A high-throughput method to identify trans-activation domains within transcription factor sequences

CRISPR technologies for genome, epigenome and transcriptome editing

Our ability to edit genomes lags behind our capacity to sequence them, but the growing understanding of CRISPR biology and its application to genome, epigenome and transcriptome engineering is narrowing this gap. In this Review, we discuss recent developments of various CRISPR-based systems that can transiently or permanently modify the genome and the transcriptome. The discovery of further CRISPR enzymes and systems through functional metagenomics has meaningfully broadened the applicability of CRISPR-based editing. Engineered Cas variants offer diverse capabilities such as base editing, prime editing, gene insertion and gene regulation, thereby providing a panoply of tools for the scientific community. We highlight the strengths and weaknesses of current CRISPR tools, considering their efficiency, precision, specificity, reliance on cellular DNA repair mechanisms and their applications in both fundamental biology and therapeutics. Finally, we discuss ongoing clinical trials that illustrate the potential impact of CRISPR systems on human health.

Commonly asked questions about transcriptional activation domains

Eukaryotic transcription factors activate gene expression with their DNA-binding domains and activation domains. DNA-binding domains bind the genome by recognizing structurally related DNA sequences; they are structured, conserved, and predictable from protein sequences. Activation domains recruit chromatin modifiers, coactivator complexes, or basal transcriptional machinery via structurally diverse protein-protein interactions. Activation domains and DNA-binding domains have been called independent, modular units, but there are many departures from modularity, including interactions between these regions and overlap in function. Compared to DNA-binding domains, activation domains are poorly understood because they are poorly conserved, intrinsically disordered, and difficult to predict from protein sequences. This review, organized around commonly asked questions, describes recent progress that the field has made in understanding the sequence features that control activation domains and predicting them from sequence.

A modular dCas9-based recruitment platform for combinatorial epigenome editing

Targeted epigenome editing tools allow precise manipulation and investigation of genome modifications, however they often display high context dependency and variable efficacy between target genes and cell types. While systems that simultaneously recruit multiple distinct 'effector' chromatin regulators can improve efficacy, they generally lack control over effector composition and spatial organisation. To overcome this we have created a modular combinatorial epigenome editing platform, called SSSavi. This system is an interchangeable and reconfigurable docking platform fused to dCas9 that enables simultaneous recruitment of up to four different effectors, allowing precise control of effector composition and spatial ordering. We demonstrate the activity and specificity of the SSSavi system and, by testing it against existing multi-effector targeting systems, demonstrate its comparable efficacy. Furthermore, we demonstrate the importance of the spatial ordering of the recruited effectors for effective transcriptional regulation. Together, the SSSavi system enables exploration of combinatorial effector co-recruitment to enhance manipulation of chromatin contexts previously resistant to targeted editing.

Clusters of acidic and hydrophobic residues can predict acidic transcriptional activation domains from protein sequence

Transcription factors activate gene expression in development, homeostasis, and stress with DNA binding domains and activation domains. Although there exist excellent computational models for predicting DNA binding domains from protein sequence, models for predicting activation domains from protein sequence have lagged, particularly in metazoans. We recently developed a simple and accurate predictor of acidic activation domains on human transcription factors. Here, we show how the accuracy of this human predictor arises from the clustering of aromatic, leucine, and acidic residues, which together are necessary for acidic activation domain function. When we combine our predictor with the predictions of convolutional neural network (CNN) models trained in yeast, the intersection is more accurate than individual models, emphasizing that each approach carries orthogonal information. We synthesize these findings into a new set of activation domain predictions on human transcription factors.

Frontiers and techniques in plant gene regulation

Understanding plant gene regulation has been a priority for generations of plant scientists. However, due to its complex nature, the regulatory code governing plant gene expression has yet to be deciphered comprehensively. Recently developed methods-often relying on next-generation sequencing technology and state-of-the-art computational approaches-have started to further our understanding of the gene regulatory logic used by plants. In this review, we discuss these methods and the insights into the regulatory code of plants that they can yield.

High-throughput functional characterization of combinations of transcriptional activators and repressors

Despite growing knowledge of the functions of individual human transcriptional effector domains, much less is understood about how multiple effector domains within the same protein combine to regulate gene expression. Here, we measure transcriptional activity for 8,400 effector domain combinations by recruiting them to reporter genes in human cells. In our assay, weak and moderate activation domains synergize to drive strong gene expression, whereas combining strong activators often results in weaker activation. In contrast, repressors combine linearly and produce full gene silencing, and repressor domains often overpower activation domains. We use this information to build a synthetic transcription factor whose function can be tuned between repression and activation independent of recruitment to target genes by using a small-molecule drug. Altogether, we outline the basic principles of how effector domains combine to regulate gene expression and demonstrate their value in building precise and flexible synthetic biology tools. A record of this paper's transparent peer review process is included in the supplemental information.

