Flexibility and structure of flanking DNA impact transcription factor affinity for its core motif

Excessive MYC Orchestrates Macrophages induced Chromatin Remodeling to Sustain Micropapillary-Patterned Malignancy in Lung Adenocarcinoma

Current understanding of micropapillary (MP)-subtype lung adenocarcinoma (LUAD) remains confined to biological activities and genomic landscapes. Unraveling the major regulatory programs underlying MP patterned malignancy offers opportunities to identify more feasible therapeutic targets for patients with MP LUAD. This study shows that patients with MP subtype LUAD have aberrant activation of the MYC pathway compared to patients with other subtypes. In vitro and xenograft mouse model studies reveal that MP pattern in malignancy cannot be solely due to aberrant MYC expression but requires the involvement of M2-like macrophages. Excessively expressed MYC leads to the accumulation of M2-like macrophages from the bone marrow, which secretes TGFβ, to induce the expression of FOSL2 in tumor cells, thereby remodeling chromatin accessibility at promoter regions of MP-pattern genes to promote the MYC-mediated de novo transcriptional regulation of these genes. Additionally, the MP-pattern in malignancy can be effectively alleviated by disrupting the TGFβ-FOSL2 axis. These findings reveal new functions for the M2-like macrophage-TGFβ-FOSL2 axis in MYC-overexpressing MP-subtype LUAD, identifying targetable vulnerabilities in this pathway.

P300/RNA polymerase II mediates induction of the teleost viral RNA sensor MDA5 through the interferon regulatory factor IRF11

Melanoma differentiation-associated gene 5 (MDA5) initiates type I interferon (IFN) production by detecting cytosolic viral RNA. Mammalian MDA5 is an IFN-inducible gene and controlled by IFN regulatory factor 1 (IRF1). Teleost MDA5 also induces type I IFN production in response to viruses, yet its regulation remains largely unexplored. This study used the large yellow croaker Larimichthys crocea (Lc) as a model organism and revealed that a type I IFN (LcIFNi) triggers the expression of LcMDA5 through the JAK-STAT signaling pathway, which involves phosphorylation of LcIRF11. LcMDA5 was transcriptionally regulated by LcIRF11. Mechanistically, LcIRF11 interacts with the IFN-stimulated response element within the LcMDA5 promoter, via α3 helix and loop1, and loop2 and loop3 in its DNA binding domain. Overexpression of LcIRF11 recruits p300 and RNA polymerase II (Pol II) to the LcMDA5 promoter region. Pull-down analysis further confirmed the interaction of LcIRF11 with these two proteins. This recruitment was accompanied by increased levels of histone H3K27 acetylation (H3K27ac) and histone H3K4 trimethylation (H3K4me3), both of which are strongly associated with active transcription. Conversely, silencing LcIRF11 reduced p300 and Pol II recruitments and hindered the enrichment of H3K27ac/H3K4me3 modifications at the LcMDA5 promoter. Thus, here we present the first report of IRF11 orchestrating the activation of MDA5 transcription by binding to the IFN-stimulated response element of MDA5 promoter and forming a transcriptional complex with p300 and Pol II. Our results revealed an ancient regulatory mechanism of MDA5 in lower vertebrates, providing insights into its function and evolution.

Protein target search diffusion-association/dissociation free energy landscape around DNA binding site with flanking sequences

In this work we present a minimal structure-based model of protein diffusional search along local DNA amid protein binding and unbinding events on the DNA, taking into account protein-DNA electrostatic interactions and hydrogen-bonding (HB) interactions or contacts at the interface. We accordingly constructed the protein diffusion-association/dissociation free energy surface and mapped it to 1D as the protein slides along DNA, maintaining the protein-DNA interfacial HB contacts that presumably dictate the DNA sequence information detection. Upon DNA helical path correction, the protein 1D diffusion rates along local DNA can be physically derived to be consistent with experimental measurements. We also show that the sequence-dependent protein sliding or stepping patterns along DNA are regulated by collective interfacial HB dynamics, which also determines the ruggedness of the protein diffusion free energy landscape on the local DNA. In comparison, protein association or binding with DNA are generically dictated by the protein-DNA electrostatic interactions, with an interaction zone of nanometers around DNA. Extra degrees of freedom (DOFs) of the protein such as rotations and conformational fluctuations can be well accommodated within the protein-DNA electrostatic interaction zone. As such we demonstrate that the protein binding or association free energy profiling along DNA smoothens over the 1D diffusion free energy landscape, which leads to population variations for an order of magnitude upon a marginal free energetic smoothening around the specific or consensus sites. We further show that the protein unbinding or dissociation from a comparatively high-binding affinity DNA site is dominated by lateral diffusion to the flanking low-affinity sites. The results predict that experimental characterizations on the relative protein-DNA binding affinities or population profiling on the DNA are systematically and physically impacted by the extra DOFs of protein motions aside from 1D translation or helical tracking, as well as from flanking DNA sequences due to protein 1D diffusion and nonspecific binding/unbinding.

