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.

Direct Identification of Hundreds of Expression-Modulating Variants using a Multiplexed Reporter Assay.

Although studies have identified hundreds of loci associated with human traits and diseases, pinpointing causal alleles remains difficult, particularly for non-coding variants. To address this challenge, we adapted the massively parallel reporter assay (MPRA) to identify variants that directly modulate gene expression. We applied it to 32,373 variants from 3,642 cis-expression quantitative trait loci and control regions. Detection by MPRA was strongly correlated with measures of regulatory function. We demonstrate MPRA's capabilities for pinpointing causal alleles, using it to identify 842 variants showing differential expression between alleles, including 53 well-annotated variants associated with diseases and traits. We investigated one in detail, a risk allele for ankylosing spondylitis, and provide direct evidence of a non-coding variant that alters expression of the prostaglandin EP4 receptor. These results create a resource of concrete leads and illustrate the promise of this approach for comprehensively interrogating how non-coding polymorphism shapes human biology.

Integration of genomic data enables selective discovery of breast cancer drivers.

Identifying driver genes in cancer remains a crucial bottleneck in therapeutic development and basic understanding of the disease. We developed Helios, an algorithm that integrates genomic data from primary tumors with data from functional RNAi screens to pinpoint driver genes within large recurrently amplified regions of DNA. Applying Helios to breast cancer data identified a set of candidate drivers highly enriched with known drivers (p < 10(-14)). Nine of ten top-scoring Helios genes are known drivers of breast cancer, and in vitro validation of 12 candidates predicted by Helios found ten conferred enhanced anchorage-independent growth, demonstrating Helios's exquisite sensitivity and specificity. We extensively characterized RSF-1, a driver identified by Helios whose amplification correlates with poor prognosis, and found increased tumorigenesis and metastasis in mouse models. We have demonstrated a powerful approach for identifying driver genes and how it can yield important insights into cancer.

Three linked variants have opposing regulatory effects on isovaleryl-CoA dehydrogenase gene expression.

While genome-wide association studies (GWAS) and positive selection scans identify genomic loci driving human phenotypic diversity, functional validation is required to discover the variant(s) responsible. We dissected the IVD gene locus-which encodes the isovaleryl-CoA dehydrogenase enzyme-implicated by selection statistics, multiple GWAS, and clinical genetics as important to function and fitness. We combined luciferase assays, CRISPR/Cas9 genome-editing, massively parallel reporter assays (MPRA), and a deletion tiling MPRA strategy across regulatory loci. We identified three regulatory variants, including an indel, that may underpin GWAS signals for pulmonary fibrosis and testosterone, and that are linked on a positively selected haplotype in the Japanese population. These regulatory variants exhibit synergistic and opposing effects on IVD expression experimentally. Alleles at these variants lie on a haplotype tagged by the variant most strongly associated with IVD expression and metabolites, but with no functional evidence itself. This work demonstrates how comprehensive functional investigation and multiple technologies are needed to discover the true genetic drivers of phenotypic diversity.

An integrated approach to uncover drivers of cancer.

Systematic characterization of cancer genomes has revealed a staggering number of diverse aberrations that differ among individuals, such that the functional importance and physiological impact of most tumor genetic alterations remain poorly defined. We developed a computational framework that integrates chromosomal copy number and gene expression data for detecting aberrations that promote cancer progression. We demonstrate the utility of this framework using a melanoma data set. Our analysis correctly identified known drivers of melanoma and predicted multiple tumor dependencies. Two dependencies, TBC1D16 and RAB27A, confirmed empirically, suggest that abnormal regulation of protein trafficking contributes to proliferation in melanoma. Together, these results demonstrate the ability of integrative Bayesian approaches to identify candidate drivers with biological, and possibly therapeutic, importance in cancer.

Nonablative Fractional Laser Treatment Is Associated With a Decreased Risk of Subsequent Facial Keratinocyte Carcinoma Development.