Systematic identification of transcriptional activator domains from non-transcription factor proteins in plants and yeast

Transcription factors promote gene expression via trans-regulatory activation domains. Although whole genome scale screens in model organisms (e.g. human, yeast, fly) have helped identify activation domains from transcription factors, such screens have been less extensively used to explore the occurrence of activation domains in non-transcription factor proteins, such as transcriptional coactivators, chromatin regulators and some cytosolic proteins, leaving a blind spot on what role activation domains in these proteins could play in regulating transcription. We utilized the activation domain predictor PADDLE to mine the entire proteomes of two model eukaryotes, Arabidopsis thaliana and Saccharomyces cerevisiae ( 1 ). We characterized 18,000 fragments covering predicted activation domains from >800 non-transcription factor genes in both species, and experimentally validated that 89% of proteins contained fragments capable of activating transcription in yeast. Peptides with similar sequence composition show a broad range of activities, which is explained by the arrangement of key amino acids. We also annotated hundreds of nuclear proteins with activation domains as putative coactivators; many of which have never been ascribed any function in plants. Furthermore, our library contains >250 non-nuclear proteins containing peptides with activation domain function across both eukaryotic lineages, suggesting that there are unknown biological roles of these peptides beyond transcription. Finally, we identify and validate short, 'universal' eukaryotic activation domains that activate transcription in both yeast and plants with comparable or stronger performance to state-of-the-art activation domains. Overall, our dual host screen provides a blueprint on how to systematically discover novel genetic parts for synthetic biology that function across a wide diversity of eukaryotes.

Significance Statement

Activation domains promote transcription and play a critical role in regulating gene expression. Although the mapping of activation domains from transcription factors has been carried out in previous genome-wide screens, their occurrence in non-transcription factors has been less explored. We utilize an activation domain predictor to mine the entire proteomes of Arabidopsis thaliana and Saccharomyces cerevisiae for new activation domains on non-transcription factor proteins. We validate peptides derived from >750 non-transcription factor proteins capable of activating transcription, discovering many potentially new coactivators in plants. Importantly, we identify novel genetic parts that can function across both species, representing unique synthetic biology tools.

Transcription factors interact with RNA to regulate genes

Transcription factors (TFs) orchestrate the gene expression programs that define each cell's identity. The canonical TF accomplishes this with two domains, one that binds specific DNA sequences and the other that binds protein coactivators or corepressors. We find that at least half of TFs also bind RNA, doing so through a previously unrecognized domain with sequence and functional features analogous to the arginine-rich motif of the HIV transcriptional activator Tat. RNA binding contributes to TF function by promoting the dynamic association between DNA, RNA, and TF on chromatin. TF-RNA interactions are a conserved feature important for vertebrate development and disrupted in disease. We propose that the ability to bind DNA, RNA, and protein is a general property of many TFs and is fundamental to their gene regulatory function.

High-throughput discovery and characterization of viral transcriptional effectors in human cells

Viruses encode transcriptional regulatory proteins critical for controlling viral and host gene expression. Given their multifunctional nature and high sequence divergence, it is unclear which viral proteins can affect transcription and which specific sequences contribute to this function. Using a high-throughput assay, we measured the transcriptional regulatory potential of over 60,000 protein tiles across ∼1,500 proteins from 11 coronaviruses and all nine human herpesviruses. We discovered hundreds of transcriptional effector domains, including a conserved repression domain in all coronavirus Spike homologs, dual activation-repression domains in viral interferon regulatory factors (VIRFs), and an activation domain in six herpesvirus homologs of the single-stranded DNA-binding protein that we show is important for viral replication and late gene expression in Kaposi's sarcoma-associated herpesvirus (KSHV). For the effector domains we identified, we investigated their mechanisms via high-throughput sequence and chemical perturbations, pinpointing sequence motifs essential for function. This work massively expands viral protein annotations, serving as a springboard for studying their biological and health implications and providing new candidates for compact gene regulation tools.

The trans-regulatory landscape of gene networks in plants

The transcriptional effector domains of transcription factors play a key role in controlling gene expression; however, their functional nature is poorly understood, hampering our ability to explore this fundamental dimension of gene regulatory networks. To map the trans-regulatory landscape in a complex eukaryote, we systematically characterized the putative transcriptional effector domains of over 400 Arabidopsis thaliana transcription factors for their capacity to modulate transcription. We demonstrate that transcriptional effector activity can be integrated into gene regulatory networks capable of elucidating the functional dynamics underlying gene expression patterns. We further show how our characterized domains can enhance genome engineering efforts and reveal how plant transcriptional activators share regulatory features conserved across distantly related eukaryotes. Our results provide a framework to systematically characterize the regulatory role of transcription factors at a genome-scale in order to understand the transcriptional wiring of biological systems.

