Different gene regulation strategies revealed by analysis of binding motifs

DNA-guided transcription factor interactions extend human gene regulatory code

In the same way that the mRNA-binding specificities of transfer RNAs define the genetic code, the DNA-binding specificities of transcription factors (TFs) form the molecular basis of the gene regulatory code1,2. The human gene regulatory code is much more complex than the genetic code, in particular because there are more than 1,600 TFs that commonly interact with each other. TF-TF interactions are required for specifying cell fate and executing cell-type-specific transcriptional programs. Despite this, the landscape of interactions between DNA-bound TFs is poorly defined. Here we map the biochemical interactions between DNA-bound TFs using CAP-SELEX, a method that can simultaneously identify individual TF binding preferences, TF-TF interactions and the DNA sequences that are bound by the interacting complexes. A screen of more than 58,000 TF-TF pairs identified 2,198 interacting TF pairs, 1,329 of which preferentially bound to their motifs arranged in a distinct spacing and/or orientation. We also discovered 1,131 TF-TF composite motifs that were markedly different from the motifs of the individual TFs. In total, we estimate that the screen identified between 18% and 47% of all human TF-TF motifs. The novel composite motifs we found were enriched in cell-type-specific elements, active in vivo and more likely to be formed between developmentally co-expressed TFs. Furthermore, TFs that define embryonic axes commonly interacted with different TFs and bound to distinct motifs, explaining how TFs with a similar specificity can define distinct cell types along developmental axes.

Specificity landscapes of 40 R2R3-MYBs reveal how paralogs target different cis-elements by homodimeric binding

Paralogous transcription factors (TFs) frequently recognize highly similar DNA motifs. Homodimerization can help distinguish them according to their different dimeric configurations. Here, by studying R2R3-MYB TFs, we show that homodimerization can also directly change the recognized DNA motifs to distinguish between similar TFs. By high-throughput SELEX, we profiled the specificity landscape for 40 R2R3-MYBs of subfamily VIII and curated 833 motif models. The dimeric models show that homodimeric binding has evoked specificity changes for AtMYBs. Focusing on AtMYB2 as an example, we show that homodimerization has modified its specificity and allowed it to recognize additional cis-regulatory sequences that are different from the closely related CCWAA-box AtMYBs and are unique among all AtMYBs. Genomic sites described by the modified dimeric specificities of AtMYB2 are conserved in evolution and involved in AtMYB2-specific transcriptional activation. Collectively, this study provides rich data on sequence preferences of VIII R2R3-MYBs and suggests an alternative mechanism that guides closely related TFs to respective cis-regulatory sites.

Intrinsically disordered regions as facilitators of the transcription factor target search

Transcription factors (TFs) contribute to organismal development and function by regulating gene expression. Despite decades of research, the factors determining the specificity and speed at which eukaryotic TFs detect their target binding sites remain poorly understood. Recent studies have pointed to intrinsically disordered regions (IDRs) within TFs as key regulators of the process by which TFs find their target sites on DNA (the TF target search). However, IDRs are challenging to study because they can confer specificity despite low sequence complexity and can be functionally conserved despite rapid sequence divergence. Nevertheless, emerging computational and experimental approaches are beginning to elucidate the sequence-function relationship within the IDRs of TFs. Additional insights are informing potential mechanisms underlying the IDR-directed search for the DNA targets of TFs, including incorporation into biomolecular condensates, facilitating TF co-localization, and the hypothesis that IDRs recognize and directly interact with specific genomic regions.

Thermodynamic principles link in vitro transcription factor affinities to single-molecule chromatin states in cells

The molecular details governing transcription factor (TF) binding and the formation of accessible chromatin are not yet quantitatively understood - including how sequence context modulates affinity, how TFs search DNA, the kinetics of TF occupancy, and how motif grammars coordinate binding. To resolve these questions for a human TF, erythroid Krüppel-like factor (eKLF/KLF1), we quantitatively compare, in high throughput, in vitro TF binding rates and affinities with in vivo single molecule TF and nucleosome occupancies across engineered DNA sequences. We find that 40-fold flanking sequence effects on affinity are consistent with distal flanks tuning TF search parameters and captured by a linear energy model. Motif recognition probability, rather than time in the bound state, drives affinity changes, and in vitro and in nuclei measurements exhibit consistent, minutes-long TF residence times. Finally, pairing in vitro biophysical parameters with thermodynamic models accurately predicts in vivo single-molecule chromatin states for unseen motif grammars.

Chromatin enables precise and scalable gene regulation with factors of limited specificity

Biophysical constraints limit the specificity with which transcription factors (TFs) can target regulatory DNA. While individual nontarget binding events may be low affinity, the sheer number of such interactions could present a challenge for gene regulation by degrading its precision or possibly leading to an erroneous induction state. Chromatin can prevent nontarget binding by rendering DNA physically inaccessible to TFs, at the cost of energy-consuming remodeling orchestrated by pioneer factors (PFs). Under what conditions and by how much can chromatin reduce regulatory errors on a global scale? We use a theoretical approach to compare two scenarios for gene regulation: one that relies on TF binding to free DNA alone and one that uses a combination of TFs and chromatin-regulating PFs to achieve desired gene expression patterns. We find, first, that chromatin effectively silences groups of genes that should be simultaneously OFF, thereby allowing more accurate graded control of expression for the remaining ON genes. Second, chromatin buffers the deleterious consequences of nontarget binding as the number of OFF genes grows, permitting a substantial expansion in regulatory complexity. Third, chromatin-based regulation productively co-opts nontarget TF binding for ON genes in order to establish a "leaky" baseline expression level, which targeted activator or repressor binding subsequently up- or down-modulates. Thus, on a global scale, using chromatin simultaneously alleviates pressure for high specificity of regulatory interactions and enables an increase in genome size with minimal impact on global expression error.

Tissue-specific chromatin accessibility and transcriptional regulation in maize cold stress response

Maize, a vital crop globally, faces significant yield losses due to its sensitivity to cold stress, especially in temperate regions. Understanding the molecular mechanisms governing maize response to cold stress is crucial for developing strategies to enhance cold tolerance. However, the precise chromatin-level regulatory mechanisms involved remain largely unknown. In this study, we employed DNase-seq and RNA-seq techniques to investigate chromatin accessibility and gene expression changes in maize root, stem, and leaf tissues subjected to cold treatment. We discovered widespread changes in chromatin accessibility and gene expression across these tissues, with strong tissue specificity. Cold stress-induced DNase I hypersensitive sites (coiDHSs) were associated with differentially expressed genes, suggesting a direct link between chromatin accessibility and gene regulation under cold stress. Motif enrichment analysis identified ERF transcription factors (TFs) as central regulators conserved across tissues, with ERF5 emerging as pivotal in the cold response regulatory network. Additionally, TF co-localization analysis highlighted six TF pairs (ERF115-SHN3, ERF9-LEP, ERF7-SHN3, LEP-SHN3, LOB-SHN3, and AS2-LOB) conserved across tissues but showing tissue-specific binding preferences. These findings indicate intricate regulatory networks in maize cold response. Overall, our study provides insights into the chromatin-level regulatory mechanisms underpinning maize adaptive response to cold stress, offering potential targets for enhancing cold tolerance in agricultural contexts.