BACKGROUND: Keratinocyte carcinoma (KC) is the most common type of nonmelanoma skin cancer. Currently, prophylactic treatment options are limited. Nonablative fractional lasers (NAFL) have received the Food and Drug Administration approval for the treatment of actinic damage; however, their role in KC prophylaxis is not known. OBJECTIVE: The aim of this study is to determine whether NAFL treatment is associated with a decrease in subsequent facial KC development. MATERIALS AND METHODS: A retrospective cohort study of patients with a history of facial KC treated at the Massachusetts General Hospital Dermatology Laser and Cosmetic Center between 2005 and 2021 was conducted. RESULTS: Forty-three NAFL-treated patients with a history of facial KC and 52 matched control subjects were included in the study. The rate of subsequent facial KC development was 20.9% in NAFL-treated patients and 40.4% in control subjects (RR 0.52, p = .049). Control subjects developed new facial KC significantly sooner than NAFL-treated patients (p = .033). When controlling for age, gender, and skin type, control subjects were more likely to develop new facial KC than NAFL-treated patients (hazard ratio 2.65, p = .0169). CONCLUSION: NAFL treatment was associated with a decreased risk of subsequent facial KC development and may have a benefit for KC prophylaxis.

Sciviewer enables interactive visual interrogation of single-cell RNA-Seq data from the Python programming environment.

MOTIVATION: Visualizing two-dimensional embeddings (such as UMAP or tSNE) is a useful step in interrogating single-cell RNA sequencing (scRNA-Seq) data. Subsequently, users typically iterate between programmatic analyses (including clustering and differential expression) and visual exploration (e.g. coloring cells by interesting features) to uncover biological signals in the data. Interactive tools exist to facilitate visual exploration of embeddings such as performing differential expression on user-selected cells. However, the practical utility of these tools is limited because they don't support rapid movement of data and results to and from the programming environments where most of the data analysis takes place, interrupting the iterative process. RESULTS: Here, we present the Single-cell Interactive Viewer (Sciviewer), a tool that overcomes this limitation by allowing interactive visual interrogation of embeddings from within Python. Beyond differential expression analysis of user-selected cells, Sciviewer implements a novel method to identify genes varying locally along any user-specified direction on the embedding. Sciviewer enables rapid and flexible iteration between interactive and programmatic modes of scRNA-Seq exploration, illustrating a useful approach for analyzing high-dimensional data. AVAILABILITY AND IMPLEMENTATION: Code and examples are provided at https://github.com/colabobio/sciviewer.

High crossreactivity of human T cell responses between Lassa virus lineages.

Lassa virus infects hundreds of thousands of people each year across rural West Africa, resulting in a high number of cases of Lassa fever (LF), a febrile disease associated with high morbidity and significant mortality. The lack of approved treatments or interventions underscores the need for an effective vaccine. At least four viral lineages circulate in defined regions throughout West Africa with substantial interlineage nucleotide and amino acid diversity. An effective vaccine should be designed to elicit Lassa virus specific humoral and cell mediated immunity across all lineages. Most current vaccine candidates use only lineage IV antigens encoded by Lassa viruses circulating around Sierra Leone, Liberia, and Guinea but not Nigeria where lineages I-III are found. As previous infection is known to protect against disease from subsequent exposure, we sought to determine whether LF survivors from Nigeria and Sierra Leone harbor memory T cells that respond to lineage IV antigens. Our results indicate a high degree of cross-reactivity of CD8+ T cells from Nigerian LF survivors to lineage IV antigens. In addition, we identified regions within the Lassa virus glycoprotein complex and nucleoprotein that contributed to these responses while T cell epitopes were not widely conserved across our study group. These data are important for current efforts to design effective and efficient vaccine candidates that can elicit protective immunity across all Lassa virus lineages.

Genomic Analysis of Lassa Virus during an Increase in Cases in Nigeria in 2018.