Large-scale mapping and mutagenesis of human transcriptional effector domains

Human gene expression is regulated by more than 2,000 transcription factors and chromatin regulators1,2. Effector domains within these proteins can activate or repress transcription. However, for many of these regulators we do not know what type of effector domains they contain, their location in the protein, their activation and repression strengths, and the sequences that are necessary for their functions. Here, we systematically measure the effector activity of more than 100,000 protein fragments tiling across most chromatin regulators and transcription factors in human cells (2,047 proteins). By testing the effect they have when recruited at reporter genes, we annotate 374 activation domains and 715 repression domains, roughly 80% of which are new and have not been previously annotated3-5. Rational mutagenesis and deletion scans across all the effector domains reveal aromatic and/or leucine residues interspersed with acidic, proline, serine and/or glutamine residues are necessary for activation domain activity. Furthermore, most repression domain sequences contain sites for small ubiquitin-like modifier (SUMO)ylation, short interaction motifs for recruiting corepressors or are structured binding domains for recruiting other repressive proteins. We discover bifunctional domains that can both activate and repress, some of which dynamically split a cell population into high- and low-expression subpopulations. Our systematic annotation and characterization of effector domains provide a rich resource for understanding the function of human transcription factors and chromatin regulators, engineering compact tools for controlling gene expression and refining predictive models of effector domain function.

Systematic identification and characterization of repressive domains in Drosophila transcription factors

All multicellular life relies on differential gene expression, determined by regulatory DNA elements and DNA-binding transcription factors that mediate activation and repression via cofactor recruitment. While activators have been extensively characterized, repressors are less well studied: the identities and properties of their repressive domains (RDs) are typically unknown and the specific co-repressors (CoRs) they recruit have not been determined. Here, we develop a high-throughput, next-generation sequencing-based screening method, repressive-domain (RD)-seq, to systematically identify RDs in complex DNA-fragment libraries. Screening more than 200,000 fragments covering the coding sequences of all transcription-related proteins in Drosophila melanogaster, we identify 195 RDs in known repressors and in proteins not previously associated with repression. Many RDs contain recurrent short peptide motifs, which are conserved between fly and human and are required for RD function, as demonstrated by motif mutagenesis. Moreover, we show that RDs that contain one of five distinct repressive motifs interact with and depend on different CoRs, such as Groucho, CtBP, Sin3A, or Smrter. These findings advance our understanding of repressors, their sequences, and the functional impact of sequence-altering mutations and should provide a valuable resource for further studies.

TGA transcription factors-Structural characteristics as basis for functional variability

TGA transcription factors are essential regulators of various cellular processes, their activity connected to different hormonal pathways, interacting proteins and regulatory elements. Belonging to the basic region leucine zipper (bZIP) family, TGAs operate by binding to their target DNA sequence as dimers through a conserved bZIP domain. Despite sharing the core DNA-binding sequence, the TGA paralogues exert somewhat different DNA-binding preferences. Sequence variability of their N- and C-terminal protein parts indicates their importance in defining TGA functional specificity through interactions with diverse proteins, affecting their DNA-binding properties. In this review, we provide a short and concise summary on plant TGA transcription factors from a structural point of view, including the relation of their structural characteristics to their functional roles in transcription regulation.

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.

Identification and functional characterization of transcriptional activators in human cells

Transcription is orchestrated by thousands of transcription factors (TFs) and chromatin-associated proteins, but how these are causally connected to transcriptional activation is poorly understood. Here, we conduct an unbiased proteome-scale screen to systematically uncover human proteins that activate transcription in a natural chromatin context. By combining interaction proteomics and chemical inhibitors, we delineate the preference of these transcriptional activators for specific co-activators, highlighting how even closely related TFs can function via distinct cofactors. We also identify potent transactivation domains among the hits and use AlphaFold2 to predict and experimentally validate interaction interfaces of two activation domains with BRD4. Finally, we show that many novel activators are partners in fusion events in tumors and functionally characterize a myofibroma-associated fusion between SRF and C3orf62, a potent p300-dependent activator. Our work provides a functional catalog of potent transactivators in the human proteome and a platform for discovering transcriptional regulators at genome scale.

fLPS 2.0: rapid annotation of compositionally-biased regions in biological sequences

Compositionally-biased (CB) regions in biological sequences are enriched for a subset of sequence residue types. These can be shorter regions with a concentrated bias (i.e., those termed ‘low-complexity’), or longer regions that have a compositional skew. These regions comprise a prominent class of the uncharacterized ‘dark matter’ of the protein universe. Here, I report the latest version of the fLPS package for the annotation of CB regions, which includes added consideration of DNA sequences, to label the eight possible biased regions of DNA. In this version, the user is now able to restrict analysis to a specified subset of residue types, and also to filter for previously annotated domains to enable detection of discontinuous CB regions. A ‘thorough’ option has been added which enables the labelling of subtler biases, typically made from a skew for several residue types. In the output, protein CB regions are now labelled with bias classes reflecting the physico-chemical character of the biasing residues. The fLPS 2.0 package is available from: https://github.com/pmharrison/flps2 or in a Supplemental File of this paper.