NetREm: Network Regression Embeddings reveal cell-type transcription factor coordination for gene regulation

Motivation

Transcription factor (TF) coordination plays a key role in gene regulation via direct and/or indirect protein-protein interactions (PPIs) and co-binding to regulatory elements on DNA. Single-cell technologies facilitate gene expression measurement for individual cells and cell-type identification, yet the connection between TF-TF coordination and target gene (TG) regulation of various cell types remains unclear.

Results

To address this, we introduce our innovative computational approach, Network Regression Embeddings (NetREm), to reveal cell-type TF-TF coordination activities for TG regulation. NetREm leverages network-constrained regularization, using prior knowledge of PPIs among TFs, to analyze single-cell gene expression data, uncovering cell-type coordinating TFs and identifying revolutionary TF-TG candidate regulatory network links. NetREm's performance is validated using simulation studies and benchmarked across several datasets in humans, mice, yeast. Further, we showcase NetREm's ability to prioritize valid novel human TF-TF coordination links in 9 peripheral blood mononuclear and 42 immune cell sub-types. We apply NetREm to examine cell-type networks in central and peripheral nerve systems (e.g. neuronal, glial, Schwann cells) and in Alzheimer's disease versus Controls. Top predictions are validated with experimental data from rat, mouse, and human models. Additional functional genomics data helps link genetic variants to our TF-TG regulatory and TF-TF coordination networks.

Availability and implementation

https://github.com/SaniyaKhullar/NetREm.

Single-molecule states link transcription factor binding to gene expression

The binding of multiple transcription factors (TFs) to genomic enhancers drives gene expression in mammalian cells1. However, the molecular details that link enhancer sequence to TF binding, promoter state and transcription levels remain unclear. Here we applied single-molecule footprinting2,3 to measure the simultaneous occupancy of TFs, nucleosomes and other regulatory proteins on engineered enhancer-promoter constructs with variable numbers of TF binding sites for both a synthetic TF and an endogenous TF involved in the type I interferon response. Although TF binding events on nucleosome-free DNA are independent, activation domains recruit cofactors that destabilize nucleosomes, driving observed TF binding cooperativity. Average TF occupancy linearly determines promoter activity, and we decompose TF strength into separable binding and activation terms. Finally, we develop thermodynamic and kinetic models that quantitatively predict both the enhancer binding microstates and gene expression dynamics. This work provides a template for the quantitative dissection of distinct contributors to gene expression, including TF activation domains, concentration, binding affinity, binding site configuration and recruitment of chromatin regulators.

Functional characteristics and computational model of abundant hyperactive loci in the human genome

Enhancers and promoters are classically considered to be bound by a small set of transcription factors (TFs) in a sequence-specific manner. This assumption has come under increasing skepticism as the datasets of ChIP-seq assays of TFs have expanded. In particular, high-occupancy target (HOT) loci attract hundreds of TFs with often no detectable correlation between ChIP-seq peaks and DNA-binding motif presence. Here, we used a set of 1003 TF ChIP-seq datasets (HepG2, K562, H1) to analyze the patterns of ChIP-seq peak co-occurrence in combination with functional genomics datasets. We identified 43,891 HOT loci forming at the promoter (53%) and enhancer (47%) regions. HOT promoters regulate housekeeping genes, whereas HOT enhancers are involved in tissue-specific process regulation. HOT loci form the foundation of human super-enhancers and evolve under strong negative selection, with some of these loci being located in ultraconserved regions. Sequence-based classification analysis of HOT loci suggested that their formation is driven by the sequence features, and the density of mapped ChIP-seq peaks across TF-bound loci correlates with sequence features and the expression level of flanking genes. Based on the affinities to bind to promoters and enhancers we detected five distinct clusters of TFs that form the core of the HOT loci. We report an abundance of HOT loci in the human genome and a commitment of 51% of all TF ChIP-seq binding events to HOT locus formation thus challenging the classical model of enhancer activity and propose a model of HOT locus formation based on the existence of large transcriptional condensates.

GHT-SELEX demonstrates unexpectedly high intrinsic sequence specificity and complex DNA binding of many human transcription factors

A long-standing challenge in human regulatory genomics is that transcription factor (TF) DNA-binding motifs are short and degenerate, while the genome is large. Motif scans therefore produce many false-positive binding site predictions. By surveying 179 TFs across 25 families using >1,500 cyclic in vitro selection experiments with fragmented, naked, and unmodified genomic DNA - a method we term GHT-SELEX (Genomic HT-SELEX) - we find that many human TFs possess much higher sequence specificity than anticipated. Moreover, genomic binding regions from GHT-SELEX are often surprisingly similar to those obtained in vivo (i.e. ChIP-seq peaks). We find that comparable specificity can also be obtained from motif scans, but performance is highly dependent on derivation and use of the motifs, including accounting for multiple local matches in the scans. We also observe alternative engagement of multiple DNA-binding domains within the same protein: long C2H2 zinc finger proteins often utilize modular DNA recognition, engaging different subsets of their DNA binding domain (DBD) arrays to recognize multiple types of distinct target sites, frequently evolving via internal duplication and divergence of one or more DBDs. Thus, contrary to conventional wisdom, it is common for TFs to possess sufficient intrinsic specificity to independently delineate cellular targets.

Massively parallel binding assay (MPBA) reveals limited transcription factor binding cooperativity, challenging models of specificity

DNA-binding domains (DBDs) within transcription factors (TFs) recognize short sequence motifs that are highly abundant in genomes. In vivo, TFs bind only a small subset of motif occurrences, which is often attributed to the cooperative binding of interacting TFs at proximal motifs. However, large-scale testing of this model is still lacking. Here, we describe a novel method allowing parallel measurement of TF binding to thousands of designed sequences within yeast cells and apply it to quantify the binding of dozens of TFs to libraries of regulatory regions containing clusters of binding motifs, systematically mutating all motif combinations. With few exceptions, TF occupancies were well explained by independent binding to individual motifs, with motif cooperation being of only limited effects. Our results challenge the general role of motif combinatorics in directing TF genomic binding and open new avenues for exploring the basis of protein-DNA interactions within cells.