During 2018, an unusual increase in Lassa fever cases occurred in Nigeria, raising concern among national and international public health agencies. We analyzed 220 Lassa virus genomes from infected patients, including 129 from the 2017-2018 transmission season, to understand the viral populations underpinning the increase. A total of 14 initial genomes from 2018 samples were generated at Redeemer's University in Nigeria, and the findings were shared with the Nigerian Center for Disease Control in real time. We found that the increase in cases was not attributable to a particular Lassa virus strain or sustained by human-to-human transmission. Instead, the data were consistent with ongoing cross-species transmission from local rodent populations. Phylogenetic analysis also revealed extensive viral diversity that was structured according to geography, with major rivers appearing to act as barriers to migration of the rodent reservoir.

Identification of Common CD8+ T Cell Epitopes from Lassa Fever Survivors in Nigeria and Sierra Leone.

Early and robust T cell responses have been associated with survival from Lassa fever (LF), but the Lassa virus-specific memory responses have not been well characterized. Regions within the virus surface glycoprotein (GPC) and nucleoprotein (NP) are the main targets of the Lassa virus-specific T cell responses, but, to date, only a few T cell epitopes within these proteins have been identified. We identified GPC and NP regions containing T cell epitopes and HLA haplotypes from LF survivors and used predictive HLA-binding algorithms to identify putative epitopes, which were then experimentally tested using autologous survivor samples. We identified 12 CD8-positive (CD8+) T cell epitopes, including epitopes common to both Nigerian and Sierra Leonean survivors. These data should be useful for the identification of dominant Lassa virus-specific T cell responses in Lassa fever survivors and vaccinated individuals as well as for designing vaccines that elicit cell-mediated immunity.IMPORTANCE The high morbidity and mortality associated with clinical cases of Lassa fever, together with the lack of licensed vaccines and limited and partially effective interventions, make Lassa virus (LASV) an important health concern in its regions of endemicity in West Africa. Previous infection with LASV protects from disease after subsequent exposure, providing a framework for designing vaccines to elicit similar protective immunity. Multiple major lineages of LASV circulate in West Africa, and therefore, ideal vaccine candidates should elicit immunity to all lineages. We therefore sought to identify common T cell epitopes between Lassa fever survivors from Sierra Leone and Nigeria, where distinct lineages circulate. We identified three such epitopes derived from highly conserved regions within LASV proteins. In this process, we also identified nine other T cell epitopes. These data should help in the design of an effective pan-LASV vaccine.

Analysis of CD8+ T cell response during the 2013-2016 Ebola epidemic in West Africa.

The recent Ebola epidemic exemplified the importance of understanding and controlling emerging infections. Despite the importance of T cells in clearing virus during acute infection, little is known about Ebola-specific CD8+ T cell responses. We investigated immune responses of individuals infected with Ebola virus (EBOV) during the 2013-2016 West Africa epidemic in Sierra Leone, where the majority of the >28,000 EBOV disease (EVD) cases occurred. We examined T cell memory responses to seven of the eight Ebola proteins (GP, sGP, NP, VP24, VP30, VP35, and VP40) and associated HLA expression in survivors. Of the 30 subjects included in our analysis, CD8+ T cells from 26 survivors responded to at least one EBOV antigen. A minority, 10 of 26 responders (38%), made CD8+ T cell responses to the viral GP or sGP. In contrast, 25 of the 26 responders (96%) made response to viral NP, 77% to VP24 (20 of 26), 69% to VP40 (18 of 26), 42% (11 of 26) to VP35, with no response to VP30. Individuals making CD8+ T cells to EBOV VP24, VP35, and VP40 also made CD8+ T cells to NP, but rarely to GP. We identified 34 CD8+ T cell epitopes for Ebola. Our data indicate the immunodominance of the EBOV NP-specific T cell response and suggest that its inclusion in a vaccine along with the EBOV GP would best mimic survivor responses and help boost cell-mediated immunity during vaccination.

Integrated single-cell genetic and transcriptional analysis suggests novel drivers of chronic lymphocytic leukemia.

