Systematically characterizing the roles of E3-ligase family members in inflammatory responses with massively parallel Perturb-seq.

E3 ligases regulate key processes, but many of their roles remain unknown. Using Perturb-seq, we interrogated the function of 1,130 E3 ligases, partners and substrates in the inflammatory response in primary dendritic cells (DCs). Dozens impacted the balance of DC1, DC2, migratory DC and macrophage states and a gradient of DC maturation. Family members grouped into co-functional modules that were enriched for physical interactions and impacted specific programs through substrate transcription factors. E3s and their adaptors co-regulated the same processes, but partnered with different substrate recognition adaptors to impact distinct aspects of the DC life cycle. Genetic interactions were more prevalent within than between modules, and a deep learning model, comßVAE, predicts the outcome of new combinations by leveraging modularity. The E3 regulatory network was associated with heritable variation and aberrant gene expression in immune cells in human inflammatory diseases. Our study provides a general approach to dissect gene function.

IRF3 inhibits IFN-γ-mediated restriction of intracellular pathogens in macrophages independently of IFNAR.

Macrophages use an array of innate immune sensors to detect intracellular pathogens and to tailor effective antimicrobial responses. In addition, extrinsic activation with the cytokine IFN-γ is often required as well to tip the scales of the host-pathogen balance toward pathogen restriction. However, little is known about how host-pathogen sensing impacts the antimicrobial IFN-γ-activated state. It was observed that in the absence of IRF3, a key downstream component of pathogen sensing pathways, IFN-γ-primed macrophages more efficiently restricted the intracellular bacterium Legionella pneumophila and the intracellular protozoan parasite Trypanosoma cruzi. This effect did not require IFNAR, the receptor for Type I IFNs known to be induced by IRF3, nor the sensing adaptors MyD88/TRIF, MAVS, or STING. This effect also did not involve differential activation of STAT1, the major signaling protein downstream of both Type 1 and Type 2 IFN receptors. IRF3-deficient macrophages displayed a significantly altered IFN-γ-induced gene expression program, with up-regulation of microbial restriction factors such as Nos2. Finally, we found that IFN-γ-primed but not unprimed macrophages largely excluded the activated form of IRF3 from the nucleus following bacterial infection. These data are consistent with a relationship of mutual inhibition between IRF3 and IFN-γ-activated programs, possibly as a component of a partially reversible mechanism for modulating the activity of potent innate immune effectors (such as Nos2) in the context of intracellular infection.

Macrophages from Rosa26-Integrated Cas9-Expressing C57BL/6J Mice Have a Putative TRIF-Mediated Defect in the TLR-3/4 Signaling.

In this study, we report that the TLR4 ligand, LPS, and TLR3 ligand polyinosinic:polycytidylic acid failed to activate IRF3 or STAT1 in bone marrow-derived macrophages (BMMs) isolated from two independently generated lines of Rosa26-integrated Cas9-expressing C57BL/6J (B6) mice. RNA-sequencing analysis reveals that hundreds to thousands of genes including IFN-stimulated genes were differentially expressed in BMMs from these Cas9 strains compared with B6 upon LPS stimulation. Furthermore, the NF-κB signaling axis and TRIF-mediated necroptosis were also strongly reduced in response to LPS and polyinosinic:polycytidylic acid. In contrast, there were no defects in the responses of BMMs to ligands of the RIG-I, STING, TLR2, TLR9, and IFN receptors. Defects in TLR3 and TLR4 signaling were observed in mice with the B6 but not 129 background, and when Cas9 was integrated at the Rosa26 but not H11 locus. However, integration at the Rosa26 site, CAG promoter-driven Cas9 or eGFP were not individually sufficient to cause the defect. Taken together, the results of this study suggest a putative TRIF-mediated defect in TLR-3/4 signaling in BMMs from commercially available and widely used B6-Cas9-expressing mice.

Loss of the Nuclear Protein RTF2 Enhances Influenza Virus Replication.

