Single-cell profiling of tuberculosis lung granulomas reveals functional lymphocyte signatures of bacterial control [preprint]

In humans and nonhuman primates, Mycobacterium tuberculosis lung infection yields a complex multicellular structure—the tuberculosis granuloma. All granulomas are not equivalent, however, even within the same host: in some, local immune activity promotes bacterial clearance, while in others, it allows persistence or outgrowth. Here, we used single-cell RNA-sequencing to define holistically cellular responses associated with control in cynomolgus macaques. Granulomas that facilitated bacterial killing contained significantly higher proportions of CD4+ and CD8+ T cells expressing hybrid Type1-Type17 immune responses or stem-like features and CD8-enriched T cells with specific cytotoxic functions; failure to control correlated with mast cell, plasma cell and fibroblast abundance. Co-registering these data with serial PET-CT imaging suggests that a degree of early immune control can be achieved through cytotoxic activity, but that more robust restriction only arises after the priming of specific adaptive immune responses, defining new targets for vaccination and treatment

Preparation of Single-Cell RNA-Seq Libraries for Next Generation Sequencing

For the past several decades, due to technical limitations, the field of transcriptomics has focused on population-level measurements that can mask significant differences between individual cells. With the advent of single-cell RNA-Seq, it is now possible to profile the responses of individual cells at unprecedented depth and thereby uncover, transcriptome-wide, the heterogeneity that exists within these populations. This unit describes a method that merges several important technologies to produce, in high-throughput, single-cell RNA-Seq libraries. Complementary DNA (cDNA) is made from full-length mRNA transcripts using a reverse transcriptase that has terminal transferase activity. This, when combined with a second “template-switch” primer, allows for cDNAs to be constructed that have two universal priming sequences. Following preamplification from these common sequences, Nextera XT is used to prepare a pool of 96 uniquely indexed samples ready for Illumina sequencing.National Institutes of Health (U.S.) (Centers of Excellence in Genomic Science 1P50HG006193-01)National Institutes of Health (U.S.) (Pioneer Award DP1OD003958-01)Broad Institute of MIT and HarvardHoward Hughes Medical InstituteKlarman Cell Observator

Deciphering molecular circuits from genetic variation underlying transcriptional responsiveness to stimuli

Individual genetic variation affects gene expression in response to stimuli, often by influencing complex molecular circuits. Here we combine genomic and intermediate-scale transcriptional profiling with computational methods to identify variants that affect the responsiveness of genes to stimuli (responsiveness QTLs; reQTLs) and to position these variants in molecular circuit diagrams. We apply this approach to study variation in transcriptional responsiveness to pathogen components in dendritic cells from recombinant inbred mouse strains. We identify reQTLs that correlate with particular stimuli and position them in known pathways. For example, in response to a virus-like stimulus, a trans-acting variant acts as an activator of the antiviral response; using RNAi, we identify Rgs16 as the likely causal gene. Our approach charts an experimental and analytic path to decipher the mechanisms underlying genetic variation in circuits that control responses to stimuli

Single-cell analysis of upper airway cells reveals host-viral dynamics in influenza infected adults [preprint]

Influenza virus infections are major causes of morbidity and mortality. Research using cultured cells, bulk tissue, and animal models cannot fully capture human disease dynamics. Many aspects of virus-host interactions in a natural setting remain unclear, including the specific cell types that are infected and how they and neighboring bystander cells contribute to the overall antiviral response. To address these questions, we performed single-cell RNA sequencing (scRNA-Seq) on cells from freshly collected nasal washes from healthy human donors and donors diagnosed with acute influenza during the 2017-18 season. We describe a previously uncharacterized goblet cell population, specific to infected individuals, with high expression of MHC class II genes. Furthermore, leveraging scRNA-Seq reads, we obtained deep viral genome coverage and developed a model to rigorously identify infected cells that detected influenza infection in all epithelial cell types and even some immune cells. Our data revealed that each donor was infected by a unique influenza variant and that each variant was separated by at least one unique non-synonymous difference. Our results demonstrate the power of massively-parallel scRNA-Seq to study viral variation, as well as host and viral transcriptional activity during human infection

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

MAST: a flexible statistical framework for assessing transcriptional changes and characterizing heterogeneity in single-cell RNA sequencing data

Single-cell transcriptomics reveals gene expression heterogeneity but suffers from stochastic dropout and characteristic bimodal expression distributions in which expression is either strongly non-zero or non-detectable. We propose a two-part, generalized linear model for such bimodal data that parameterizes both of these features. We argue that the cellular detection rate, the fraction of genes expressed in a cell, should be adjusted for as a source of nuisance variation. Our model provides gene set enrichment analysis tailored to single-cell data. It provides insights into how networks of co-expressed genes evolve across an experimental treatment. MAST is available at https://github.com/RGLab/MAST