Characterization of the transactivation and nuclear localization functions of Pichia pastoris zinc finger transcription factor Mxr1p

The zinc finger transcription factor Mxr1p regulates the transcription of genes involved in methanol, acetate, and amino acid metabolism of the industrial yeast Pichia pastoris (a.k.a. Komagataella phaffii) by binding to Mxr1p response elements in their promoters. Here, we demonstrate that Mxr1p is a key regulator of ethanol metabolism as well. Using transcriptomic analysis, we identified target genes of Mxr1p that mediate ethanol metabolism, including ALD6-1 encoding an aldehyde dehydrogenase. ALD6-1 is essential for ethanol metabolism, and the ALD6-1 promoter harbors three Mxr1p response elements to which Mxr1p binds in vitro and activates transcription in vivo. We show that a nine-amino acid transactivation domain located between amino acids 365 and 373 of Mxr1p is essential for the transactivation of ALD6-1 to facilitate ethanol metabolism. Mxr1N250, containing the N-terminal 250 amino acids of Mxr1p, localized to the nucleus of cells metabolizing ethanol dependent on basic amino acid residues present between amino acids 75 and 85. While the N-terminal 400 amino acids of Mxr1p are sufficient for the activation of target genes essential for ethanol metabolism, the region between amino acids 401 and 1155 was also required for the regulation of genes essential for methanol metabolism. Finally, we identified several novel genes whose expression is differentially regulated by Mxr1p during methanol metabolism by DNA microarray. This study demonstrates that Mxr1p is a key regulator of ethanol metabolism and provides new insights into the mechanism by which Mxr1p functions as a global regulator of multiple metabolic pathways of P. pastoris.

Activation of gene expression by detergent-like protein domains

The mechanisms by which transcriptional activation domains (tADs) initiate eukaryotic gene expression have been an enigma for decades because most tADs lack specificity in sequence, structure, and interactions with targets. Machine learning analysis of data sets of tAD sequences generated in vivo elucidated several functionality rules: the functional tAD sequences should (i) be devoid of or depleted with basic amino acid residues, (ii) be enriched with aromatic and acidic residues, (iii) be with aromatic residues localized mostly near the terminus of the sequence, and acidic residues localized more internally within a span of 20-30 amino acids, (iv) be with both aromatic and acidic residues preferably spread out in the sequence and not clustered, and (v) not be separated by occasional basic residues. These and other more subtle rules are not absolute, reflecting absence of a tAD consensus sequence, enormous variability, and consistent with surfactant-like tAD biochemical properties. The findings are compatible with the paradigm-shifting nucleosome detergent mechanism of gene expression activation, contributing to the development of the liquid-liquid phase separation model and the biochemistry of near-stochastic functional allosteric interactions.

PARROT is a flexible recurrent neural network framework for analysis of large protein datasets

The rise of high-throughput experiments has transformed how scientists approach biological questions. The ubiquity of large-scale assays that can test thousands of samples in a day has necessitated the development of new computational approaches to interpret this data. Among these tools, machine learning approaches are increasingly being utilized due to their ability to infer complex nonlinear patterns from high-dimensional data. Despite their effectiveness, machine learning (and in particular deep learning) approaches are not always accessible or easy to implement for those with limited computational expertise. Here we present PARROT, a general framework for training and applying deep learning-based predictors on large protein datasets. Using an internal recurrent neural network architecture, PARROT is capable of tackling both classification and regression tasks while only requiring raw protein sequences as input. We showcase the potential uses of PARROT on three diverse machine learning tasks: predicting phosphorylation sites, predicting transcriptional activation function of peptides generated by high-throughput reporter assays, and predicting the fibrillization propensity of amyloid beta with data generated by deep mutational scanning. Through these examples, we demonstrate that PARROT is easy to use, performs comparably to state-of-the-art computational tools, and is applicable for a wide array of biological problems.

Stop codon readthrough alters the activity of a POU/Oct transcription factor during Drosophila development

Background

A number of cellular processes have evolved in metazoans that increase the proteome repertoire in relation to the genome, such as alternative splicing and translation recoding. Another such process, translational stop codon readthrough (SCR), generates C-terminally extended protein isoforms in many eukaryotes, including yeast, plants, insects, and humans. While comparative genome analyses have predicted the existence of programmed SCR in many species including humans, experimental proof of its functional consequences are scarce.