While hundreds of genes are induced by type I interferons, their roles in restricting the influenza virus life cycle remain mostly unknown. Using a loss-of-function CRISPR screen in cells prestimulated with interferon beta (IFN-ß), we identified a small number of factors required for restricting influenza A virus replication. In addition to known components of the interferon signaling pathway, we found that replication termination factor 2 (RTF2) restricts influenza virus at the nuclear stage (and perhaps other stages) of the viral life cycle, based on several lines of evidence. First, a deficiency in RTF2 leads to higher levels of viral primary transcription, even in the presence of cycloheximide to block genome replication and secondary transcription. Second, cells that lack RTF2 have enhanced activity of a viral reporter that depends solely on four viral proteins that carry out replication and transcription in the nucleus. Third, when the RTF2 protein is mislocalized outside the nucleus, it is not able to restrict replication. Finally, the absence of RTF2 leads not only to enhanced viral transcription but also to reduced expression of antiviral factors in response to interferon. RTF2 thus inhibits primary influenza virus transcription, likely acts in the nucleus, and contributes to the upregulation of antiviral effectors in response to type I interferons.IMPORTANCE Viral infection triggers the secretion of type I interferons, which in turn induce the expression of hundreds of antiviral genes. However, the roles of these induced genes in controlling viral infections remain largely unknown, limiting our ability to develop host-based antiviral therapeutics against pathogenic viruses, such as influenza virus. Here, we performed a loss-of-function genetic CRISPR screen in cells prestimulated with type I interferon to identify antiviral genes that restrict influenza A virus replication. Besides finding key components of the interferon signaling pathway, we discovered a new restriction factor, RTF2, which acts in the nucleus, restricts influenza virus transcription, and contributes to the interferon-induced upregulation of known restriction factors. Our work contributes to the field of antiviral immunology by discovering and characterizing a novel restriction factor of influenza virus and may ultimately be useful for understanding how to control a virus that causes significant morbidity and mortality worldwide.

Extranuclear DNA accumulates in aged cells and contributes to senescence and inflammation.

Systemic inflammation is central to aging-related conditions. However, the intrinsic factors that induce inflammation are not well understood. We previously identified a cell-autonomous pathway through which damaged nuclear DNA is trafficked to the cytosol where it activates innate cytosolic DNA sensors that trigger inflammation. These results led us to hypothesize that DNA released after cumulative damage contributes to persistent inflammation in aging cells through a similar mechanism. Consistent with this notion, we found that older cells harbored higher levels of extranuclear DNA compared to younger cells. Extranuclear DNA was exported by a leptomycin B-sensitive process, degraded through the autophagosome-lysosomal pathway and triggered innate immune responses through the DNA-sensing cGAS-STING pathway. Patient cells from the aging diseases ataxia and progeria also displayed extranuclear DNA accumulation, increased pIRF3 and pTBK1, and STING-dependent p16 expression. Removing extranuclear DNA in old cells using DNASE2A reduced innate immune responses and senescence-associated (SA) ß-gal enzyme activity. Cells and tissues of Dnase2a-/- mice with defective DNA degradation exhibited slower growth, higher activity of ß-gal, or increased expression of HP-1ß and p16 proteins, while Dnase2a-/- ;Sting-/- cells and tissues were rescued from these phenotypes, supporting a role for extranuclear DNA in senescence. We hypothesize a direct role for excess DNA in aging-related inflammation and in replicative senescence, and propose DNA degradation as a therapeutic approach to remove intrinsic DNA and revert inflammation associated with aging.

Genetic analysis of isoform usage in the human anti-viral response reveals influenza-specific regulation of ERAP2 transcripts under balancing selection.

While genetic variants are known to be associated with overall gene abundance in stimulated immune cells, less is known about their effects on alternative isoform usage. By analyzing RNA-seq profiles of monocyte-derived dendritic cells from 243 individuals, we uncovered thousands of unannotated isoforms synthesized in response to influenza infection and type 1 interferon stimulation. We identified more than a thousand quantitative trait loci (QTLs) associated with alternate isoform usage (isoQTLs), many of which are independent of expression QTLs (eQTLs) for the same gene. Compared with eQTLs, isoQTLs are enriched for splice sites and untranslated regions, but depleted of sequences upstream of annotated transcription start sites. Both eQTLs and isoQTLs explain a significant proportion of the disease heritability attributed to common genetic variants. At the ERAP2 locus, we shed light on the function of the gene and how two frequent, highly differentiated haplotypes with intermediate frequencies could be maintained by balancing selection. At baseline and following type 1 interferon stimulation, the major haplotype is associated with low ERAP2 expression caused by nonsense-mediated decay, while the minor haplotype, known to increase Crohn's disease risk, is associated with high ERAP2 expression. In response to influenza infection, we found two uncharacterized isoforms expressed from the major haplotype, likely the result of multiple perfectly linked variants affecting the transcription and splicing at the locus. Thus, genetic variants at a single locus could modulate independent gene regulatory processes in innate immune responses and, in the case of ERAP2, may confer a historical fitness advantage in response to virus.

