Impaired local intrinsic immunity to SARS-CoV-2 infection in severe COVID-19.

SARS-CoV-2 infection can cause severe respiratory COVID-19. However, many individuals present with isolated upper respiratory symptoms, suggesting potential to constrain viral pathology to the nasopharynx. Which cells SARS-CoV-2 primarily targets and how infection influences the respiratory epithelium remains incompletely understood. We performed scRNA-seq on nasopharyngeal swabs from 58 healthy and COVID-19 participants. During COVID-19, we observe expansion of secretory, loss of ciliated, and epithelial cell repopulation via deuterosomal cell expansion. In mild and moderate COVID-19, epithelial cells express anti-viral/interferon-responsive genes, while cells in severe COVID-19 have muted anti-viral responses despite equivalent viral loads. SARS-CoV-2 RNA+ host-target cells are highly heterogenous, including developing ciliated, interferon-responsive ciliated, AZGP1high goblet, and KRT13+ "hillock"-like cells, and we identify genes associated with susceptibility, resistance, or infection response. Our study defines protective and detrimental responses to SARS-CoV-2, the direct viral targets of infection, and suggests that failed nasal epithelial anti-viral immunity may underlie and precede severe COVID-19.

Cellular and transcriptional diversity over the course of human lactation.

Human breast milk (hBM) is a dynamic fluid that contains millions of cells, but their identities and phenotypic properties are poorly understood. We generated and analyzed single-cell RNA-sequencing (scRNA-seq) data to characterize the transcriptomes of cells from hBM across lactational time from 3 to 632 d postpartum in 15 donors. We found that the majority of cells in hBM are lactocytes, a specialized epithelial subset, and that cell-type frequencies shift over the course of lactation, yielding greater epithelial diversity at later points. Analysis of lactocytes reveals a continuum of cell states characterized by transcriptional changes in hormone-, growth factor-, and milk production-related pathways. Generalized additive models suggest that one subcluster, LC1 epithelial cells, increases as a function of time postpartum, daycare attendance, and the use of hormonal birth control. We identify several subclusters of macrophages in hBM that are enriched for tolerogenic functions, possibly playing a role in protecting the mammary gland during lactation. Our description of the cellular components of breast milk, their association with maternal­infant dyad metadata, and our quantification of alterations at the gene and pathway levels provide a detailed longitudinal picture of hBM cells across lactational time. This work paves the way for future investigations of how a potential division of cellular labor and differential hormone regulation might be leveraged therapeutically to support healthy lactation and potentially aid in milk production.

Loss of DNA methyltransferase activity in primed human ES cells triggers increased cell-cell variability and transcriptional repression.

Maintenance of pluripotency and specification towards a new cell fate are both dependent on precise interactions between extrinsic signals and transcriptional and epigenetic regulators. Directed methylation of cytosines by the de novo methyltransferases DNMT3A and DNMT3B plays an important role in facilitating proper differentiation, whereas DNMT1 is essential for maintaining global methylation levels in all cell types. Here, we generated single-cell mRNA expression data from wild-type, DNMT3A, DNMT3A/3B and DNMT1 knockout human embryonic stem cells and observed a widespread increase in cellular and transcriptional variability, even with limited changes in global methylation levels in the de novo knockouts. Furthermore, we found unexpected transcriptional repression upon either loss of the de novo methyltransferase DNMT3A or the double knockout of DNMT3A/3B that is further propagated upon differentiation to mesoderm and ectoderm. Taken together, our single-cell RNA-sequencing data provide a high-resolution view into the consequences of depleting the three catalytically active DNMTs in human pluripotent stem cells.

Single-cell transcriptomics of staged oocytes and somatic cells reveal novel regulators of follicle activation.

In brief: Proper development of ovarian follicles, comprised of an oocyte and surrounding somatic cells, is essential to support female fertility and endocrine health. Here, we describe a method to isolate single oocytes and somatic cells from the earliest stage follicles, called primordial follicles, and we characterize signals that drive their activation. Abstract: Primordial follicles are the first class of follicles formed in the mammalian ovary and are comprised of an oocyte surrounded by a layer of squamous pre-granulosa cells. This developmental class remains in a non-growing state until individual follicles activate to initiate folliculogenesis. What regulates the timing of follicle activation and the upstream signals that govern these processes are major unanswered questions in ovarian biology. This is partly due to the paucity of data on staged follicle cells since isolating and manipulating individual oocytes and somatic cells from early follicle stages are challenging. To date, most studies on isolated primordial follicles have been conducted on cells collected from animal-age- or oocyte size-specific samples, which encompass multiple follicular stages. Here, we report a method for collecting primordial follicles and their associated oocytes and somatic cells from neonatal murine ovaries using liberase, DNase I, and Accutase. This methodology allows for the identification and collection of follicles immediately post-activation enabling unprecedented interrogation of the primordial-to-primary follicle transition. Molecular profiling by single-cell RNA sequencing revealed that processes including organelle disassembly and cadherin binding were enriched in oocytes and somatic cells as they transitioned from primordial to the primary follicle stage. Furthermore, targets including WNT4, TGFB1, FOXO3, and a network of transcription factors were identified in the transitioning oocytes and somatic cells as potential upstream regulators that collectively may drive follicle activation. Taken together, we have developed a more precise characterization and selection method for studying staged-follicle cells, revealing several novel regulators of early folliculogenesis.