Results

We show that SCR of the Drosophila POU/Oct transcription factor Ventral veins lacking/Drifter (Vvl/Dfr) mRNA is prevalent in certain tissues in vivo, reaching a rate of 50% in the larval prothoracic gland. Phylogenetically, the C-terminal extension is conserved and harbors intrinsically disordered regions and amino acid stretches implied in transcriptional activation. Elimination of Vvl/Dfr translational readthrough by CRISPR/Cas9 mutagenesis changed the expression of a large number of downstream genes involved in processes such as chromatin regulation, neurogenesis, development, and immune response. As a proof-of-principle, we demonstrate that the C-terminal extension of Vvl/Dfr is necessary for correct timing of pupariation, by increasing the capacity to regulate its target genes. The extended Vvl/Dfr isoform acts in synergy with the transcription factor Molting defective (Mld) to increase the expression and biosynthesis of the steroid hormone ecdysone, thereby advancing pupariation. Consequently, late-stage larval development was prolonged and metamorphosis delayed in vvl/dfr readthrough mutants.

Conclusions

We demonstrate that translational recoding of a POU/Oct transcription factor takes place in a highly tissue-specific and temporally controlled manner. This dynamic and regulated recoding is necessary for normal expression of a large number of genes involved in many cellular and developmental processes. Loss of Vvl/Dfr translational readthrough negatively affects steroid hormone biosynthesis and delays larval development and progression into metamorphosis. Thus, this study demonstrates how SCR of a transcription factor can act as a developmental switch in a spatiotemporal manner, feeding into the timing of developmental transitions between different life-cycle stages.

Graphical abstract

Supplementary Information

The online version contains supplementary material available at 10.1186/s12915-021-01106-0.

Simple biochemical features underlie transcriptional activation domain diversity and dynamic, fuzzy binding to Mediator

Gene activator proteins comprise distinct DNA-binding and transcriptional activation domains (ADs). Because few ADs have been described, we tested domains tiling all yeast transcription factors for activation in vivo and identified 150 ADs. By mRNA display, we showed that 73% of ADs bound the Med15 subunit of Mediator, and that binding strength was correlated with activation. AD-Mediator interaction in vitro was unaffected by a large excess of free activator protein, pointing to a dynamic mechanism of interaction. Structural modeling showed that ADs interact with Med15 without shape complementarity (‘fuzzy’ binding). ADs shared no sequence motifs, but mutagenesis revealed biochemical and structural constraints. Finally, a neural network trained on AD sequences accurately predicted ADs in human proteins and in other yeast proteins, including chromosomal proteins and chromatin remodeling complexes. These findings solve the longstanding enigma of AD structure and function and provide a rationale for their role in biology.

Cells adapt and respond to changes by regulating the activity of their genes. To turn genes on or off, they use a family of proteins called transcription factors. Transcription factors influence specific but overlapping groups of genes, so that each gene is controlled by several transcription factors that act together like a dimmer switch to regulate gene activity.

The presence of transcription factors attracts proteins such as the Mediator complex, which activates genes by gathering the protein machines that read the genes. The more transcription factors are found near a specific gene, the more strongly they attract Mediator and the more active the gene is. A specific region on the transcription factor called the activation domain is necessary for this process. The biochemical sequences of these domains vary greatly between species, yet activation domains from, for example, yeast and human proteins are often interchangeable.

To understand why this is the case, Sanborn et al. analyzed the genome of baker’s yeast and identified 150 activation domains, each very different in sequence. Three-quarters of them bound to a subunit of the Mediator complex called Med15. Sanborn et al. then developed a machine learning algorithm to predict activation domains in both yeast and humans. This algorithm also showed that negatively charged and greasy regions on the activation domains were essential to be activated by the Mediator complex.

Further analyses revealed that activation domains used different poses to bind multiple sites on Med15, a behavior known as ‘fuzzy’ binding. This creates a high overall affinity even though the binding strength at each individual site is low, enabling the protein complexes to remain dynamic. These weak interactions together permit fine control over the activity of several genes, allowing cells to respond quickly and precisely to many changes.

The computer algorithm used here provides a new way to identify activation domains across species and could improve our understanding of how living things grow, adapt and evolve. It could also give new insights into mechanisms of disease, particularly cancer, where transcription factors are often faulty.