Combinatorial effector targeting (COMET) for transcriptional modulation and locus-specific biochemistry

Understanding how human gene expression is coordinately regulated by functional units of proteins across the genome remains a major biological goal. Here, we present COMET, a high-throughput screening platform for combinatorial effector targeting for the identification of transcriptional modulators. We generate libraries of combinatorial dCas9-based fusion proteins, containing two to six effector domains, allowing us to systematically investigate more than 110,000 combinations of effector proteins at endogenous human loci for their influence on transcription. Importantly, we keep full proteins or domains intact, maintaining catalytic cores and surfaces for protein-protein interactions. We observe more than 5800 significant hits that modulate transcription, we demonstrate cell type specific transcriptional modulation, and we further investigate epistatic relationships between our effector combinations. We validate unexpected combinations as synergistic or buffering, emphasizing COMET as both a method for transcriptional effector discovery, and as a functional genomics tool for identifying novel domain interactions and directing locus-specific biochemistry.

How to scan naked DNA using promiscuous recognition and no clamping: a model for pioneer transcription factors

Most DNA scanning proteins uniquely recognize their cognate sequence motif and slide on DNA assisted by some sort of clamping interface. The pioneer transcription factors that control cell fate in eukaryotes must forgo both elements to gain access to DNA in naked and chromatin forms; thus, whether or how these factors scan naked DNA is unknown. Here, we use single-molecule techniques to investigate naked DNA scanning by the Engrailed homeodomain (enHD) as paradigm of highly promiscuous recognition and open DNA binding interface. We find that enHD scans naked DNA quite effectively, and about 200000-fold faster than expected for a continuous promiscuous slide. To do so, enHD scans about 675 bp of DNA in 100 ms and then redeploys stochastically to another location 530 bp afar in just 10 ms. During the scanning phase enHD alternates between slow- and medium-paced modes every 3 and 40 ms, respectively. We also find that enHD binds nucleosomes and does so with enhanced affinity relative to naked DNA. Our results demonstrate that pioneer-like transcription factors can in principle do both, target nucleosomes and scan active DNA efficiently. The hybrid scanning mechanism used by enHD appears particularly well suited for the highly complex genomic signals of eukaryotic cells.

Genome access is transcription factor-specific and defined by nucleosome position

Mammalian gene expression is controlled by transcription factors (TFs) that engage sequence motifs in a chromatinized genome, where nucleosomes can restrict DNA access. Yet, how nucleosomes affect individual TFs remains unclear. Here, we measure the ability of over one hundred TF motifs to recruit TFs in a defined chromosomal locus in mouse embryonic stem cells. This identifies a set sufficient to enable the binding of TFs with diverse tissue specificities, functions, and DNA-binding domains. These chromatin-competent factors are further classified when challenged to engage motifs within a highly phased nucleosome. The pluripotency factors OCT4-SOX2 preferentially engage non-nucleosomal and entry-exit motifs, but not nucleosome-internal sites, a preference that also guides binding genome wide. By contrast, factors such as BANP, REST, or CTCF engage throughout, causing nucleosomal displacement. This supports that TFs vary widely in their sensitivity to nucleosomes and that genome access is TF specific and influenced by nucleosome position in the cell.

Discerning the Role of DNA Sequence, Shape, and Flexibility in Recognition by Drosophila Transcription Factors

The precise spatial and temporal orchestration of gene expression is crucial for the ontogeny of an organism and is mainly governed by transcription factors (TFs). The mechanism of recognition of cognate sites amid millions of base pairs in the genome by TFs is still incompletely understood. In this study, we focus on DNA sequence composition, shape, and flexibility preferences of 28 quintessential TFs from Drosophila melanogaster that are critical to development and body patterning mechanisms. Our study finds that TFs exhibit distinct predilections for DNA shape, flexibility, and sequence compositions in the proximity of transcription factor binding sites (TFBSs). Notably, certain zinc finger proteins prefer GC-rich areas with less negative propeller twist, while homeodomains mainly seek AT-rich regions with a more negative propeller twist at their sites. Intriguingly, while numerous cofactors share similar binding site preferences and bind closer to each other in the genome, some cofactors that have different preferences bind farther apart. These findings shed light on TF DNA recognition and provide novel insights into possible cofactor binding and transcriptional regulation mechanisms.

TFscope: systematic analysis of the sequence features involved in the binding preferences of transcription factors

Characterizing the binding preferences of transcription factors (TFs) in different cell types and conditions is key to understand how they orchestrate gene expression. Here, we develop TFscope, a machine learning approach that identifies sequence features explaining the binding differences observed between two ChIP-seq experiments targeting either the same TF in two conditions or two TFs with similar motifs (paralogous TFs). TFscope systematically investigates differences in the core motif, nucleotide environment and co-factor motifs, and provides the contribution of each key feature in the two experiments. TFscope was applied to > 305 ChIP-seq pairs, and several examples are discussed.

Living in a noisy world-origins of gene expression noise and its impact on cellular decision-making

The expression level of a gene can vary between genetically identical cells under the same environmental condition-a phenomenon referred to as gene expression noise. Several studies have now elucidated a central role of transcription factors in the generation of expression noise. Transcription factors, as the key components of gene regulatory networks, drive many important cellular decisions in response to cellular and environmental signals. Therefore, a very relevant question is how expression noise impacts gene regulation and influences cellular decision-making. In this Review, we summarize the current understanding of the molecular origins of expression noise, highlighting the role of transcription factors in this process, and discuss the ways in which noise can influence cellular decision-making. As advances in single-cell technologies open new avenues for studying expression noise as well as gene regulatory circuits, a better understanding of the influence of noise on cellular decisions will have important implications for many biological processes.

Position-dependent function of human sequence-specific transcription factors

Patterns of transcriptional activity are encoded in our genome through regulatory elements such as promoters or enhancers that, paradoxically, contain similar assortments of sequence-specific transcription factor (TF) binding sites1-3. Knowledge of how these sequence motifs encode multiple, often overlapping, gene expression programs is central to understanding gene regulation and how mutations in non-coding DNA manifest in disease4,5. Here, by studying gene regulation from the perspective of individual transcription start sites (TSSs), using natural genetic variation, perturbation of endogenous TF protein levels and massively parallel analysis of natural and synthetic regulatory elements, we show that the effect of TF binding on transcription initiation is position dependent. Analysing TF-binding-site occurrences relative to the TSS, we identified several motifs with highly preferential positioning. We show that these patterns are a combination of a TF's distinct functional profiles-many TFs, including canonical activators such as NRF1, NFY and Sp1, activate or repress transcription initiation depending on their precise position relative to the TSS. As such, TFs and their spacing collectively guide the site and frequency of transcription initiation. More broadly, these findings reveal how similar assortments of TF binding sites can generate distinct gene regulatory outcomes depending on their spatial configuration and how DNA sequence polymorphisms may contribute to transcription variation and disease and underscore a critical role for TSS data in decoding the regulatory information of our genome.