Optofluidic real-time cell sorter for longitudinal CTC studies in mouse models of cancer.

Circulating tumor cells (CTCs) play a fundamental role in cancer progression. However, in mice, limited blood volume and the rarity of CTCs in the bloodstream preclude longitudinal, in-depth studies of these cells using existing liquid biopsy techniques. Here, we present an optofluidic system that continuously collects fluorescently labeled CTCs from a genetically engineered mouse model (GEMM) for several hours per day over multiple days or weeks. The system is based on a microfluidic cell sorting chip connected serially to an unanesthetized mouse via an implanted arteriovenous shunt. Pneumatically controlled microfluidic valves capture CTCs as they flow through the device, and CTC-depleted blood is returned back to the mouse via the shunt. To demonstrate the utility of our system, we profile CTCs isolated longitudinally from animals over 4 days of treatment with the BET inhibitor JQ1 using single-cell RNA sequencing (scRNA-Seq) and show that our approach eliminates potential biases driven by intermouse heterogeneity that can occur when CTCs are collected across different mice. The CTC isolation and sorting technology presented here provides a research tool to help reveal details of how CTCs evolve over time, allowing studies to credential changes in CTCs as biomarkers of drug response and facilitating future studies to understand the role of CTCs in metastasis.

Follicle-intrinsic and spatially distinct molecular programs drive follicle rupture and luteinization during ex vivo mammalian ovulation.

During ovulation, the apical wall of the preovulatory follicle breaks down to facilitate gamete release. In parallel, the residual follicle wall differentiates into a progesterone-producing corpus luteum. Disruption of ovulation, whether through contraceptive intervention or infertility, has implications for women's health. In this study, we harness the power of an ex vivo ovulation model and machine-learning guided microdissection to identify differences between the ruptured and unruptured sides of the follicle wall. We demonstrate that the unruptured side exhibits clear markers of luteinization after ovulation while the ruptured side exhibits cell death signals. RNA-sequencing of individual follicle sides reveals 2099 differentially expressed genes (DEGs) between follicle sides without ovulation induction, and 1673 DEGs 12 h after induction of ovulation. Our model validates molecular patterns consistent with known ovulation biology even though this process occurs in the absence of the ovarian stroma, vasculature, and immune cells. We further identify previously unappreciated pathways including amino acid transport and Jag-Notch signaling on the ruptured side and glycolysis, metal ion processing, and IL-11 signaling on the unruptured side of the follicle. This study yields key insights into follicle-inherent, spatially-defined pathways that underlie follicle rupture, which may further understanding of ovulation physiology and advance women's health.

An enhanced IL17 and muted type I interferon nasal epithelial cell state characterizes severe COVID-19 with fungal coinfection.

Recent case reports and epidemiological data suggest that fungal infections represent an underappreciated complication among people with severe COVID-19. However, the frequency of fungal colonization in patients with COVID-19 and associations with specific immune responses in the airways remain incompletely defined. We previously generated a single-cell RNA-sequencing data set characterizing the upper respiratory microenvironment during COVID-19 and mapped the relationship between disease severity and the local behavior of nasal epithelial cells and infiltrating immune cells. Our previous study, in agreement with findings from related human cohorts, demonstrated that a profound deficiency in host immunity, particularly in type I and type III interferon signaling in the upper respiratory tract, is associated with rapid progression to severe disease and worse clinical outcomes. We have now performed further analysis of this cohort and identified a subset of participants with severe COVID-19 and concurrent detection of Candida species-derived transcripts within samples collected from the nasopharynx and trachea. Here, we present the clinical characteristics of these individuals. Using matched single-cell transcriptomic profiles of these individuals' respiratory mucosa, we identify epithelial immune signatures suggestive of IL17 stimulation and anti-fungal immunity. Further, we observe a significant expression of anti-fungal inflammatory cascades in the nasal and tracheal epithelium of all participants who went on to develop severe COVID-19, even among participants without detectable genetic material from fungal pathogens. Together, our data suggest that IL17 stimulation-in part driven by Candida colonization-and blunted interferon signaling represent a common feature of severe COVID-19 infection. IMPORTANCE: In this paper, we present an analysis suggesting that symptomatic and asymptomatic fungal coinfections can impact patient disease progression during COVID-19 hospitalization. By looking into the presence of other pathogens and their effect on the host immune response during COVID-19 hospitalizations, we aim to offer insight into an underestimated scenario, furthering our current knowledge of determinants of severity that could be considered for future diagnostic and intervention strategies.

