Human Virus Transcriptional Regulators.

Viral genomes encode transcriptional regulators that alter the expression of viral and host genes. Despite an emerging role in human diseases, a thorough annotation of human viral transcriptional regulators (vTRs) is currently lacking, limiting our understanding of their molecular features and functions. Here, we provide a comprehensive catalog of 419 vTRs belonging to 20 different virus families. Using this catalog, we characterize shared and unique cellular genes, proteins, and pathways targeted by particular vTRs and discuss the role of vTRs in human disease pathogenesis. Our study provides a unique and valuable resource for the fields of virology, genomics, and human disease genetics.

Essential role of a ThPOK autoregulatory loop in the maintenance of mature CD4+ T cell identity and function.

The transcription factor ThPOK (encoded by the Zbtb7b gene) controls homeostasis and differentiation of mature helper T cells, while opposing their differentiation to CD4+ intraepithelial lymphocytes (IELs) in the intestinal mucosa. Thus CD4 IEL differentiation requires ThPOK transcriptional repression via reactivation of the ThPOK transcriptional silencer element (SilThPOK). In the present study, we describe a new autoregulatory loop whereby ThPOK binds to the SilThPOK to maintain its own long-term expression in CD4 T cells. Disruption of this loop in vivo prevents persistent ThPOK expression, leads to genome-wide changes in chromatin accessibility and derepresses the colonic regulatory T (Treg) cell gene expression signature. This promotes selective differentiation of naive CD4 T cells into GITRloPD-1loCD25lo (Triplelo) Treg cells and conversion to CD4+ IELs in the gut, thereby providing dominant protection from colitis. Hence, the ThPOK autoregulatory loop represents a key mechanism to physiologically control ThPOK expression and T cell differentiation in the gut, with potential therapeutic relevance.

Human gene-centered transcription factor networks for enhancers and disease variants.

Gene regulatory networks (GRNs) comprising interactions between transcription factors (TFs) and regulatory loci control development and physiology. Numerous disease-associated mutations have been identified, the vast majority residing in non-coding regions of the genome. As current GRN mapping methods test one TF at a time and require the use of cells harboring the mutation(s) of interest, they are not suitable to identify TFs that bind to wild-type and mutant loci. Here, we use gene-centered yeast one-hybrid (eY1H) assays to interrogate binding of 1,086 human TFs to 246 enhancers, as well as to 109 non-coding disease mutations. We detect both loss and gain of TF interactions with mutant loci that are concordant with target gene expression changes. This work establishes eY1H assays as a powerful addition to the toolkit of mapping human GRNs and for the high-throughput characterization of genomic variants that are rapidly being identified by genome-wide association studies.

Widespread macromolecular interaction perturbations in human genetic disorders.

How disease-associated mutations impair protein activities in the context of biological networks remains mostly undetermined. Although a few renowned alleles are well characterized, functional information is missing for over 100,000 disease-associated variants. Here we functionally profile several thousand missense mutations across a spectrum of Mendelian disorders using various interaction assays. The majority of disease-associated alleles exhibit wild-type chaperone binding profiles, suggesting they preserve protein folding or stability. While common variants from healthy individuals rarely affect interactions, two-thirds of disease-associated alleles perturb protein-protein interactions, with half corresponding to "edgetic" alleles affecting only a subset of interactions while leaving most other interactions unperturbed. With transcription factors, many alleles that leave protein-protein interactions intact affect DNA binding. Different mutations in the same gene leading to different interaction profiles often result in distinct disease phenotypes. Thus disease-associated alleles that perturb distinct protein activities rather than grossly affecting folding and stability are relatively widespread.

Compendium of human transcription factor effector domains.

Transcription factors (TFs) regulate gene expression by binding to DNA sequences and modulating transcriptional activity through their effector domains. Despite the central role of effector domains in TF function, there is a current lack of a comprehensive resource and characterization of effector domains. Here, we provide a catalog of 924 effector domains across 594 human TFs. Using this catalog, we characterized the amino acid composition of effector domains, their conservation across species and across the human population, and their roles in human diseases. Furthermore, we provide a classification system for effector domains that constitutes a valuable resource and a blueprint for future experimental studies of TF effector domain function.

Viral cis-regulatory elements as sensors of cellular states and environmental cues.