Exploring the enigma: history, present, and future of long non-coding RNAs in cancer

Long noncoding RNAs (lncRNAs), which are more than 200 nucleotides in length and do not encode proteins, play crucial roles in governing gene expression at both the transcriptional and posttranscriptional levels. These molecules demonstrate specific expression patterns in various tissues and developmental stages, suggesting their involvement in numerous developmental processes and diseases, notably cancer. Despite their widespread acknowledgment and the growing enthusiasm surrounding their potential as diagnostic and prognostic biomarkers, the precise mechanisms through which lncRNAs function remain inadequately understood. A few lncRNAs have been studied in depth, providing valuable insights into their biological activities and suggesting emerging functional themes and mechanistic models. However, the extent to which the mammalian genome is transcribed into functional noncoding transcripts is still a matter of debate. This review synthesizes our current understanding of lncRNA biogenesis, their genomic contexts, and their multifaceted roles in tumorigenesis, highlighting their potential in cancer-targeted therapy. By exploring historical perspectives alongside recent breakthroughs, we aim to illuminate the diverse roles of lncRNA and reflect on the broader implications of their study for understanding genome evolution and function, as well as for advancing clinical applications.

Structural dynamics in chromatin unraveling by pioneer transcription factors

Pioneer transcription factors are proteins with a dual function. First, they regulate transcription by binding to nucleosome-free DNA regulatory elements. Second, they bind to DNA while wrapped around histone proteins in the chromatin and mediate chromatin opening. The molecular mechanisms that connect the two functions are yet to be discovered. In recent years, pioneer factors received increased attention mainly because of their crucial role in promoting cell fate transitions that could be used for regenerative therapies. For example, the three factors required to induce pluripotency in somatic cells, Oct4, Sox2, and Klf4 were classified as pioneer factors and studied extensively. With this increased attention, several structures of complexes between pioneer factors and chromatin structural units (nucleosomes) have been resolved experimentally. Furthermore, experimental and computational approaches have been designed to study two unresolved, key scientific questions: First, do pioneer factors induce directly local opening of nucleosomes and chromatin fibers upon binding? And second, how do the unstructured tails of the histones impact the structural dynamics involved in such conformational transitions? Here we review the current knowledge about transcription factor-induced nucleosome dynamics and the role of the histone tails in this process. We discuss what is needed to bridge the gap between the static views obtained from the experimental structures and the key structural dynamic events in chromatin opening. Finally, we propose that integrating nuclear magnetic resonance spectroscopy with molecular dynamics simulations is a powerful approach to studying pioneer factor-mediated dynamics of nucleosomes and perhaps small chromatin fibers using native DNA sequences.

DNA methylation-dependent and -independent binding of CDX2 directs activation of distinct developmental and homeostatic genes

Precise spatiotemporal and cell type-specific gene expression is essential for proper tissue development and function. Transcription factors (TFs) guide this process by binding to developmental stage-specific targets and establishing an appropriate enhancer landscape. In turn, DNA and chromatin modifications direct the genomic binding of TFs. However, how TFs navigate various chromatin features and selectively bind a small portion of the millions of possible genomic target loci is still not well understood. Here we show that Cdx2 - a pioneer TF that binds distinct targets in developing versus adult intestinal epithelial cells - has a preferential affinity for a non-canonical CpG-containing motif in vivo. A higher frequency of this motif at embryonic and fetal Cdx2 target loci and the specifically methylated state of the CpG during development allows selective Cdx2 binding and activation of developmental enhancers and linked genes. Conversely, demethylation at these enhancers prohibits ectopic Cdx2 binding in adult cells, where Cdx2 binds its canonical motif without a CpG. This differential Cdx2 binding allows for corecruitment of Ctcf and Hnf4, facilitating the establishment of intestinal superenhancers during development and enhancers mediating adult homeostatic functions, respectively. Induced gain of DNA methylation in the adult mouse epithelium or cultured cells causes ectopic recruitment of Cdx2 to the developmental target loci and facilitates cobinding of the partner TFs. Together, our results demonstrate that the differential CpG motif requirements for Cdx2 binding to developmental versus adult target sites allow it to navigate different DNA methylation profiles and activate cell type-specific genes at appropriate times.

Long non-coding RNA (lncRNA) PVT1 in drug resistance of cancers: Focus on pathological mechanisms

According to estimates, cancer will be the leading cause of death globally in 2022, accounting for 9.6 million deaths. At present, the three main therapeutic modalities utilized to treat cancer are radiation therapy, chemotherapy, and surgery. However, during treatment, tumor cells resistant to chemotherapy may arise. Drug resistance remains a major oppose since it often leads to therapeutic failure. Furthermore, the term "acquired drug resistance" describes the situation where tumor cells already display drug resistance before undergoing chemotherapy. However, little is still known about the basic mechanisms underlying chemotherapy-induced drug resistance. The development of new technologies and bioinformatics has led to the discovery of additional genes associated with drug resistance. Long noncoding RNA plasmacytoma variant translocation 1 (PVT1) has been linked to an increased risk of cancer, according to a growing body of research. Apart from biological functions associated with cell division, development, pluripotency, and cell cycle, lncRNA PVT1 contributes significantly to the regulation of various aspects of genome function, such as transcription, splicing, and epigenetics. The article will address the mechanism by which lncRNA PVT1 influences drug resistance in cancer cells.

p300 is an obligate integrator of combinatorial transcription factor inputs

Transcription coactivators are proteins or protein complexes that mediate transcription factor (TF) function. However, they lack DNA-binding capacity, prompting the question of how they engage target loci. Three non-exclusive hypotheses have been posited: coactivators are recruited by complexing with TFs, by binding histones through epigenetic reader domains, or by partitioning into condensates through their extensive intrinsically disordered regions. Using p300 as a prototypical coactivator, we systematically mutated its annotated domains and show by single-molecule tracking in live U2OS cells that coactivator-chromatin binding depends entirely on combinatorial binding of multiple TF-interaction domains. Furthermore, we demonstrate that acetyltransferase activity opposes p300-chromatin association and that the N-terminal TF-interaction domains regulate that activity. Single TF-interaction domains are insufficient for chromatin binding and regulation of catalytic activity, implying a principle that we speculate could broadly apply to eukaryotic gene regulation: a TF must act in coordination with other TFs to recruit coactivator activity.

Hold out the genome: a roadmap to solving the cis-regulatory code

Gene expression is regulated by transcription factors that work together to read cis-regulatory DNA sequences. The 'cis-regulatory code' - how cells interpret DNA sequences to determine when, where and how much genes should be expressed - has proven to be exceedingly complex. Recently, advances in the scale and resolution of functional genomics assays and machine learning have enabled substantial progress towards deciphering this code. However, the cis-regulatory code will probably never be solved if models are trained only on genomic sequences; regions of homology can easily lead to overestimation of predictive performance, and our genome is too short and has insufficient sequence diversity to learn all relevant parameters. Fortunately, randomly synthesized DNA sequences enable testing a far larger sequence space than exists in our genomes, and designed DNA sequences enable targeted queries to maximally improve the models. As the same biochemical principles are used to interpret DNA regardless of its source, models trained on these synthetic data can predict genomic activity, often better than genome-trained models. Here we provide an outlook on the field, and propose a roadmap towards solving the cis-regulatory code by a combination of machine learning and massively parallel assays using synthetic DNA.