Profiling Transcriptional Heterogeneity with Seq-Well S3: A Low-Cost, Portable, High-Fidelity Platform for Massively Parallel Single-Cell RNA-Seq.

Seq-Well is a high-throughput, picowell-based single-cell RNA-seq technology that can be used to simultaneously profile the transcriptomes of thousands of cells (Gierahn et al. Nat Methods 14(4):395-398, 2017). Relative to its reverse-emulsion-droplet-based counterparts, Seq-Well addresses key cost, portability, and scalability limitations. Recently, we introduced an improved molecular biology for Seq-Well to enhance the information content that can be captured from individual cells using the platform. This update, which we call Seq-Well S3 (S3: Second-Strand Synthesis), incorporates a second-strand-synthesis step after reverse transcription to boost the detection of cellular transcripts normally missed when running the original Seq-Well protocol (Hughes et al. Immunity 53(4):878-894.e7, 2020). This chapter provides details and tips on how to perform Seq-Well S3, along with general pointers on how to subsequently analyze the resultant single-cell RNA-seq data.

Severe COVID-19 is associated with fungal colonization of the nasopharynx and potent induction of IL-17 responses in the nasal epithelium.

Recent case reports and epidemiological data suggest fungal infections represent an under-appreciated complication among people with severe COVID-19. However, the frequency of fungal colonization in patients with COVID-19 and associations with specific immune responses in the airways remain incompletely defined. We previously generated a single-cell RNA-sequencing (scRNA-seq) dataset characterizing the upper respiratory microenvironment during COVID-19, and mapped the relationship between disease severity and the local behavior of nasal epithelial cells and infiltrating immune cells. Our study, in agreement with findings from related human cohorts, demonstrated that a profound deficiency in host immunity, particularly in type I and type III interferon signaling in the upper respiratory tract, is associated with rapid progression to severe disease and worse clinical outcomes. We have now performed further analysis of this cohort and identified a subset of participants with severe COVID-19 and concurrent detection of Candida species-derived transcripts within samples collected from the nasopharynx and trachea. Here, we present the clinical characteristics of these individuals, including confirmatory diagnostic testing demonstrating elevated serum (1, 3)-ß-D-glucan and/or confirmed fungal culture of the predicted pathogen. Using matched single-cell transcriptomic profiles of these individuals' respiratory mucosa, we identify epithelial immune signatures suggestive of IL-17 stimulation and anti-fungal immunity. Further, we observe significant expression of anti-fungal inflammatory cascades in the nasal and tracheal epithelium of all participants who went on to develop severe COVID-19, even among participants without detectable genetic material from fungal pathogens. Together, our data suggests that IL-17 stimulation - in part driven by Candida colonization - and blunted type I/III interferon signaling represents a common feature of severe COVID-19 infection.

Leukocyte dynamics after intracerebral hemorrhage in a living patient reveal rapid adaptations to tissue milieu.

Intracerebral hemorrhage (ICH) is a devastating form of stroke with a high mortality rate and few treatment options. Discovery of therapeutic interventions has been slow given the challenges associated with studying acute injury in the human brain. Inflammation induced by exposure of brain tissue to blood appears to be a major part of brain tissue injury. Here, we longitudinally profiled blood and cerebral hematoma effluent from a patient enrolled in the Minimally Invasive Surgery with Thrombolysis in Intracerebral Hemorrhage Evacuation trial, offering a rare window into the local and systemic immune responses to acute brain injury. Using single-cell RNA-Seq (scRNA-Seq), this is the first report to our knowledge that characterized the local cellular response during ICH in the brain of a living patient at single-cell resolution. Our analysis revealed shifts in the activation states of myeloid and T cells in the brain over time, suggesting that leukocyte responses are dynamically reshaped by the hematoma microenvironment. Interestingly, the patient had an asymptomatic rebleed that our transcriptional data indicated occurred prior to detection by CT scan. This case highlights the rapid immune dynamics in the brain after ICH and suggests that sensitive methods such as scRNA-Seq would enable greater understanding of complex intracerebral events.

Longitudinal transcriptomics define the stages of myeloid activation in the living human brain after intracerebral hemorrhage.