To withstand a hostile cellular environment and replicate, viruses must sense, interpret, and respond to many internal and external cues. Retroviruses and DNA viruses can intercept these cues impinging on host transcription factors via cis-regulatory elements (CREs) in viral genomes, allowing them to sense and coordinate context-specific responses to varied signals. Here, we explore the characteristics of viral CREs, the classes of signals and host transcription factors that regulate them, and how this informs outcomes of viral replication, immune evasion, and latency. We propose that viral CREs constitute central hubs for signal integration from multiple pathways and that sequence variation between viral isolates can rapidly rewire sensing mechanisms, contributing to the variability observed in patient outcomes.

Identification of conserved skeletal enhancers associated with craniosynostosis risk genes.

Craniosynostosis, defined by premature fusion of one or multiple cranial sutures, is a common congenital defect affecting more than 1/2000 infants and results in restricted brain expansion. Single gene mutations account for 15-20% of cases, largely as part of a syndrome, but the majority are nonsyndromic with complex underlying genetics. We hypothesized that the two noncoding genomic regions identified by a GWAS for craniosynostosis contain distal regulatory elements for the risk genes BMPER and BMP2. To identify such regulatory elements, we surveyed conserved noncoding sequences from both risk loci for enhancer activity in transgenic Danio rerio. We identified enhancers from both regions that direct expression to skeletal tissues, consistent with the endogenous expression of bmper and bmp2. For each locus, we also found a skeletal enhancer that also contains a sequence variant associated with craniosynostosis risk. We examined the activity of each enhancer during craniofacial development and found that the BMPER-associated enhancer is active in the restricted region of cartilage closely associated with frontal bone initiation. The same enhancer is active in mouse skeletal tissues, demonstrating evolutionarily conserved activity. Using enhanced yeast one-hybrid assays, we identified transcription factors that bind each enhancer and observed differential binding between alleles, implicating multiple signaling pathways. Our findings help unveil the genetic mechanism of the two craniosynostosis risk loci. More broadly, our combined in vivo approach is applicable to many complex genetic diseases to build a link between association studies and specific genetic mechanisms.

A functional screen identifies transcriptional networks that regulate HIV-1 and HIV-2.

The molecular networks involved in the regulation of HIV replication, transcription, and latency remain incompletely defined. To expand our understanding of these networks, we performed an unbiased high-throughput yeast one-hybrid screen, which identified 42 human transcription factors and 85 total protein-DNA interactions with HIV-1 and HIV-2 long terminal repeats. We investigated a subset of these transcription factors for transcriptional activity in cell-based models of infection. KLF2 and KLF3 repressed HIV-1 and HIV-2 transcription in CD4+ T cells, whereas PLAGL1 activated transcription of HIV-2 through direct protein-DNA interactions. Using computational modeling with interacting proteins, we leveraged the results from our screen to identify putative pathways that define intrinsic transcriptional networks. Overall, we used a high-throughput functional screen, computational modeling, and biochemical assays to identify and confirm several candidate transcription factors and biochemical processes that influence HIV-1 and HIV-2 transcription and latency.

Intragenic proviral elements support transcription of defective HIV-1 proviruses.

HIV-1 establishes a persistent proviral reservoir by integrating into the genome of infected host cells. Current antiretroviral treatments do not target this persistent population of proviruses which include latently infected cells that upon treatment interruption can be reactivated to contribute to HIV-1 rebound. Deep sequencing of persistent HIV proviruses has revealed that greater than 90% of integrated HIV genomes are defective and unable to produce infectious virions. We hypothesized that intragenic elements in the HIV genome support transcription of aberrant HIV-1 RNAs from defective proviruses that lack long terminal repeats (LTRs). Using an intact provirus detection assay, we observed that resting CD4+ T cells and monocyte-derived macrophages (MDMs) are biased towards generating defective HIV-1 proviruses. Multiplex reverse transcription droplet digital PCR identified env and nef transcripts which lacked 5' untranslated regions (UTR) in acutely infected CD4+ T cells and MDMs indicating transcripts are generated that do not utilize the promoter within the LTR. 5'UTR-deficient env transcripts were also identified in a cohort of people living with HIV (PLWH) on ART, suggesting that these aberrant RNAs are produced in vivo. Using 5' rapid amplification of cDNA ends (RACE), we mapped the start site of these transcripts within the Env gene. This region bound several cellular transcription factors and functioned as a transcriptional regulatory element that could support transcription and translation of downstream HIV-1 RNAs. These studies provide mechanistic insights into how defective HIV-1 proviruses are persistently expressed to potentially drive inflammation in PLWH.