Genome-wide DNase I-hypersensitive site assay reveals distinct genomic distributions and functional features of open chromatin in autopolyploid sugarcane

The characterization of cis-regulatory DNA elements (CREs) is essential for deciphering the regulation of gene expression in eukaryotes. Although there have been endeavors to identify CREs in plants, the properties of CREs in polyploid genomes are still largely unknown. Here, we conducted the genome-wide identification of DNase I-hypersensitive sites (DHSs) in leaf and stem tissues of the auto-octoploid species Saccharum officinarum. We revealed that DHSs showed highly similar distributions in the genomes of these two S. officinarum tissues. Notably, we observed that approximately 74% of DHSs were located in distal intergenic regions, suggesting considerable differences in the abundance of distal CREs between S. officinarum and other plants. Leaf- and stem-dependent transcriptional regulatory networks were also developed by mining the binding motifs of transcription factors (TFs) from tissue-specific DHSs. Four TEOSINTE BRANCHED 1, CYCLOIDEA, and PCF1 (TCP) TFs (TCP2, TCP4, TCP7, and TCP14) and two ethylene-responsive factors (ERFs) (ERF109 and ERF03) showed strong causal connections with short binding distances from each other, pointing to their possible roles in the regulatory networks of leaf and stem development. Through functional validation in transiently transgenic protoplasts, we isolate a set of tissue-specific promoters. Overall, the DHS maps presented here offer a global view of the potential transcriptional regulatory elements in polyploid sugarcane and can be expected to serve as a valuable resource for both transcriptional network elucidation and genome editing in sugarcane breeding.

Quantification of absolute transcription factor binding affinities in the native chromatin context using BANC-seq

Transcription factor binding across the genome is regulated by DNA sequence and chromatin features. However, it is not yet possible to quantify the impact of chromatin context on transcription factor binding affinities. Here, we report a method called binding affinities to native chromatin by sequencing (BANC-seq) to determine absolute apparent binding affinities of transcription factors to native DNA across the genome. In BANC-seq, a concentration range of a tagged transcription factor is added to isolated nuclei. Concentration-dependent binding is then measured per sample to quantify apparent binding affinities across the genome. BANC-seq adds a quantitative dimension to transcription factor biology, which enables stratification of genomic targets based on transcription factor concentration and prediction of transcription factor binding sites under non-physiological conditions, such as disease-associated overexpression of (onco)genes. Notably, whereas consensus DNA binding motifs for transcription factors are important to establish high-affinity binding sites, these motifs are not always strictly required to generate nanomolar-affinity interactions in the genome.

MORA and EnsembleTFpredictor: An ensemble approach to reveal functional transcription factor regulatory networks

MOTIVATION

Our study aimed to identify biologically relevant transcription factors (TFs) that control the expression of a set of co-expressed or co-regulated genes.

RESULTS

We developed a fully automated pipeline, Motif Over Representation Analysis (MORA), to detect enrichment of known TF binding motifs in any query sequences. MORA performed better than or comparable to five other TF-prediction tools as evaluated using hundreds of differentially expressed gene sets and ChIP-seq datasets derived from known TFs. Additionally, we developed EnsembleTFpredictor to harness the power of multiple TF-prediction tools to provide a list of functional TFs ranked by prediction confidence. When applied to the test datasets, EnsembleTFpredictor not only identified the target TF but also revealed many TFs known to cooperate with the target TF in the corresponding biological systems. MORA and EnsembleTFpredictor have been used in two publications, demonstrating their power in guiding experimental design and in revealing novel biological insights.

Microbial thermogenesis is dependent on ATP concentrations and the protein kinases ArcB, GlnL, and YccC

Organisms necessarily release heat energy in their pursuit of survival. This process is known as cellular thermogenesis and is implicated in many processes from cancer metabolism to spontaneous farm fires. However, the molecular basis for this fundamental phenomenon is yet to be elucidated. Here, we show that the major players involved in the cellular thermogenesis of Escherichia coli are the protein kinases ArcB, GlnL, and YccC. We also reveal the substrate-level control of adenosine triphosphate (ATP)-driven autophosphorylation that governs cellular thermogenesis. Specifically, through live cell microcalorimetry, we find these regulatory proteins, when knocked out in a model E. coli strain, dysregulate cellular thermogenesis. This dysregulation can be seen in an average 25% or greater increase in heat output by these cells. We also discover that both heat output and intracellular ATP levels are maximal during the late log phase of growth. Additionally, we show that microbial thermogenesis can be engineered through overexpressing glnL. Our results demonstrate a correlation between ATP concentrations in the cell and a cell's ability to generate excess heat. We expect this work to be the foundation for engineering thermogenically tuned organisms for a variety of applications.

Cooperative assembly confers regulatory specificity and long-term genetic circuit stability

A ubiquitous feature of eukaryotic transcriptional regulation is cooperative self-assembly between transcription factors (TFs) and DNA cis-regulatory motifs. It is thought that this strategy enables specific regulatory connections to be formed in gene networks between otherwise weakly interacting, low-specificity molecular components. Here, using synthetic gene circuits constructed in yeast, we find that high regulatory specificity can emerge from cooperative, multivalent interactions among artificial zinc-finger-based TFs. We show that circuits "wired" using the strategy of cooperative TF assembly are effectively insulated from aberrant misregulation of the host cell genome. As we demonstrate in experiments and mathematical models, this mechanism is sufficient to rescue circuit-driven fitness defects, resulting in genetic and functional stability of circuits in long-term continuous culture. Our naturally inspired approach offers a simple, generalizable means for building high-fidelity, evolutionarily robust gene circuits that can be scaled to a wide range of host organisms and applications.

Predicting the impact of sequence motifs on gene regulation using single-cell data

The binding of transcription factors at proximal promoters and distal enhancers is central to gene regulation. Identifying regulatory motifs and quantifying their impact on expression remains challenging. Using a convolutional neural network trained on single-cell data, we infer putative regulatory motifs and cell type-specific importance. Our model, scover, explains 29% of the variance in gene expression in multiple mouse tissues. Applying scover to distal enhancers identified using scATAC-seq from the developing human brain, we identify cell type-specific motif activities in distal enhancers. Scover can identify regulatory motifs and their importance from single-cell data where all parameters and outputs are easily interpretable.

Finding meaning in chaos: a selection signature for functional interactions and its use in molecular biology

A primary goal of biomedical research is to elucidate molecular mechanisms, particularly those responsible for human traits, either normal or pathological. Yet achieving this goal is difficult if not impossible when the traits of interest lack tractable models and so cannot be dissected through time-honoured approaches like forward genetics or reconstitution. Arguably, no biological problem has hindered scientific progress more than this: the inability to dissect a trait's mechanism without a tractable likeness of the trait. At root, forward genetics and reconstitution are powerful approaches because they assay for specific molecular functions. Here, we discuss an alternative way to uncover important mechanistic interactions, namely, to assay for positive natural selection. If an interaction has been selected for, then it must perform an important function, a function that significantly promotes reproductive success. Accordingly, selection is a consequence and indicator of function, and uncovering multimolecular selection will reveal important functional interactions. We propose a selection signature for interactions and review recent selection-based approaches through which to dissect traits that are not inherently tractable. The review includes proof-of-principle studies in which important interactions were uncovered by screening for selection. In sum, screens for selection appear feasible when screens for specific functions are not. Selection screens thus constitute a novel tool through which to reveal the mechanisms that shape the fates of organisms.