Intra-tumoral genetic heterogeneity has been characterized across cancers by genome sequencing of bulk tumors, including chronic lymphocytic leukemia (CLL). In order to more accurately identify subclones, define phylogenetic relationships, and probe genotype-phenotype relationships, we developed methods for targeted mutation detection in DNA and RNA isolated from thousands of single cells from five CLL samples. By clearly resolving phylogenic relationships, we uncovered mutated LCP1 and WNK1 as novel CLL drivers, supported by functional evidence demonstrating their impact on CLL pathways. Integrative analysis of somatic mutations with transcriptional states prompts the idea that convergent evolution generates phenotypically similar cells in distinct genetic branches, thus creating a cohesive expression profile in each CLL sample despite the presence of genetic heterogeneity. Our study highlights the potential for single-cell RNA-based targeted analysis to sensitively determine transcriptional and mutational profiles of individual cancer cells, leading to increased understanding of driving events in malignancy.

Reproducible single cell annotation of programs underlying T-cell subsets, activation states, and functions.

T-cells recognize antigens and induce specialized gene expression programs (GEPs) enabling functions including proliferation, cytotoxicity, and cytokine production. Traditionally, different classes of helper T-cells express mutually exclusive responses - for example, Th1, Th2, and Th17 programs. However, new single-cell RNA sequencing (scRNA-Seq) experiments have revealed a continuum of T-cell states without discrete clusters corresponding to these subsets, implying the need for new analytical frameworks. Here, we advance the characterization of T-cells with T-CellAnnoTator (TCAT), a pipeline that simultaneously quantifies pre-defined GEPs capturing activation states and cellular subsets. From 1,700,000 T-cells from 700 individuals across 38 tissues and five diverse disease contexts, we discover 46 reproducible GEPs reflecting the known core functions of T-cells including proliferation, cytotoxicity, exhaustion, and T helper effector states. We experimentally characterize several novel activation programs and apply TCAT to describe T-cell activation and exhaustion in Covid-19 and cancer, providing insight into T-cell function in these diseases.

Genome-wide association study identifies human genetic variants associated with fatal outcome from Lassa fever.

Infection with Lassa virus (LASV) can cause Lassa fever, a haemorrhagic illness with an estimated fatality rate of 29.7%, but causes no or mild symptoms in many individuals. Here, to investigate whether human genetic variation underlies the heterogeneity of LASV infection, we carried out genome-wide association studies (GWAS) as well as seroprevalence surveys, human leukocyte antigen typing and high-throughput variant functional characterization assays. We analysed Lassa fever susceptibility and fatal outcomes in 533 cases of Lassa fever and 1,986 population controls recruited over a 7 year period in Nigeria and Sierra Leone. We detected genome-wide significant variant associations with Lassa fever fatal outcomes near GRM7 and LIF in the Nigerian cohort. We also show that a haplotype bearing signatures of positive selection and overlapping LARGE1, a required LASV entry factor, is associated with decreased risk of Lassa fever in the Nigerian cohort but not in the Sierra Leone cohort. Overall, we identified variants and genes that may impact the risk of severe Lassa fever, demonstrating how GWAS can provide insight into viral pathogenesis.

Natural history of Ebola virus disease in rhesus monkeys shows viral variant emergence dynamics and tissue-specific host responses.

Ebola virus (EBOV) causes Ebola virus disease (EVD), marked by severe hemorrhagic fever; however, the mechanisms underlying the disease remain unclear. To assess the molecular basis of EVD across time, we performed RNA sequencing on 17 tissues from a natural history study of 21 rhesus monkeys, developing new methods to characterize host-pathogen dynamics. We identified alterations in host gene expression with previously unknown tissue-specific changes, including downregulation of genes related to tissue connectivity. EBOV was widely disseminated throughout the body; using a new, broadly applicable deconvolution method, we found that viral load correlated with increased monocyte presence. Patterns of viral variation between tissues differentiated primary infections from compartmentalized infections, and several variants impacted viral fitness in a EBOV/Kikwit minigenome system, suggesting that functionally significant variants can emerge during early infection. This comprehensive portrait of host-pathogen dynamics in EVD illuminates new features of pathogenesis and establishes resources to study other emerging pathogens.

Identifying gene expression programs of cell-type identity and cellular activity with single-cell RNA-Seq.