Protein self-assembly: A new frontier in cell signaling

Long viewed as paradigm-shifting, but rare, prions have recently been discovered in all domains of life. Protein sequences that can drive this form of self-assembly are strikingly common in eukaryotic proteomes, where they are enriched in proteins involved in information flow and signal transduction. Although prions were thought to be a consequence of random errors in protein folding, recent studies suggest that prion formation can be a controlled process initiated by defined cellular signals. Many are present in normal biological contexts, yet are invisible to most technologies used to interrogate the proteome. Here, we review mechanisms by which protein self-assembly can create a stable record of past stimuli, altering adaptive responses, and how prion behavior is controlled by signaling processes. We touch on the diverse implications that this has for normal biological function and regulation, ranging from drug resistance in fungi to the innate immune response in humans. Finally, we discuss the potential for prion domains in transcription factors and RNA-binding proteins to orchestrate heritable gene expression changes in response to transient signals, such as during development.

The duality of PRDM proteins: epigenetic and structural perspectives

PRDF1 and RIZ1 homology domain containing (PRDMs) are a subfamily of Krüppel-like zinc finger proteins controlling key processes in metazoan development and in cancer. PRDMs exhibit unique dualities: (a) PR domain/ZNF arrays-their structure combines a SET-like domain known as a PR domain, typically found in methyltransferases, with a variable array of C2H2 zinc fingers (ZNF) characteristic of DNA-binding transcription factors; (b) transcriptional activators/repressors-their physiological function is context- and cell-dependent; mechanistically, some PRDMs have a PKMT activity and directly catalyze histone lysine methylation, while others are rather pseudomethyltransferases and act by recruiting transcriptional cofactors; (c) oncogenes/tumor suppressors-their pathological function depends on the specific PRDM isoform expressed during tumorigenesis. This duality is well known as the 'Yin and Yang' of PRDMs and involves a complex regulation of alternative splicing or alternative promoter usage, to generate full-length or PR-deficient isoforms with opposing functions in cancer. In conclusion, once their dualities are fully appreciated, PRDMs represent a promising class of targets in oncology by virtue of their widespread upregulation across multiple tumor types and their somatic dispensability, conferring a broad therapeutic window and limited toxic side effects. The recent discovery of a first-in-class compound able to inhibit PRDM9 activity has paved the way for the identification of further small molecular inhibitors able to counteract PRDM oncogenic activity.

Arabidopsis Abscisic Acid Repressor 1 is a susceptibility hub that interacts with multiple Pseudomonas syringae effectors

Pathogens secrete effector proteins into host cells to suppress host immunity and promote pathogen virulence, although many features at the molecular interface of host-pathogen interactions remain to be characterized. In a yeast two-hybrid assay, we found that the Pseudomonas syringae effector HopZ1a interacts with the Arabidopsis transcriptional regulator Abscisic Acid Repressor 1 (ABR1). Further analysis revealed that ABR1 interacts with multiple P. syringae effectors, suggesting that it may be targeted as a susceptibility hub. Indeed, loss-of-function abr1 mutants exhibit reduced susceptibility to a number of P. syringae strains. The ABR1 protein comprises a conserved APETALA2 (AP2) domain flanked by long regions of predicted structural disorder. We verified the DNA-binding activity of the AP2 domain and demonstrated that the disordered domains act redundantly to enhance DNA binding and to facilitate transcriptional activation by ABR1. Finally, we compared gene expression profiles from wild-type and abr1 plants following inoculation with P. syringae, which suggested that the reduced susceptibility of abr1 mutants is due to the loss of a virulence target rather than an enhanced immune response. These data highlight ABR1 as a functionally important component at the host-pathogen interface.

Insights into gene regulation: From regulatory genomic elements to DNA-protein and protein-protein interactions

Transcription is orchestrated by non-coding regulatory elements embedded in chromatin, which exist within the larger context of chromosome topology. Here, we review recent insights into the functions of non-coding regulatory elements and their protein interactors during transcription control. A picture emerges in which the topological environment constraints enhancer-promoter interactions and specific enhancer-bound proteins with distinct promoter-compatibilities refine target promoter choice. Such compatibilities are encoded within the sequences of enhancers and promoters and realized by diverse transcription factors and cofactors with distinct biochemical activities. An emerging property of transcription factors and cofactors is the formation of nuclear microenvironments or membraneless compartments that can have properties of phase-separated liquids. These environments are able to selectively enrich certain proteins and small molecules over others. Further investigation into the interaction of transcriptional regulators with themselves and regulatory DNA elements will help reveal the complexities of gene regulation within the context of the nucleus.

High-Throughput Discovery and Characterization of Human Transcriptional Effectors

Thousands of proteins localize to the nucleus; however, it remains unclear which contain transcriptional effectors. Here, we develop HT-recruit, a pooled assay where protein libraries are recruited to a reporter, and their transcriptional effects are measured by sequencing. Using this approach, we measure gene silencing and activation for thousands of domains. We find a relationship between repressor function and evolutionary age for the KRAB domains, discover that Homeodomain repressor strength is collinear with Hox genetic organization, and identify activities for several domains of unknown function. Deep mutational scanning of the CRISPRi KRAB maps the co-repressor binding surface and identifies substitutions that improve stability/silencing. By tiling 238 proteins, we find repressors as short as ten amino acids. Finally, we report new activator domains, including a divergent KRAB. These results provide a resource of 600 human proteins containing effectors and demonstrate a scalable strategy for assigning functions to protein domains.