A single-cell survey of the small intestinal epithelium.

Intestinal epithelial cells absorb nutrients, respond to microbes, function as a barrier and help to coordinate immune responses. Here we report profiling of 53,193 individual epithelial cells from the small intestine and organoids of mice, which enabled the identification and characterization of previously unknown subtypes of intestinal epithelial cell and their gene signatures. We found unexpected diversity in hormone-secreting enteroendocrine cells and constructed the taxonomy of newly identified subtypes, and distinguished between two subtypes of tuft cell, one of which expresses the epithelial cytokine Tslp and the pan-immune marker CD45, which was not previously associated with non-haematopoietic cells. We also characterized the ways in which cell-intrinsic states and the proportions of different cell types respond to bacterial and helminth infections: Salmonella infection caused an increase in the abundance of Paneth cells and enterocytes, and broad activation of an antimicrobial program; Heligmosomoides polygyrus caused an increase in the abundance of goblet and tuft cells. Our survey highlights previously unidentified markers and programs, associates sensory molecules with cell types, and uncovers principles of gut homeostasis and response to pathogens.

An Integrative Framework Reveals Signaling-to-Transcription Events in Toll-like Receptor Signaling.

Building an integrated view of cellular responses to environmental cues remains a fundamental challenge due to the complexity of intracellular networks in mammalian cells. Here, we introduce an integrative biochemical and genetic framework to dissect signal transduction events using multiple data types and, in particular, to unify signaling and transcriptional networks. Using the Toll-like receptor (TLR) system as a model cellular response, we generate multifaceted datasets on physical, enzymatic, and functional interactions and integrate these data to reveal biochemical paths that connect TLR4 signaling to transcription. We define the roles of proximal TLR4 kinases, identify and functionally test two dozen candidate regulators, and demonstrate a role for Ap1ar (encoding the Gadkin protein) and its binding partner, Picalm, potentially linking vesicle transport with pro-inflammatory responses. Our study thus demonstrates how deciphering dynamic cellular responses by integrating datasets on various regulatory layers defines key components and higher-order logic underlying signaling-to-transcription pathways.

Perturb-Seq: Dissecting Molecular Circuits with Scalable Single-Cell RNA Profiling of Pooled Genetic Screens.

Genetic screens help infer gene function in mammalian cells, but it has remained difficult to assay complex phenotypes-such as transcriptional profiles-at scale. Here, we develop Perturb-seq, combining single-cell RNA sequencing (RNA-seq) and clustered regularly interspaced short palindromic repeats (CRISPR)-based perturbations to perform many such assays in a pool. We demonstrate Perturb-seq by analyzing 200,000 cells in immune cells and cell lines, focusing on transcription factors regulating the response of dendritic cells to lipopolysaccharide (LPS). Perturb-seq accurately identifies individual gene targets, gene signatures, and cell states affected by individual perturbations and their genetic interactions. We posit new functions for regulators of differentiation, the anti-viral response, and mitochondrial function during immune activation. By decomposing many high content measurements into the effects of perturbations, their interactions, and diverse cell metadata, Perturb-seq dramatically increases the scope of pooled genomic assays.

A Regression-Based Analysis of Ribosome-Profiling Data Reveals a Conserved Complexity to Mammalian Translation.

A fundamental goal of genomics is to identify the complete set of expressed proteins. Automated annotation strategies rely on assumptions about protein-coding sequences (CDSs), e.g., they are conserved, do not overlap, and exceed a minimum length. However, an increasing number of newly discovered proteins violate these rules. Here we present an experimental and analytical framework, based on ribosome profiling and linear regression, for systematic identification and quantification of translation. Application of this approach to lipopolysaccharide-stimulated mouse dendritic cells and HCMV-infected human fibroblasts identifies thousands of novel CDSs, including micropeptides and variants of known proteins, that bear the hallmarks of canonical translation and exhibit translation levels and dynamics comparable to that of annotated CDSs. Remarkably, many translation events are identified in both mouse and human cells even when the peptide sequence is not conserved. Our work thus reveals an unexpected complexity to mammalian translation suited to provide both conserved regulatory or protein-based functions.

