs (Mann Whitney p = 6.15 × 10-76, r = 0.24; cohen's D = 2.6). Building on this, we developed an augmented annotation algorithm (single cell Annotation via Literature Encoding, or scALE) that leverages GCAs to categorize cell clusters identified in scRNA-seq datasets, and we tested its ability to predict the cellular identity of 133 clusters from nine datasets of human breast, colon, heart, joint, ovary, prostate, skin, and small intestine tissues. With the optimized settings, the true cellular identity matched the top prediction in 59% of tested clusters and was present among the top five predictions for 91% of clusters. scALE slightly outperformed an existing method for reference data driven automated cluster annotation, and we demonstrate that integration of scALE can meaningfully improve the annotations derived from such methods. Further, contextualization of differential expression analyses with these GCAs highlights poorly characterized markers of well-studied cell types, such as CLIC6 and DNASE1L3 in retinal pigment epithelial cells and endothelial cells, respectively. Taken together, this study illustrates for the first time how the systematic application of a literature-derived knowledge graph can expedite and enhance the annotation and interpretation of scRNA-seq data.

Human airway mast cells proliferate and acquire distinct inflammation-driven phenotypes during type 2 inflammation.

Mast cells (MCs) play a pathobiologic role in type 2 (T2) allergic inflammatory diseases of the airway, including asthma and chronic rhinosinusitis with nasal polyposis (CRSwNP). Distinct MC subsets infiltrate the airway mucosa in T2 disease, including subepithelial MCs expressing the proteases tryptase and chymase (MCTC) and epithelial MCs expressing tryptase without chymase (MCT). However, mechanisms underlying MC expansion and the transcriptional programs underlying their heterogeneity are poorly understood. Here, we use flow cytometry and single-cell RNA-sequencing (scRNA-seq) to conduct a comprehensive analysis of human MC hyperplasia in CRSwNP, a T2 cytokine-mediated inflammatory disease. We link discrete cell surface phenotypes to the distinct transcriptomes of CRSwNP MCT and MCTC, which represent polarized ends of a transcriptional gradient of nasal polyp MCs. We find a subepithelial population of CD38highCD117high MCs that is markedly expanded during T2 inflammation. These CD38highCD117high MCs exhibit an intermediate phenotype relative to the expanded MCT and MCTC subsets. CD38highCD117high MCs are distinct from circulating MC progenitors and are enriched for proliferation, which is markedly increased in CRSwNP patients with aspirin-exacerbated respiratory disease, a severe disease subset characterized by increased MC burden and elevated MC activation. We observe that MCs expressing a polyp MCT-like effector program are also found within the lung during fibrotic diseases and asthma, and further identify marked differences between MCTC in nasal polyps and skin. These results indicate that MCs display distinct inflammation-associated effector programs and suggest that in situ MC proliferation is a major component of MC hyperplasia in human T2 inflammation.

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.

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

An amendment to this paper has been published and can be accessed via a link at the top of the paper.