Unexpected specificity within dynamic transcriptional protein-protein complexes

A key functional event in eukaryotic gene activation is the formation of dynamic protein-protein interaction networks between transcriptional activators and transcriptional coactivators. Seemingly incongruent with the tight regulation of transcription, many biochemical and biophysical studies suggest that activators use nonspecific hydrophobic and/or electrostatic interactions to bind to coactivators, with few if any specific contacts. Here a mechanistic dissection of a set of representative dynamic activator•coactivator complexes, comprised of the ETV/PEA3 family of activators and the coactivator Med25, reveals a different molecular recognition model. The data demonstrate that small sequence variations within an activator family significantly redistribute the conformational ensemble of the complex while not affecting overall affinity, and distal residues within the activator-not often considered as contributing to binding-play a key role in mediating conformational redistribution. The ETV/PEA3•Med25 ensembles are directed by specific contacts between the disordered activator and the Med25 interface, which is facilitated by structural shifts of the coactivator binding surface. Taken together, these data highlight the critical role coactivator plasticity plays in recognition of disordered activators and indicate that molecular recognition models of disordered proteins must consider the ability of the binding partners to mediate specificity.

Epigenetic regulators of neuronal ferroptosis identify novel therapeutics for neurological diseases: HDACs, transglutaminases, and HIF prolyl hydroxylases

A major thrust of our laboratory has been to identify how physiological stress is transduced into transcriptional responses that feed back to overcome the inciting stress or its consequences, thereby fostering survival and repair. To this end, we have adopted the use of an in vitro model of ferroptosis, a caspase-independent, but iron-dependent form of cell death (Dixon et al., 2012; Ratan, 2020). In this review, we highlight three distinct epigenetic targets that have evolved from our studies and which have been validated in vivo studies. In the first section, we discuss our studies of broad, pan-selective histone deacetylase (HDAC) inhibitors in ferroptosis and how these studies led to the validation of HDAC inhibitors as candidate therapeutics in a host of disease models. In the second section, we discuss our studies that revealed a role for transglutaminase as an epigenetic modulator of proferroptotic pathways and how these studies set the stage for recent elucidation of monoamines as post-translation modifiers of histone function. In the final section, we discuss our studies of iron-, 2-oxoglutarate-, and oxygen-dependent dioxygenases and the role of one family of these enzymes, the HIF prolyl hydroxylases, in mediating transcriptional events necessary for ferroptosis in vitro and for dysfunction in a host of neurological conditions. Overall, our studies highlight the importance of epigenetic proteins in mediating prodeath and prosurvival responses to ferroptosis. Pharmacological agents that target these epigenetic proteins are showing robust beneficial effects in diverse rodent models of stroke, Parkinson's disease, Huntington's disease, and Alzheimer's disease.

Multivalent and Bidirectional Binding of Transcriptional Transactivation Domains to the MED25 Coactivator

The human mediator subunit MED25 acts as a coactivator that binds the transcriptional activation domains (TADs) present in various cellular and viral gene-specific transcription factors. Previous studies, including on NMR measurements and site-directed mutagenesis, have only yielded low-resolution models that are difficult to refine further by experimental means. Here, we apply computational molecular dynamics simulations to study the interactions of two different TADs from the human transcription factor ETV5 (ERM) and herpes virus VP16-H1 with MED25. Like other well-studied coactivator-TAD complexes, the interactions of these intrinsically disordered domains with the coactivator surface are temporary and highly dynamic (‘fuzzy’). Due to the fact that the MED25 TAD-binding region is organized as an elongated cleft, we specifically asked whether these TADs are capable of binding in either orientation and how this could be achieved structurally and energetically. The binding of both the ETV5 and VP16-TADs in either orientation appears to be possible but occurs in a conformationally distinct manner and utilizes different sets of hydrophobic residues present in the TADs to drive the interactions. We propose that MED25 and at least a subset of human TADs specifically evolved a redundant set of molecular interaction patterns to allow binding to particular coactivators without major prior spatial constraints.