A Genome-wide CRISPR Screen in Primary Immune Cells to Dissect Regulatory Networks.

Finding the components of cellular circuits and determining their functions systematically remains a major challenge in mammalian cells. Here, we introduced genome-wide pooled CRISPR-Cas9 libraries into dendritic cells (DCs) to identify genes that control the induction of tumor necrosis factor (Tnf) by bacterial lipopolysaccharide (LPS), a key process in the host response to pathogens, mediated by the Tlr4 pathway. We found many of the known regulators of Tlr4 signaling, as well as dozens of previously unknown candidates that we validated. By measuring protein markers and mRNA profiles in DCs that are deficient in known or candidate genes, we classified the genes into three functional modules with distinct effects on the canonical responses to LPS and highlighted functions for the PAF complex and oligosaccharyltransferase (OST) complex. Our findings uncover new facets of innate immune circuits in primary cells and provide a genetic approach for dissection of mammalian cell circuits.

Immunogenetics. Dynamic profiling of the protein life cycle in response to pathogens.

Protein expression is regulated by the production and degradation of messenger RNAs (mRNAs) and proteins, but their specific relationships remain unknown. We combine measurements of protein production and degradation and mRNA dynamics so as to build a quantitative genomic model of the differential regulation of gene expression in lipopolysaccharide-stimulated mouse dendritic cells. Changes in mRNA abundance play a dominant role in determining most dynamic fold changes in protein levels. Conversely, the preexisting proteome of proteins performing basic cellular functions is remodeled primarily through changes in protein production or degradation, accounting for more than half of the absolute change in protein molecules in the cell. Thus, the proteome is regulated by transcriptional induction for newly activated cellular functions and by protein life-cycle changes for remodeling of preexisting functions.

High-resolution sequencing and modeling identifies distinct dynamic RNA regulatory strategies.

Cells control dynamic transitions in transcript levels by regulating transcription, processing, and/or degradation through an integrated regulatory strategy. Here, we combine RNA metabolic labeling, rRNA-depleted RNA-seq, and DRiLL, a novel computational framework, to quantify the level; editing sites; and transcription, processing, and degradation rates of each transcript at a splice junction resolution during the LPS response of mouse dendritic cells. Four key regulatory strategies, dominated by RNA transcription changes, generate most temporal gene expression patterns. Noncanonical strategies that also employ dynamic posttranscriptional regulation control only a minority of genes, but provide unique signal processing features. We validate Tristetraprolin (TTP) as a major regulator of RNA degradation in one noncanonical strategy. Applying DRiLL to the regulation of noncoding RNAs and to zebrafish embryogenesis demonstrates its broad utility. Our study provides a new quantitative approach to discover transcriptional and posttranscriptional events that control dynamic changes in transcript levels using RNA sequencing data.

Single-cell RNA-seq reveals dynamic paracrine control of cellular variation.

High-throughput single-cell transcriptomics offers an unbiased approach for understanding the extent, basis and function of gene expression variation between seemingly identical cells. Here we sequence single-cell RNA-seq libraries prepared from over 1,700 primary mouse bone-marrow-derived dendritic cells spanning several experimental conditions. We find substantial variation between identically stimulated dendritic cells, in both the fraction of cells detectably expressing a given messenger RNA and the transcript's level within expressing cells. Distinct gene modules are characterized by different temporal heterogeneity profiles. In particular, a 'core' module of antiviral genes is expressed very early by a few 'precocious' cells in response to uniform stimulation with a pathogenic component, but is later activated in all cells. By stimulating cells individually in sealed microfluidic chambers, analysing dendritic cells from knockout mice, and modulating secretion and extracellular signalling, we show that this response is coordinated by interferon-mediated paracrine signalling from these precocious cells. Notably, preventing cell-to-cell communication also substantially reduces variability between cells in the expression of an early-induced 'peaked' inflammatory module, suggesting that paracrine signalling additionally represses part of the inflammatory program. Our study highlights the importance of cell-to-cell communication in controlling cellular heterogeneity and reveals general strategies that multicellular populations can use to establish complex dynamic responses.