Negatively charged, intrinsically disordered regions can accelerate target search by DNA-binding proteins

In eukaryotes, many DNA/RNA-binding proteins possess intrinsically disordered regions (IDRs) with large negative charge, some of which involve a consecutive sequence of aspartate (D) or glutamate (E) residues. We refer to them as D/E repeats. The functional role of D/E repeats is not well understood, though some of them are known to cause autoinhibition through intramolecular electrostatic interaction with functional domains. In this work, we investigated the impacts of D/E repeats on the target DNA search kinetics for the high-mobility group box 1 (HMGB1) protein and the artificial protein constructs of the Antp homeodomain fused with D/E repeats of varied lengths. Our experimental data showed that D/E repeats of particular lengths can accelerate the target association in the overwhelming presence of non-functional high-affinity ligands ('decoys'). Our coarse-grained molecular dynamics (CGMD) simulations showed that the autoinhibited proteins can bind to DNA and transition into the uninhibited complex with DNA through an electrostatically driven induced-fit process. In conjunction with the CGMD simulations, our kinetic model can explain how D/E repeats can accelerate the target association process in the presence of decoys. This study illuminates an unprecedented role of the negatively charged IDRs in the target search process.

Heat shock transcription factors demonstrate a distinct mode of interaction with mitotic chromosomes

A large number of transcription factors have been shown to bind and interact with mitotic chromosomes, which may promote the efficient reactivation of transcriptional programs following cell division. Although the DNA-binding domain (DBD) contributes strongly to TF behavior, the mitotic behaviors of TFs from the same DBD family may vary. To define the mechanisms governing TF behavior during mitosis in mouse embryonic stem cells, we examined two related TFs: Heat Shock Factor 1 and 2 (HSF1 and HSF2). We found that HSF2 maintains site-specific binding genome-wide during mitosis, whereas HSF1 binding is somewhat decreased. Surprisingly, live-cell imaging shows that both factors appear excluded from mitotic chromosomes to the same degree, and are similarly more dynamic in mitosis than in interphase. Exclusion from mitotic DNA is not due to extrinsic factors like nuclear import and export mechanisms. Rather, we found that the HSF DBDs can coat mitotic chromosomes, and that HSF2 DBD is able to establish site-specific binding. These data further confirm that site-specific binding and chromosome coating are independent properties, and that for some TFs, mitotic behavior is largely determined by the non-DBD regions.

p300 Is an Obligate Integrator of Combinatorial Transcription Factor Inputs

Transcription coactivators are proteins or protein complexes that mediate transcription factor (TF) function. However, they lack DNA binding capacity, prompting the question of how they engage target loci. Three non-exclusive hypotheses have been posited: coactivators are recruited by complexing with TFs, by binding histones through epigenetic reader domains, or by partitioning into phase-separated compartments through their extensive intrinsically disordered regions (IDRs). Using p300 as a prototypical coactivator, we systematically mutated its annotated domains and show by single-molecule tracking in live cells that coactivator-chromatin binding depends entirely on combinatorial binding of multiple TF-interaction domains. Furthermore, we demonstrate that acetyltransferase activity negatively impacts p300-chromatin association and that the N-terminal TF-interaction domains regulate that activity. Single TF-interaction domains are insufficient for both chromatin binding and regulation of catalytic activity, implying a principle that could broadly inform eukaryotic gene regulation: a TF must act in coordination with other TFs to recruit coactivator activity.

Transcriptional kinetic synergy: A complex landscape revealed by integrating modeling and synthetic biology

Transcription factors (TFs) control gene expression, often acting synergistically. Classical thermodynamic models offer a biophysical explanation for synergy based on binding cooperativity and regulated recruitment of RNA polymerase. Because transcription requires polymerase to transition through multiple states, recent work suggests that "kinetic synergy" can arise through TFs acting on distinct steps of the transcription cycle. These types of synergy are not mutually exclusive and are difficult to disentangle conceptually and experimentally. Here, we model and build a synthetic circuit in which TFs bind to a single shared site on DNA, such that TFs cannot synergize by simultaneous binding. We model mRNA production as a function of both TF binding and regulation of the transcription cycle, revealing a complex landscape dependent on TF concentration, DNA binding affinity, and regulatory activity. We use synthetic TFs to confirm that the transcription cycle must be integrated with recruitment for a quantitative understanding of gene regulation.

Minimal synthetic enhancers reveal control of the probability of transcriptional engagement and its timing by a morphogen gradient

How enhancers interpret morphogen gradients to generate gene expression patterns is a central question in developmental biology. Recent studies have proposed that enhancers can dictate whether, when, and at what rate promoters engage in transcription, but the complexity of endogenous enhancers calls for theoretical models with too many free parameters to quantitatively dissect these regulatory strategies. To overcome this limitation, we established a minimal promoter-proximal synthetic enhancer in embryos of Drosophila melanogaster. Here, a gradient of the Dorsal activator is read by a single Dorsal DNA binding site. Using live imaging to quantify transcriptional activity, we found that a single binding site can regulate whether promoters engage in transcription in a concentration-dependent manner. By modulating the binding-site affinity, we determined that a gene's decision to transcribe and its transcriptional onset time can be explained by a simple model where the promoter traverses multiple kinetic barriers before transcription can ensue.

Enhancer architecture and chromatin accessibility constrain phenotypic space during Drosophila development

Developmental enhancers bind transcription factors and dictate patterns of gene expression during development. Their molecular evolution can underlie phenotypical evolution, but the contributions of the evolutionary pathways involved remain little understood. Here, using mutation libraries in Drosophila melanogaster embryos, we observed that most point mutations in developmental enhancers led to changes in gene expression levels but rarely resulted in novel expression outside of the native pattern. In contrast, random sequences, often acting as developmental enhancers, drove expression across a range of cell types; random sequences including motifs for transcription factors with pioneer activity acted as enhancers even more frequently. Our findings suggest that the phenotypic landscapes of developmental enhancers are constrained by enhancer architecture and chromatin accessibility. We propose that the evolution of existing enhancers is limited in its capacity to generate novel phenotypes, whereas the activity of de novo elements is a primary source of phenotypic novelty.