Opportunities to interrogate the immune responses in the injured tissue of living patients suffering from acute sterile injuries such as stroke and heart attack are limited. We leveraged a clinical trial of minimally invasive neurosurgery for patients with intracerebral hemorrhage (ICH), a severely disabling subtype of stroke, to investigate the dynamics of inflammation at the site of brain injury over time. Longitudinal transcriptional profiling of CD14+ monocytes/macrophages and neutrophils from hematomas of patients with ICH revealed that the myeloid response to ICH within the hematoma is distinct from that in the blood and occurs in stages conserved across the patient cohort. Initially, hematoma myeloid cells expressed a robust anabolic proinflammatory profile characterized by activation of hypoxia-inducible factors (HIFs) and expression of genes encoding immune factors and glycolysis. Subsequently, inflammatory gene expression decreased over time, whereas anti-inflammatory circuits were maintained and phagocytic and antioxidative pathways up-regulated. During this transition to immune resolution, glycolysis gene expression and levels of the potent proresolution lipid mediator prostaglandin E2 remained elevated in the hematoma, and unexpectedly, these elevations correlated with positive patient outcomes. Ex vivo activation of human macrophages by ICH-associated stimuli highlighted an important role for HIFs in production of both inflammatory and anti-inflammatory factors, including PGE2, which, in turn, augmented VEGF production. Our findings define the time course of myeloid activation in the human brain after ICH, revealing a conserved progression of immune responses from proinflammatory to proresolution states in humans after brain injury and identifying transcriptional programs associated with neurological recovery.

Impaired local intrinsic immunity to SARS-CoV-2 infection in severe COVID-19.

Infection with SARS-CoV-2, the virus that causes COVID-19, can lead to severe lower respiratory illness including pneumonia and acute respiratory distress syndrome, which can result in profound morbidity and mortality. However, many infected individuals are either asymptomatic or have isolated upper respiratory symptoms, which suggests that the upper airways represent the initial site of viral infection, and that some individuals are able to largely constrain viral pathology to the nasal and oropharyngeal tissues. Which cell types in the human nasopharynx are the primary targets of SARS-CoV-2 infection, and how infection influences the cellular organization of the respiratory epithelium remains incompletely understood. Here, we present nasopharyngeal samples from a cohort of 35 individuals with COVID-19, representing a wide spectrum of disease states from ambulatory to critically ill, as well as 23 healthy and intubated patients without COVID-19. Using standard nasopharyngeal swabs, we collected viable cells and performed single-cell RNA-sequencing (scRNA-seq), simultaneously profiling both host and viral RNA. We find that following infection with SARS-CoV-2, the upper respiratory epithelium undergoes massive reorganization: secretory cells diversify and expand, and mature epithelial cells are preferentially lost. Further, we observe evidence for deuterosomal cell and immature ciliated cell expansion, potentially representing active repopulation of lost ciliated cells through coupled secretory cell differentiation. Epithelial cells from participants with mild/moderate COVID-19 show extensive induction of genes associated with anti-viral and type I interferon responses. In contrast, cells from participants with severe lower respiratory symptoms appear globally muted in their anti-viral capacity, despite substantially higher local inflammatory myeloid populations and equivalent nasal viral loads. This suggests an essential role for intrinsic, local epithelial immunity in curbing and constraining viral-induced pathology. Using a custom computational pipeline, we characterized cell-associated SARS-CoV-2 RNA and identified rare cells with RNA intermediates strongly suggestive of active replication. Both within and across individuals, we find remarkable diversity and heterogeneity among SARS-CoV-2 RNA+ host cells, including developing/immature and interferon-responsive ciliated cells, KRT13+ "hillock"-like cells, and unique subsets of secretory, goblet, and squamous cells. Finally, SARS-CoV-2 RNA+ cells, as compared to uninfected bystanders, are enriched for genes involved in susceptibility (e.g., CTSL, TMPRSS2) or response (e.g., MX1, IFITM3, EIF2AK2) to infection. Together, this work defines both protective and detrimental host responses to SARS-CoV-2, determines the direct viral targets of infection, and suggests that failed anti-viral epithelial immunity in the nasal mucosa may underlie the progression to severe COVID-19.

Linking single-cell measurements of mass, growth rate, and gene expression.

Mass and growth rate are highly integrative measures of cell physiology not discernable via genomic measurements. Here, we introduce a microfluidic platform enabling direct measurement of single-cell mass and growth rate upstream of highly multiplexed single-cell profiling such as single-cell RNA sequencing. We resolve transcriptional signatures associated with single-cell mass and growth rate in L1210 and FL5.12 cell lines and activated CD8+ T cells. Further, we demonstrate a framework using these linked measurements to characterize biophysical heterogeneity in a patient-derived glioblastoma cell line with and without drug treatment. Our results highlight the value of coupled phenotypic metrics in guiding single-cell genomics.