Genome-wide characterization of human minisatellite VNTRs: population-specific alleles and gene expression differences.

Variable Number Tandem Repeats (VNTRs) are tandem repeat (TR) loci that vary in copy number across a population. Using our program, VNTRseek, we analyzed human whole genome sequencing datasets from 2770 individuals in order to detect minisatellite VNTRs, i.e., those with pattern sizes ≥7 bp. We detected 35 638 VNTR loci and classified 5676 as commonly polymorphic (i.e. with non-reference alleles occurring in >5% of the population). Commonly polymorphic VNTR loci were found to be enriched in genomic regions with regulatory function, i.e. transcription start sites and enhancers. Investigation of the commonly polymorphic VNTRs in the context of population ancestry revealed that 1096 loci contained population-specific alleles and that those could be used to classify individuals into super-populations with near-perfect accuracy. Search for quantitative trait loci (eQTLs), among the VNTRs proximal to genes, indicated that in 187 genes expression differences correlated with VNTR genotype. We validated our predictions in several ways, including experimentally, through the identification of predicted alleles in long reads, and by comparisons showing consistency between sequencing platforms. This study is the most comprehensive analysis of minisatellite VNTRs in the human population to date.

Comprehensive mapping of the human cytokine gene regulatory network.

Proper cytokine gene expression is essential in development, homeostasis and immune responses. Studies on the transcriptional control of cytokine genes have mostly focused on highly researched transcription factors (TFs) and cytokines, resulting in an incomplete portrait of cytokine gene regulation. Here, we used enhanced yeast one-hybrid (eY1H) assays to derive a comprehensive network comprising 1380 interactions between 265 TFs and 108 cytokine gene promoters. Our eY1H-derived network greatly expands the known repertoire of TF-cytokine gene interactions and the set of TFs known to regulate cytokine genes. We found an enrichment of nuclear receptors and confirmed their role in cytokine regulation in primary macrophages. Additionally, we used the eY1H-derived network as a framework to identify pairs of TFs that can be targeted with commercially-available drugs to synergistically modulate cytokine production. Finally, we integrated the eY1H data with single cell RNA-seq and phenotypic datasets to identify novel TF-cytokine regulatory axes in immune diseases and immune cell lineage development. Overall, the eY1H data provides a rich resource to study cytokine regulation in a variety of physiological and disease contexts.

A gene-centered C. elegans protein-DNA interaction network provides a framework for functional predictions.

Transcription factors (TFs) play a central role in controlling spatiotemporal gene expression and the response to environmental cues. A comprehensive understanding of gene regulation requires integrating physical protein-DNA interactions (PDIs) with TF regulatory activity, expression patterns, and phenotypic data. Although great progress has been made in mapping PDIs using chromatin immunoprecipitation, these studies have only characterized ~10% of TFs in any metazoan species. The nematode C. elegans has been widely used to study gene regulation due to its compact genome with short regulatory sequences. Here, we delineated the largest gene-centered metazoan PDI network to date by examining interactions between 90% of C. elegans TFs and 15% of gene promoters. We used this network as a backbone to predict TF binding sites for 77 TFs, two-thirds of which are novel, as well as integrate gene expression, protein-protein interaction, and phenotypic data to predict regulatory and biological functions for multiple genes and TFs.

Using networks to measure similarity between genes: association index selection.

Biological networks can be used to functionally annotate genes on the basis of interaction-profile similarities. Metrics known as association indices can be used to quantify interaction-profile similarity. We provide an overview of commonly used association indices, including the Jaccard index and the Pearson correlation coefficient, and compare their performance in different types of analyses of biological networks. We introduce the Guide for Association Index for Networks (GAIN), a web tool for calculating and comparing interaction-profile similarities and defining modules of genes with similar profiles.

Transcription factor binding to Caenorhabditis elegans first introns reveals lack of redundancy with gene promoters.