Sequence-Specific Structural Features and Solvation Properties of Transcription Factor Binding DNA Motifs: Insights from Molecular Dynamics Simulation

Sequence-specific recognition of transcription factor (TF) binding motifs in the target site of DNA over the vast amount of non-target DNA is of primary importance for the transcriptional regulation of gene expression by the TFs. Binding of TFs to the target site of DNA relies not only on the direct contact formation but also on the structural and conformational features of DNA. Recognition of DNA structural features or shape readout by proteins is an important factor in the context of TF-DNA interaction. Based on the atomistic molecular simulation, here we report the sequence-dependent unique structural features, solvation, and ion-binding properties of biologically relevant AT- and GC-rich human TF binding motifs in DNA. Counterion and water distribution around the motif is found to be sensitive to the motif sequence, which is accompanied with the DNA shape features. The motif sequence affects the electrostatic potential along the grooves, and cytosine methylation alters the DNA shape features. Characteristic solvation properties of TF binding motif DNA fragments infer that an ionic environment and hydration influences are essential to describe TF-DNA interactions.

Molecular basis for lethal cross-talk between two unrelated bacterial transcription factors - the regulatory protein of a restriction-modification system and the repressor of a defective prophage

Bacterial gene expression depends on the efficient functioning of global transcriptional networks, however their interconnectivity and orchestration rely mainly on the action of individual DNA binding proteins called transcription factors (TFs). TFs interact not only with their specific target sites, but also with secondary (off-target) sites, and vary in their promiscuity. It is not clear yet what mechanisms govern the interactions with secondary sites, and how such rewiring affects the overall regulatory network, but this could clearly constrain horizontal gene transfer. Here, we show the molecular mechanism of one such off-target interaction between two unrelated TFs in Escherichia coli: the C regulatory protein of a Type II restriction-modification system, and the RacR repressor of a defective prophage. We reveal that the C protein interferes with RacR repressor expression, resulting in derepression of the toxic YdaT protein. These results also provide novel insights into regulation of the racR-ydaST operon. We mapped the C regulator interaction to a specific off-target site, and also visualized C protein dynamics, revealing intriguing differences in single molecule dynamics in different genetic contexts. Our results demonstrate an apparent example of horizontal gene transfer leading to adventitious TF cross-talk with negative effects on the recipient's viability. More broadly, this study represents an experimentally-accessible model of a regulatory constraint on horizontal gene transfer.

Transcription factors perform a 2-step search of the nucleus

Transcription factors regulate gene expression by binding to regulatory DNA and recruiting regulatory protein complexes. The DNA-binding and protein-binding functions of transcription factors are traditionally described as independent functions performed by modular protein domains. Here, I argue that genome binding can be a 2-part process with both DNA-binding and protein-binding steps, enabling transcription factors to perform a 2-step search of the nucleus to find their appropriate binding sites in a eukaryotic genome. I support this hypothesis with new and old results in the literature, discuss how this hypothesis parsimoniously resolves outstanding problems, and present testable predictions.

Systematic analysis of low-affinity transcription factor binding site clusters in vitro and in vivo establishes their functional relevance

Binding to binding site clusters has yet to be characterized in depth, and the functional relevance of low-affinity clusters remains uncertain. We characterized transcription factor binding to low-affinity clusters in vitro and found that transcription factors can bind concurrently to overlapping sites, challenging the notion of binding exclusivity. Furthermore, small clusters with binding sites an order of magnitude lower in affinity give rise to high mean occupancies at physiologically-relevant transcription factor concentrations. To assess whether the observed in vitro occupancies translate to transcriptional activation in vivo, we tested low-affinity binding site clusters in a synthetic and native gene regulatory network in S. cerevisiae. In both systems, clusters of low-affinity binding sites generated transcriptional output comparable to single or even multiple consensus sites. This systematic characterization demonstrates that clusters of low-affinity binding sites achieve substantial occupancies, and that this occupancy can drive expression in eukaryotic promoters.

Eukaryotic gene regulation at equilibrium, or non?

Models of transcriptional regulation that assume equilibrium binding of transcription factors have been less successful at predicting gene expression from sequence in eukaryotes than in bacteria. This could be due to the non-equilibrium nature of eukaryotic regulation. Unfortunately, the space of possible non-equilibrium mechanisms is vast and predominantly uninteresting. The key question is therefore how this space can be navigated efficiently, to focus on mechanisms and models that are biologically relevant. In this review, we advocate for the normative role of theory-theory that prescribes rather than just describes-in providing such a focus. Theory should expand its remit beyond inferring mechanistic models from data, towards identifying non-equilibrium gene regulatory schemes that may have been evolutionarily selected, despite their energy consumption, because they are precise, reliable, fast, or otherwise outperform regulation at equilibrium. We illustrate our reasoning by toy examples for which we provide simulation code.

Transcription factor-nucleosome dynamics from plasma cfDNA identifies ER-driven states in breast cancer

Genome-wide binding profiles of estrogen receptor (ER) and FOXA1 reflect cancer state in ER+ breast cancer. However, routine profiling of tumor transcription factor (TF) binding is impractical in the clinic. Here, we show that plasma cell-free DNA (cfDNA) contains high-resolution ER and FOXA1 tumor binding profiles for breast cancer. Enrichment of TF footprints in plasma reflects the binding strength of the TF in originating tissue. We defined pure in vivo tumor TF signatures in plasma using ER+ breast cancer xenografts, which can distinguish xenografts with distinct ER states. Furthermore, state-specific ER-binding signatures can partition human breast tumors into groups with significantly different ER expression and mortality. Last, TF footprints in human plasma samples can identify the presence of ER+ breast cancer. Thus, plasma TF footprints enable minimally invasive mapping of the regulatory landscape of breast cancer in humans and open vast possibilities for clinical applications across multiple tumor types.

Generating specificity in genome regulation through transcription factor sensitivity to chromatin

Cell type-specific gene expression relies on transcription factors (TFs) binding DNA sequence motifs embedded in chromatin. Understanding how motifs are accessed in chromatin is crucial to comprehend differential transcriptional responses and the phenotypic impact of sequence variation. Chromatin obstacles to TF binding range from DNA methylation to restriction of DNA access by nucleosomes depending on their position, composition and modification. In vivo and in vitro approaches now enable the study of TF binding in chromatin at unprecedented resolution. Emerging insights suggest that TFs vary in their ability to navigate chromatin states. However, it remains challenging to link binding and transcriptional outcomes to molecular characteristics of TFs or the local chromatin substrate. Here, we discuss our current understanding of how TFs access DNA in chromatin and novel techniques and directions towards a better understanding of this critical step in genome regulation.