Mediator complex subunit Med19 binds directly GATA transcription factors and is required with Med1 for GATA-driven gene regulation in vivo

The evolutionarily conserved multiprotein Mediator complex (MED) serves as an interface between DNA-bound transcription factors (TFs) and the RNA Pol II machinery. It has been proposed that each TF interacts with a dedicated MED subunit to induce specific transcriptional responses. But are these binary partnerships sufficient to mediate TF functions? We have previously established that the Med1 Mediator subunit serves as a cofactor of GATA TFs in Drosophila, as shown in mammals. Here, we observe mutant phenotype similarities between another subunit, Med19, and the Drosophila GATA TF Pannier (Pnr), suggesting functional interaction. We further show that Med19 physically interacts with the Drosophila GATA TFs, Pnr and Serpent (Srp), in vivo and in vitro through their conserved C-zinc finger domains. Moreover, Med19 loss of function experiments in vivo or in cellulo indicate that it is required for Pnr- and Srp-dependent gene expression, suggesting general GATA cofactor functions. Interestingly, Med19 but not Med1 is critical for the regulation of all tested GATA target genes, implying shared or differential use of MED subunits by GATAs depending on the target gene. Lastly, we show a direct interaction between Med19 and Med1 by GST pulldown experiments indicating privileged contacts between these two subunits of the MED middle module. Together, these findings identify Med19/Med1 as a composite GATA TF interface and suggest that binary MED subunit-TF partnerships are probably oversimplified models. We propose several mechanisms to account for the transcriptional regulation of GATA-targeted genes.

Global translation during early development depends on the essential transcription factor PRDM10

Members of the PR/SET domain-containing (PRDM) family of zinc finger transcriptional regulators play diverse developmental roles. PRDM10 is a yet uncharacterized family member, and its function in vivo is unknown. Here, we report an essential requirement for PRDM10 in pre-implantation embryos and embryonic stem cells (mESCs), where loss of PRDM10 results in severe cell growth inhibition. Detailed genomic and biochemical analyses reveal that PRDM10 functions as a sequence-specific transcription factor. We identify Eif3b, which encodes a core component of the eukaryotic translation initiation factor 3 (eIF3) complex, as a key downstream target, and demonstrate that growth inhibition in PRDM10-deficient mESCs is in part mediated through EIF3B-dependent effects on global translation. Our work elucidates the molecular function of PRDM10 in maintaining global translation, establishes its essential role in early embryonic development and mESC homeostasis, and offers insights into the functional repertoire of PRDMs as well as the transcriptional mechanisms regulating translation.

A High-Throughput Screen for Transcription Activation Domains Reveals Their Sequence Features and Permits Prediction by Deep Learning

Acidic transcription activation domains (ADs) are encoded by a wide range of seemingly unrelated amino acid sequences, making it difficult to recognize features that promote their dynamic behavior, "fuzzy" interactions, and target specificity. We screened a large set of random 30-mer peptides for AD function in yeast and trained a deep neural network (ADpred) on the AD-positive and -negative sequences. ADpred identifies known acidic ADs within transcription factors and accurately predicts the consequences of mutations. Our work reveals that strong acidic ADs contain multiple clusters of hydrophobic residues near acidic side chains, explaining why ADs often have a biased amino acid composition. ADs likely use a binding mechanism similar to avidity where a minimum number of weak dynamic interactions are required between activator and target to generate biologically relevant affinity and in vivo function. This mechanism explains the basis for fuzzy binding observed between acidic ADs and targets.

Tuning up Transcription Factors for Therapy

The recent developments in the delivery and design of transcription factors put their therapeutic applications within reach, exemplified by cell replacement, cancer differentiation and T-cell based cancer therapies. The success of such applications depends on the efficacy and precision in the action of transcription factors. The biophysical and genetic characterization of the paradigmatic prokaryotic repressors, LacI and TetR and the designer transcription factors, transcription activator-like effector (TALE) and CRISPR-dCas9 revealed common principles behind their efficacy, which can aid the optimization of transcriptional activators and repressors. Further studies will be required to analyze the linkage between dissociation constants and enzymatic activity, the role of phase separation and squelching in activation and repression and the long-range interaction of transcription factors with epigenetic regulators in the context of the chromosomes. Understanding these mechanisms will help to tailor natural and synthetic transcription factors to the needs of specific applications.

Biophysical Techniques for Target Validation and Drug Discovery in Transcription-Targeted Therapy

In the post-genome era, pathologies become associated with specific gene expression profiles and defined molecular lesions can be identified. The traditional therapeutic strategy is to block the identified aberrant biochemical activity. However, an attractive alternative could aim at antagonizing key transcriptional events underlying the pathogenesis, thereby blocking the consequences of a disorder, irrespective of the original biochemical nature. This approach, called transcription therapy, is now rendered possible by major advances in biophysical technologies. In the last two decades, techniques have evolved to become key components of drug discovery platforms, within pharmaceutical companies as well as academic laboratories. This review outlines the current biophysical strategies for transcription manipulation and provides examples of successful applications. It also provides insights into the future development of biophysical methods in drug discovery and personalized medicine.