CD209a expression on dendritic cells is critical for the development of pathogenic Th17 cell responses in murine schistosomiasis.

In murine schistosomiasis, immunopathology and cytokine production in response to parasite eggs are uneven and strain dependent. CBA/J (CBA) mice develop severe hepatic granulomatous inflammation associated with prominent Th17 cell responses driven by dendritic cell (DC)-derived IL-1ß and IL-23. Such Th17 cells fail to develop in low-pathology C57BL/6 (BL/6) mice, and the reasons for these strain-specific differences in APC reactivity to eggs remain unclear. We show by gene profiling that CBA DCs display an 18-fold higher expression of the C-type lectin receptor CD209a, a murine homolog of human DC-specific ICAM-3-grabbing nonintegrin, compared with BL/6 DCs. Higher CD209a expression was observed in CBA splenic and granuloma APC subpopulations, but only DCs induced Th17 cell differentiation in response to schistosome eggs. Gene silencing in CBA DCs and overexpression in BL/6 DCs demonstrated that CD209a is essential for egg-elicited IL-1ß and IL-23 production and subsequent Th17 cell development, which is associated with SRC, RAF-1, and ERK1/2 activation. These findings reveal a novel mechanism controlling the development of Th17 cell-mediated severe immunopathology in helminthic disease.

Semiconductor-based DNA sequencing of histone modification states.

The recent development of a semiconductor-based, non-optical DNA sequencing technology promises scalable, low-cost and rapid sequence data production. The technology has previously been applied mainly to genomic sequencing and targeted re-sequencing. Here we demonstrate the utility of Ion Torrent semiconductor-based sequencing for sensitive, efficient and rapid chromatin immunoprecipitation followed by sequencing (ChIP-seq) through the application of sample preparation methods that are optimized for ChIP-seq on the Ion Torrent platform. We leverage this method for epigenetic profiling of tumour tissues.

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 output, with important functional consequences. Existing studies of cellular heterogeneity, however, have typically measured only a few pre-selected RNAs or proteins simultaneously, because genomic profiling methods could not be applied to single cells until very recently. 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.

Deciphering molecular circuits from genetic variation underlying transcriptional responsiveness to stimuli.

Individual genetic variation affects gene responsiveness 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 quantitative trait loci or 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 responds as an activator of the antiviral response; using RNA interference, 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.

A high-throughput chromatin immunoprecipitation approach reveals principles of dynamic gene regulation in mammals.

Understanding the principles governing mammalian gene regulation has been hampered by the difficulty in measuring in vivo binding dynamics of large numbers of transcription factors (TF) to DNA. Here, we develop a high-throughput Chromatin ImmunoPrecipitation (HT-ChIP) method to systematically map protein-DNA interactions. HT-ChIP was applied to define the dynamics of DNA binding by 25 TFs and 4 chromatin marks at 4 time-points following pathogen stimulus of dendritic cells. Analyzing over 180,000 TF-DNA interactions we find that TFs vary substantially in their temporal binding landscapes. This data suggests a model for transcription regulation whereby TF networks are hierarchically organized into cell differentiation factors, factors that bind targets prior to stimulus to prime them for induction, and factors that regulate specific gene programs. Overlaying HT-ChIP data on gene-expression dynamics shows that many TF-DNA interactions are established prior to the stimuli, predominantly at immediate-early genes, and identified specific TF ensembles that coordinately regulate gene-induction.

Full-length transcriptome assembly from RNA-Seq data without a reference genome.

Massively parallel sequencing of cDNA has enabled deep and efficient probing of transcriptomes. Current approaches for transcript reconstruction from such data often rely on aligning reads to a reference genome, and are thus unsuitable for samples with a partial or missing reference genome. Here we present the Trinity method for de novo assembly of full-length transcripts and evaluate it on samples from fission yeast, mouse and whitefly, whose reference genome is not yet available. By efficiently constructing and analyzing sets of de Bruijn graphs, Trinity fully reconstructs a large fraction of transcripts, including alternatively spliced isoforms and transcripts from recently duplicated genes. Compared with other de novo transcriptome assemblers, Trinity recovers more full-length transcripts across a broad range of expression levels, with a sensitivity similar to methods that rely on genome alignments. Our approach provides a unified solution for transcriptome reconstruction in any sample, especially in the absence of a reference genome.