TF-COMB - discovering grammar of transcription factor binding sites

Cooperativity between transcription factors is important to regulate target gene expression. In particular, the binding grammar of TFs in relation to each other, as well as in the context of other genomic elements, is crucial for TF functionality. However, tools to easily uncover co-occurrence between DNA-binding proteins, and investigate the regulatory modules of TFs, are limited. Here we present TF-COMB (Transcription Factor Co-Occurrence using Market Basket analysis) - a tool to investigate co-occurring TFs and binding grammar within regulatory regions. We found that TF-COMB can accurately identify known co-occurring TFs from ChIP-seq data, as well as uncover preferential localization to other genomic elements. With the use of ATAC-seq footprinting and TF motif locations, we found that TFs exhibit both preferred orientation and distance in relation to each other, and that these are biologically significant. Finally, we extended the analysis to not only investigate individual TF pairs, but also TF pairs in the context of networks, which enabled the investigation of TF complexes and TF hubs. In conclusion, TF-COMB is a flexible tool to investigate various aspects of TF binding grammar.

Modeling binding specificities of transcription factor pairs with random forests

Background

Transcription factors (TFs) bind regulatory DNA regions with sequence specificity, form complexes and regulate gene expression. In cooperative TF-TF binding, two transcription factors bind onto a shared DNA binding site as a pair. Previous work has demonstrated pairwise TF-TF-DNA interactions with position weight matrices (PWMs), which may however not sufficiently take into account the complexity and flexibility of pairwise binding.

Results

We propose two random forest (RF) methods for joint TF-TF binding site prediction: and . We train models with previously published large-scale CAP-SELEX DNA libraries, which comprise DNA sequences enriched for binding of a selected TF pair. builds a random forest with sub-sequences selected from CAP-SELEX DNA reads with previously proposed pairwise PWM. outperforms (area under receiver operating characteristics curve, AUROC, 0.75) the current state-of-the-art method i.e. orientation and spacing specific pairwise PWMs (AUROC 0.59). Thus, may be utilized to improve prediction accuracy for pre-determined binding preferences. However, pairwise TF binding is currently considered flexible; a pair may bind DNA with different orientations and amounts of dinucleotide gaps or overlap between the two motifs. Thus, we developed , which utilizes random forests by considering simultaneously multiple orientations and spacings of the two factors. Our approach outperforms (AUROC 0.78) PWMs, as well as (p<0.00195). provides an approach for predicting TF-TF binding sites without prior knowledge on pairwise binding preferences. However, more research is needed to assess eligibility for practical applications.

Conclusions

Random forest is well suited for modeling pairwise TF-TF-DNA binding specificities, and provides an improvement to pairwise binding site prediction accuracy.

H3K9 trimethylation in active chromatin restricts the usage of functional CTCF sites in SINE B2 repeats

Here, Gualdrini et al. found that loss of H3K9me3 caused by SETDB1 depletion was associated with increased recruitment of CTCF to >1600 DNA binding motifs contained within SINE B2 repeats, a previously unidentified target of SETDB1-mediated repression. Their findings suggest a role for H3K9me3 in restraining genomic distribution and activity of CTCF, influencing chromatin organization and gene regulation.

Six methyltransferases divide labor in establishing genomic profiles of histone H3 lysine 9 methylation (H3K9me), an epigenomic modification controlling constitutive heterochromatin, gene repression, and silencing of retroelements. Among them, SETDB1 is recruited to active chromatin domains to silence the expression of endogenous retroviruses. In the context of experiments aimed at determining the impact of SETDB1 on stimulus-inducible gene expression in macrophages, we found that loss of H3K9me3 caused by SETDB1 depletion was associated with increased recruitment of CTCF to >1600 DNA binding motifs contained within SINE B2 repeats, a previously unidentified target of SETDB1-mediated repression. CTCF is an essential regulator of chromatin folding that restrains DNA looping by cohesin, thus creating boundaries among adjacent topological domains. Increased CTCF binding to SINE B2 repeats enhanced insulation at hundreds of sites and increased loop formation within topological domains containing lipopolysaccharide-inducible genes, which correlated with their impaired regulation in response to stimulation. These data indicate a role of H3K9me3 in restraining genomic distribution and activity of CTCF, with an impact on chromatin organization and gene regulation.

Cognate DNA Recognition by Engrailed Homeodomain Involves a Conformational Change Controlled via an Electrostatic-Spring-Loaded Latch

Transcription factors must scan genomic DNA, recognize the cognate sequence of their control element(s), and bind tightly to them. The DNA recognition process is primarily carried out by their DNA binding domains (DBD), which interact with the cognate site with high affinity and more weakly with any other DNA sequence. DBDs are generally thought to bind to their cognate DNA without changing conformation (lock-and-key). Here, we used nuclear magnetic resonance and circular dichroism to investigate the interplay between DNA recognition and DBD conformation in the engrailed homeodomain (enHD), as a model case for the homeodomain family of eukaryotic DBDs. We found that the conformational ensemble of enHD is rather flexible and becomes gradually more disordered as ionic strength decreases following a Debye–Hückel’s dependence. Our analysis indicates that enHD’s response to ionic strength is mediated by a built-in electrostatic spring-loaded latch that operates as a conformational transducer. We also found that, at moderate ionic strengths, enHD changes conformation upon binding to cognate DNA. This change is of larger amplitude and somewhat orthogonal to the response to ionic strength. As a consequence, very high ionic strengths (e.g., 700 mM) block the electrostatic-spring-loaded latch and binding to cognate DNA becomes lock-and-key. However, the interplay between enHD conformation and cognate DNA binding is robust across a range of ionic strengths (i.e., 45 to 300 mM) that covers the physiologically-relevant conditions. Therefore, our results demonstrate the presence of a mechanism for the conformational control of cognate DNA recognition on a eukaryotic DBD. This mechanism can function as a signal transducer that locks the DBD in place upon encountering the cognate site during active DNA scanning. The electrostatic-spring-loaded latch of enHD can also enable the fine control of DNA recognition in response to transient changes in local ionic strength induced by variate physiological processes.

Deciphering the mechanism of p73 recognition of p53 response elements using the crystal structure of p73-DNA complexes and computational studies

P73 belongs to p53 family transcription factor activating more than 50% of cell fate p53 target genes involved in cell cycle, apoptosis, DNA damage response alongside neuronal system development and differentiation by binding to 20-bp response elements (REs) having sequence motif (PPPCA/T-T/AGYYY) where P-purines and Y-pyrimidines with each 10-bp separated by minimum 0 to 13-bp spacer. The promiscuous nature of recognizing both cell fate and development genes and the underlying RE selectivity mechanism by p73 is not well understood. Here, we report the molecular details of p73 recognizing the REs using the crystal structure of p73 DNA binding domain (DBD) in complex with 12 base pair DNA sequence 5'-cAGGCATGCCTg-3' and molecular dynamics simulations with six different p53 natural promoter sequences. Each 20-base pair natural promoter forms a different major/minor groove due to the presence of nucleotides A/T, A/C, G/G, T/T and G/T at positions 3, 8, 13, 18 uniquely recognized by p73 key residues Lys138 and Arg268. The loops L1 and L3 bearing these residues influence inter-and intra-dimer interfaces interactions and hence p73 forms a unique tetramer with each natural promoter sequence. Structural features of the DNA and the spacing between half-sites influence p73 tetramerization and its transactivation function.