Gene expression is controlled through the binding of transcription factors (TFs) to regulatory genomic regions. First introns are longer than other introns in multiple eukaryotic species and are under selective constraint. Here we explore the importance of first introns in TF binding in the nematode Caenorhabditis elegans by combining computational predictions and experimentally derived TF-DNA interaction data. We found that first introns of C. elegans genes, particularly those for families enriched in long first introns, are more conserved in length, have more conserved predicted TF interactions and are bound by more TFs than other introns. We detected a significant positive correlation between first intron size and the number of TF interactions obtained from chromatin immunoprecipitation assays or determined by yeast one-hybrid assays. TFs that bind first introns are largely different from those binding promoters, suggesting that the different interactions are complementary rather than redundant. By combining first intron and promoter interactions, we found that genes that share a large fraction of TF interactions are more likely to be co-expressed than when only TF interactions with promoters are considered. Altogether, our data suggest that C. elegans gene regulation may be additive through the combined effects of multiple regulatory regions.

Semi-Automatic Detection of Errors in Genome-Scale Metabolic Models.

Background: Genome-Scale Metabolic Models (GSMMs) are used for numerous tasks requiring computational estimates of metabolic fluxes, from predicting novel drug targets to engineering microbes to produce valuable compounds. A key limiting step in most applications of GSMMs is ensuring their representation of the target organism's metabolism is complete and accurate. Identifying and visualizing errors in GSMMs is complicated by the fact that they contain thousands of densely interconnected reactions. Furthermore, many errors in GSMMs only become apparent when considering pathways of connected reactions collectively, as opposed to examining reactions individually. Results: We present Metabolic Accuracy Check and Analysis Workflow (MACAW), a collection of algorithms for detecting errors in GSMMs. The relative frequencies of errors we detect in manually curated GSMMs appear to reflect the different approaches used to curate them. Changing the method used to automatically create a GSMM from a particular organism's genome can have a larger impact on the kinds of errors in the resulting GSMM than using the same method with a different organism's genome. Our algorithms are particularly capable of identifying errors that are only apparent at the pathway level, including loops, and nontrivial cases of dead ends. Conclusions: MACAW is capable of identifying inaccuracies of varying severity in a wide range of GSMMs. Correcting these errors can measurably improve the predictive capacity of a GSMM. The relative prevalence of each type of error we identify in a large collection of GSMMs could help shape future efforts for further automation of error correction and GSMM creation.

Widespread variation in molecular interactions and regulatory properties among transcription factor isoforms.

Most human Transcription factors (TFs) genes encode multiple protein isoforms differing in DNA binding domains, effector domains, or other protein regions. The global extent to which this results in functional differences between isoforms remains unknown. Here, we systematically compared 693 isoforms of 246 TF genes, assessing DNA binding, protein binding, transcriptional activation, subcellular localization, and condensate formation. Relative to reference isoforms, two-thirds of alternative TF isoforms exhibit differences in one or more molecular activities, which often could not be predicted from sequence. We observed two primary categories of alternative TF isoforms: "rewirers" and "negative regulators", both of which were associated with differentiation and cancer. Our results support a model wherein the relative expression levels of, and interactions involving, TF isoforms add an understudied layer of complexity to gene regulatory networks, demonstrating the importance of isoform-aware characterization of TF functions and providing a rich resource for further studies.

AT1 receptor blockade delays postlactational mammary gland involution: a novel role for the renin angiotensin system.

Angiotensin II (AngII), the main effector peptide of the renin-angiotensin system (RAS), participates in multiple biological processes, including cell growth, apoptosis, and tissue remodeling. Since AngII activates, in different cell types, signal transducing pathways that are critical for mammary gland postlactational regression, we investigated the role of the RAS during this process. We found that exogenous administration of AngII in mammary glands of lactating Balb/c mice induced epithelium apoptosis [2.9±0.5% (control) vs. 9.6±1.1% (AngII); P < 0.001] and activation of the proapoptotic factor STAT3, an effect inhibited by irbesartan, an AT(1) receptor blocker. Subsequently, we studied the expression kinetics of RAS components during involution. We found that angiotensin-converting enzyme (ACE) mRNA expression peaked 6 h after weaning (5.7-fold; P<0.01), while induction of angiotensinogen and AT(1) and AT(2) receptors expression was detected 96 h after weaning (6.2-, 10-, and 6.2-fold increase, respectively; P<0.01). To assess the role of endogenously generated AngII, mice were treated with losartan, an AT(1) receptor blocker, during mammary involution. Mammary glands from losartan-treated mice showed activation of the survival factors AKT and BCL-(XL), significantly lower LIF and TNF-α mRNA expression (P<0.05), reduced apoptosis [12.1±2.1% (control) vs. 4.8±0.7% (losartan); P<0.001] and shedding of epithelial cells, inhibition of MMP-9 activity in a dose-dependent manner (80%; P<0.05; with losartan IC(50) value of 6.9 mg/kg/d] and lower collagen deposition and adipocyte invasion causing a delayed involution compared to vehicle-treated mice. Furthermore, mammary glands of forced weaned AT(1A)- and/or AT(1B)-deficient mice exhibited retarded apoptosis of epithelial cells [6.3±0.95% (WT) vs. 3.3±0.56% (AT(1A)/AT(1B) DKO); P<0.05] with remarkable delayed postlactational regression compared to wild-type animals. Taken together, these results strongly suggest that AngII, via the AT(1) receptor, plays a major role in mouse mammary gland involution identifying a novel role for the RAS. angiotensin system.