Single-cell RNA-seq highlights intratumoral heterogeneity in primary glioblastoma

Human cancers are complex ecosystems composed of cells with distinct phenotypes, genotypes, and epigenetic states, but current models do not adequately reflect tumor composition in patients. We used single-cell RNA sequencing (RNA-seq) to profile 430 cells from five primary glioblastomas, which we found to be inherently variable in their expression of diverse transcriptional programs related to oncogenic signaling, proliferation, complement/immune response, and hypoxia. We also observed a continuum of stemness-related expression states that enabled us to identify putative regulators of stemness in vivo. Finally, we show that established glioblastoma subtype classifiers are variably expressed across individual cells within a tumor and demonstrate the potential prognostic implications of such intratumoral heterogeneity. Thus, we reveal previously unappreciated heterogeneity in diverse regulatory programs central to glioblastoma biology, prognosis, and therapy.National Institutes of Health (U.S.) (U24 CA180922

Single-cell transcriptomics reveals bimodality in expression and splicing in immune cells

Recent molecular studies have shown that, even when derived from a seemingly homogenous population, individual cells can exhibit substantial differences in gene expression, protein levels and phenotypic output1, 2, 3, 4, 5, with important functional consequences4, 5. Existing studies of cellular heterogeneity, however, have typically measured only a few pre-selected RNAs1, 2 or proteins5, 6 simultaneously, because genomic profiling methods3 could not be applied to single cells until very recently7, 8, 9, 10. Here we use single-cell RNA sequencing to investigate heterogeneity in the response of mouse bone-marrow-derived dendritic cells (BMDCs) to lipopolysaccharide. We find extensive, and previously unobserved, bimodal variation in messenger RNA abundance and splicing patterns, which we validate by RNA-fluorescence in situ hybridization for select transcripts. In particular, hundreds of key immune genes are bimodally expressed across cells, surprisingly even for genes that are very highly expressed at the population average. Moreover, splicing patterns demonstrate previously unobserved levels of heterogeneity between cells. Some of the observed bimodality can be attributed to closely related, yet distinct, known maturity states of BMDCs; other portions reflect differences in the usage of key regulatory circuits. For example, we identify a module of 137 highly variable, yet co-regulated, antiviral response genes. Using cells from knockout mice, we show that variability in this module may be propagated through an interferon feedback circuit, involving the transcriptional regulators Stat2 and Irf7. Our study demonstrates the power and promise of single-cell genomics in uncovering functional diversity between cells and in deciphering cell states and circuits.National Institutes of Health (U.S.) (NIH Postdoctoral Fellowship (1F32HD075541-01))Charles H. Hood Foundation (Postdoctoral Fellowship)National Institutes of Health (U.S.) (NIH grant U54 AI057159)National Institutes of Health (U.S.) (NIH New Innovator Award (DP2 OD002230))National Institutes of Health (U.S.) (NIH CEGS Award (1P50HG006193-01))National Institutes of Health (U.S.) (NIH Pioneer Awards (5DP1OD003893-03))National Institutes of Health (U.S.) (NIH Pioneer Awards (DP1OD003958-01))Broad Institute of MIT and HarvardBroad Institute of MIT and Harvard (Klarman Cell Observatory

Innate Lymphoid Cell Activation and Sustained Depletion in Blood and Tissue of Children Infected with HIV from Birth Despite Antiretroviral Therapy

Innate lymphoid cells (ILCs) are important for response to infection and for immune development in early life. HIV infection in adults depletes circulating ILCs, but the impact on children infected from birth remains unknown. We study vertically HIV-infected children from birth to adulthood and find severe and persistent depletion of all circulating ILCs that, unlike CD4+ T cells, are not restored by long-term antiretroviral therapy unless initiated at birth. Remaining ILCs upregulate genes associated with cellular activation and metabolic perturbation. Unlike HIV-infected adults, ILCs are also profoundly depleted in tonsils of vertically infected children. Transcriptional profiling of remaining ILCs reveals ongoing cell-type-specific activity despite antiretroviral therapy. Collectively, these data suggest an important and ongoing role for ILCs in lymphoid tissue of HIV-infected children from birth, where persistent depletion and sustained transcriptional activity are likely to have long-term immune consequences that merit further investigation

Seq-Well: A Portable, Low-Cost Platform for High-Throughput Single-Cell RNA-Seq of Low-Input Samples

Single-cell RNA-Seq can precisely resolve cellular states but application to sparse 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 semi-permeable membrane, enabling efficient cell lysis and transcript capture. We characterize Seq-Well using species-mixing experiments and PBMCs, and profile thousands of primary human macrophages exposed to tuberculosis