Identifying gene expression programs underlying both cell-type identity and cellular activities (e.g. life-cycle processes, responses to environmental cues) is crucial for understanding the organization of cells and tissues. Although single-cell RNA-Seq (scRNA-Seq) can quantify transcripts in individual cells, each cell's expression profile may be a mixture of both types of programs, making them difficult to disentangle. Here, we benchmark and enhance the use of matrix factorization to solve this problem. We show with simulations that a method we call consensus non-negative matrix factorization (cNMF) accurately infers identity and activity programs, including their relative contributions in each cell. To illustrate the insights this approach enables, we apply it to published brain organoid and visual cortex scRNA-Seq datasets; cNMF refines cell types and identifies both expected (e.g. cell cycle and hypoxia) and novel activity programs, including programs that may underlie a neurosecretory phenotype and synaptogenesis.

Detecting genome-wide directional effects of transcription factor binding on polygenic disease risk.

Biological interpretation of genome-wide association study data frequently involves assessing whether SNPs linked to a biological process, for example, binding of a transcription factor, show unsigned enrichment for disease signal. However, signed annotations quantifying whether each SNP allele promotes or hinders the biological process can enable stronger statements about disease mechanism. We introduce a method, signed linkage disequilibrium profile regression, for detecting genome-wide directional effects of signed functional annotations on disease risk. We validate the method via simulations and application to molecular quantitative trait loci in blood, recovering known transcriptional regulators. We apply the method to expression quantitative trait loci in 48 Genotype-Tissue Expression tissues, identifying 651 transcription factor-tissue associations including 30 with robust evidence of tissue specificity. We apply the method to 46 diseases and complex traits (average n = 290 K), identifying 77 annotation-trait associations representing 12 independent transcription factor-trait associations, and characterize the underlying transcriptional programs using gene-set enrichment analyses. Our results implicate new causal disease genes and new disease mechanisms.

Field validation of recombinant antigen immunoassays for diagnosis of Lassa fever.

Lassa fever, a hemorrhagic fever caused by Lassa virus (LASV), is endemic in West Africa. It is difficult to distinguish febrile illnesses that are common in West Africa from Lassa fever based solely on a patient's clinical presentation. The field performance of recombinant antigen-based Lassa fever immunoassays was compared to that of quantitative polymerase chain assays (qPCRs) using samples from subjects meeting the case definition of Lassa fever presenting to Kenema Government Hospital in Sierra Leone. The recombinant Lassa virus (ReLASV) enzyme-linked immunosorbant assay (ELISA) for detection of viral antigen in blood performed with 95% sensitivity and 97% specificity using a diagnostic standard that combined results of the immunoassays and qPCR. The ReLASV rapid diagnostic test (RDT), a lateral flow immunoassay based on paired monoclonal antibodies to the Josiah strain of LASV (lineage IV), performed with 90% sensitivity and 100% specificity. ReLASV immunoassays performed better than the most robust qPCR currently available, which had 82% sensitivity and 95% specificity. The performance characteristics of recombinant antigen-based Lassa virus immunoassays indicate that they can aid in the diagnosis of LASV Infection and inform the clinical management of Lassa fever patients.

Transcriptomic Characterization of SF3B1 Mutation Reveals Its Pleiotropic Effects in Chronic Lymphocytic Leukemia.

Mutations in SF3B1, which encodes a spliceosome component, are associated with poor outcome in chronic lymphocytic leukemia (CLL), but how these contribute to CLL progression remains poorly understood. We undertook a transcriptomic characterization of primary human CLL cells to identify transcripts and pathways affected by SF3B1 mutation. Splicing alterations, identified in the analysis of bulk cells, were confirmed in single SF3B1-mutated CLL cells and also found in cell lines ectopically expressing mutant SF3B1. SF3B1 mutation was found to dysregulate multiple cellular functions including DNA damage response, telomere maintenance, and Notch signaling (mediated through KLF8 upregulation, increased TERC and TERT expression, or altered splicing of DVL2 transcript, respectively). SF3B1 mutation leads to diverse changes in CLL-related pathways.