Transcription factors in the development and treatment of immune disorders.

Immune function is highly controlled at the transcriptional level by the binding of transcription factors (TFs) to promoter and enhancer elements. Several TF families play major roles in immune gene expression, including NF-κB, STAT, IRF, AP-1, NRs, and NFAT, which trigger anti-pathogen responses, promote cell differentiation, and maintain immune system homeostasis. Aberrant expression, activation, or sequence of isoforms and variants of these TFs can result in autoimmune and inflammatory diseases as well as hematological and solid tumor cancers. For this reason, TFs have become attractive drug targets, even though most were previously deemed "undruggable" due to their lack of small molecule binding pockets and the presence of intrinsically disordered regions. However, several aspects of TF structure and function can be targeted for therapeutic intervention, such as ligand-binding domains, protein-protein interactions between TFs and with cofactors, TF-DNA binding, TF stability, upstream signaling pathways, and TF expression. In this review, we provide an overview of each of the important TF families, how they function in immunity, and some related diseases they are involved in. Additionally, we discuss the ways of targeting TFs with drugs along with recent research developments in these areas and their clinical applications, followed by the advantages and disadvantages of targeting TFs for the treatment of immune disorders.

Paired yeast one-hybrid assays to detect DNA-binding cooperativity and antagonism across transcription factors.

Cooperativity and antagonism between transcription factors (TFs) can drastically modify their binding to regulatory DNA elements. While mapping these relationships between TFs is important for understanding their context-specific functions, existing approaches either rely on DNA binding motif predictions, interrogate one TF at a time, or study individual TFs in parallel. Here, we introduce paired yeast one-hybrid (pY1H) assays to detect cooperativity and antagonism across hundreds of TF-pairs at DNA regions of interest. We provide evidence that a wide variety of TFs are subject to modulation by other TFs in a DNA region-specific manner. We also demonstrate that TF-TF relationships are often affected by alternative isoform usage and identify cooperativity and antagonism between human TFs and viral proteins from human papillomaviruses, Epstein-Barr virus, and other viruses. Altogether, pY1H assays provide a broadly applicable framework to study how different functional relationships affect protein occupancy at regulatory DNA regions.

Extracellular DNA: a major proinflammatory component of Pseudomonas aeruginosa biofilms.

We previously demonstrated that extracellular bacterial DNA activates neutrophils through a CpG- and TLR9-independent mechanism. Biofilms are microbial communities enclosed in a polymeric matrix that play a critical role in the pathogenesis of many infectious diseases. Because extracellular DNA is a key component of biofilms of different bacterial species, the aim of this study was to determine whether it plays a role in the ability of biofilms to induce human neutrophil activation. We found that degradation of matrix extracellular DNA with DNase I markedly reduced the capacity of Pseudomonas aeruginosa biofilms to induce the release of the neutrophil proinflammatory cytokines IL-8 and IL-1beta (>75%); reduced the upregulation of neutrophil activation markers CD18, CD11b, and CD66b (p < 0.001); reduced the number of bacteria phagocytosed per neutrophil contacting the biofilm; and reduced the production of neutrophil extracellular traps. Consistent with these findings, we found that biofilms formed by the lasI rhlI P. aeruginosa mutant strain, exhibiting a very low content of matrix extracellular DNA, displayed a lower capacity to stimulate the release of proinflammatory cytokines by neutrophils, which was not decreased further by DNase I treatment. Together, our findings support that matrix extracellular DNA is a major proinflammatory component of P. aeruginosa biofilms.