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.

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.

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.

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.

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.

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.

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.

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.

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.

Therapeutic Targeting of Transcription Factors to Control the Cytokine Release Syndrome in COVID-19.

Treatment of the cytokine release syndrome (CRS) has become an important part of rescuing hospitalized COVID-19 patients. Here, we systematically explored the transcriptional regulators of inflammatory cytokines involved in the COVID-19 CRS to identify candidate transcription factors (TFs) for therapeutic targeting using approved drugs. We integrated a resource of TF-cytokine gene interactions with single-cell RNA-seq expression data from bronchoalveolar lavage fluid cells of COVID-19 patients. We found 581 significantly correlated interactions, between 95 TFs and 16 cytokines upregulated in the COVID-19 patients, that may contribute to pathogenesis of the disease. Among these, we identified 19 TFs that are targets of FDA approved drugs. We investigated the potential therapeutic effect of 10 drugs and 25 drugs combinations on inflammatory cytokine production, which revealed two drugs that inhibited cytokine production and numerous combinations that show synergistic efficacy in downregulating cytokine production. Further studies of these candidate repurposable drugs could lead to a therapeutic regimen to treat the CRS in COVID-19 patients.

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.

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.

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.

Options and Considerations When Using a Yeast One-Hybrid System.

Comprehensive mapping of protein-DNA interactions is essential to uncover the mechanisms involved in gene regulation. However, the data generated has been sparse given the number of regulatory elements and transcription factors (TFs) encoded in the genomes of metazoan organisms. Yeast one-hybrid (Y1H) assays provide a powerful "DNA-centered" method, complementary to "TF-centered" methods such as chromatin immunoprecipitation, to identify the TFs that can bind a DNA sequence of interest. Here, we present different technical variations that should be considered when using a Y1H system, including the type of DNA sequence to test, source of TF clones, as well as types of vectors and screening format. Finally, we discuss limitations of the assay and future challenges.

Identification of Single Nucleotide Non-coding Driver Mutations in Cancer.

Recent whole-genome sequencing studies have identified millions of somatic variants present in tumor samples. Most of these variants reside in non-coding regions of the genome potentially affecting transcriptional and post-transcriptional gene regulation. Although a few hallmark examples of driver mutations in non-coding regions have been reported, the functional role of the vast majority of somatic non-coding variants remains to be determined. This is because the few driver variants in each sample must be distinguished from the thousands of passenger variants and because the logic of regulatory element function has not yet been fully elucidated. Thus, variants prioritized based on mutational burden and location within regulatory elements need to be validated experimentally. This is generally achieved by combining assays that measure physical binding, such as chromatin immunoprecipitation, with those that determine regulatory activity, such as luciferase reporter assays. Here, we present an overview of in silico approaches used to prioritize somatic non-coding variants and the experimental methods used for functional validation and characterization.

Cellular network perturbations by disease-associated variants.

Genetic and genome-wide association studies (GWAS) have identified a myriad of human disease-associated genomic variants. However, these studies do not reveal the mechanisms by which these variants perturb cellular networks, a necessary step to intervene and improve disease outcomes. This has been challenging because multiple variants are present in haplotype blocks, thereby confounding the identification of causal variants, and because most reside in noncoding regions. Here, we review recent advances in the identification of functional variants and gene-variant associations. In addition, we examine approaches used to study perturbations in protein-protein and protein-DNA interactions associated with disease, and discuss how these perturbations affect cellular networks.

Generating Bait Strains for Yeast One-Hybrid Assays.

Yeast one-hybrid (Y1H) assays are used to identify which transcription factor (TF) "preys" can bind a DNA fragment of interest that is used as the "bait." Undertaking Y1H assays requires the generation of a yeast "bait strain" for each DNA fragment of interest that features the DNA bait coupled to a reporter(s). Plasmids encoding TFs fused to the Gal4 activation domain (AD) are then introduced into the bait strain, and activation of the reporter(s) indicates that a TF-DNA interaction has occurred. Here, we present a protocol for the first part of the strategy-the generation of a bait strain for Y1H assays. We assume that the DNA bait has already been cloned into two different reporter constructs: One places the fragment of interest upstream of HIS3, an auxotrophic growth marker, whereas the other places the DNA bait upstream of LacZ, a colorimetric marker that changes colorless X-gal into a blue compound. Briefly, generation of the bait strain involves using homologous recombination to integrate the two reporters into the genome of the yeast strain, screening individual integrants for background reporter expression (i.e., expression in the absence of a TF), and using polymerase chain reaction (PCR) and sequencing to confirm the DNA bait identity from both integrated reporter cassettes.

Performing Yeast One-Hybrid Library Screens.

Yeast one-hybrid (Y1H) assays are used to identify which transcription factor (TF) "prey" molecules can bind a DNA fragment of interest that is used as "bait". Y1H assays involve introducing plasmids that encode TFs into a yeast "bait strain" in which the DNA fragment of interest is integrated upstream of one or more reporters, and activation of these reporters indicates that a TF-DNA interaction has occurred. These plasmids express each TF as a hybrid protein (hence the "one-hybrid" name) fused to the activation domain (AD) of the yeast TF Gal4. The AD moiety activates reporter expression even if the TF to which it is fused typically functions as a repressor. Here, we describe how to perform a Y1H screen of a library of cDNA fragments cloned into a pPC86 plasmid expressing the protein encoded by the cDNA as an AD fusion. The method assumes availability of either commercially available libraries or libraries generated in house using mRNA extracted from a tissue of interest. We also assume that users have access to a yeast bait strain that possesses the DNA fragment of interest integrated upstream of two different reporters-HIS3, an auxotrophic marker, and LacZ, a colorimetric marker that changes colorless X-gal into a blue compound. Briefly, the screen involves transforming the AD-cDNA library into the yeast bait strain, identifying colonies that show activation of both reporters, retesting the interaction in a freshly grown bait strain, and sequencing the cDNA insert to identify the interacting TF.