Peculiar k-mer Spectra Are Correlated with 3D Contact Frequencies and Breakpoint Regions in the Human Genome

BACKGROUND

It is widely accepted that the 3D chromatin organization in human cell nuclei is not random and recent investigations point towards an interactive relation of epigenetic functioning and chromatin (re-)organization. Although chromatin organization seems to be the result of self-organization of the entirety of all molecules available in the cell nucleus, a general question remains open as to what extent chromatin organization might additionally be predetermined by the DNA sequence and, if so, if there are characteristic differences that distinguish typical regions involved in dysfunction-related aberrations from normal ones, since typical DNA breakpoint regions involved in disease-related chromosome aberrations are not randomly distributed along the DNA sequence.

METHODS

Highly conserved k-mer patterns in intronic and intergenic regions have been reported in eukaryotic genomes. In this article, we search and analyze regions deviating from average spectra (ReDFAS) of k-mer word frequencies in the human genome. This includes all assembled regions, e.g., telomeric, centromeric, genic as well as intergenic regions.

RESULTS

A positive correlation between k-mer spectra and 3D contact frequencies, obtained exemplarily from given Hi-C datasets, has been found indicating a relation of ReDFAS to chromatin organization and interactions. We also searched and found correlations of known functional annotations, e.g., genes correlating with ReDFAS. Selected regions known to contain typical breakpoints on chromosomes 9 and 5 that are involved in cancer-related chromosomal aberrations appear to be enriched in ReDFAS. Since transposable elements like ALUs are often assigned as major players in 3D genome organization, we also studied their impact on our examples but could not find a correlation between ALU regions and breakpoints comparable to ReDFAS.

CONCLUSIONS

Our findings might show that ReDFAS are associated with instable regions of the genome and regions with many chromatin contacts which is in line with current research indicating that chromatin loop anchor points lead to genomic instability.

Utilizing biological experimental data and molecular dynamics for the classification of mutational hotspots through machine learning

Motivation

Benzo[a]pyrene, a notorious DNA-damaging carcinogen, belongs to the family of polycyclic aromatic hydrocarbons commonly found in tobacco smoke. Surprisingly, nucleotide excision repair (NER) machinery exhibits inefficiency in recognizing specific bulky DNA adducts including Benzo[a]pyrene Diol-Epoxide (BPDE), a Benzo[a]pyrene metabolite. While sequence context is emerging as the leading factor linking the inadequate NER response to BPDE adducts, the precise structural attributes governing these disparities remain inadequately understood. We therefore combined the domains of molecular dynamics and machine learning to conduct a comprehensive assessment of helical distortion caused by BPDE-Guanine adducts in multiple gene contexts. Specifically, we implemented a dual approach involving a random forest classification-based analysis and subsequent feature selection to identify precise topological features that may distinguish adduct sites of variable repair capacity. Our models were trained using helical data extracted from duplexes representing both BPDE hotspot and nonhotspot sites within the TP53 gene, then applied to sites within TP53, cII, and lacZ genes.

Results

We show our optimized model consistently achieved exceptional performance, with accuracy, precision, and f1 scores exceeding 91%. Our feature selection approach uncovered that discernible variance in regional base pair rotation played a pivotal role in informing the decisions of our model. Notably, these disparities were highly conserved among TP53 and lacZ duplexes and appeared to be influenced by the regional GC content. As such, our findings suggest that there are indeed conserved topological features distinguishing hotspots and nonhotpot sites, highlighting regional GC content as a potential biomarker for mutation.

Availability and implementation

Code for comparing machine learning classifiers and evaluating their performance is available at https://github.com/jdavies24/ML-Classifier-Comparison, and code for analysing DNA structure with Curves+ and Canal using Random Forest is available at https://github.com/jdavies24/ML-classification-of-DNA-trajectories.

Cooperative Gsx2-DNA binding requires DNA bending and a novel Gsx2 homeodomain interface

The conserved Gsx homeodomain (HD) transcription factors specify neural cell fates in animals from flies to mammals. Like many HD proteins, Gsx factors bind A/T-rich DNA sequences prompting the following question: How do HD factors that bind similar DNA sequences in vitro regulate specific target genes in vivo? Prior studies revealed that Gsx factors bind DNA both as a monomer on individual A/T-rich sites and as a cooperative homodimer to two sites spaced precisely 7 bp apart. However, the mechanistic basis for Gsx-DNA binding and cooperativity is poorly understood. Here, we used biochemical, biophysical, structural and modeling approaches to (i) show that Gsx factors are monomers in solution and require DNA for cooperative complex formation, (ii) define the affinity and thermodynamic binding parameters of Gsx2/DNA interactions, (iii) solve a high-resolution monomer/DNA structure that reveals that Gsx2 induces a 20° bend in DNA, (iv) identify a Gsx2 protein-protein interface required for cooperative DNA binding and (v) determine that flexible spacer DNA sequences enhance Gsx2 cooperativity on dimer sites. Altogether, our results provide a mechanistic basis for understanding the protein and DNA structural determinants that underlie cooperative DNA binding by Gsx factors.

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.

Transient interactions modulate the affinity of NF-κB transcription factors for DNA

The dimeric nuclear factor kappa B (NF-κB) transcription factors (TFs) regulate gene expression by binding to a variety of κB DNA elements with conserved G:C-rich flanking sequences enclosing a degenerate central region. Toward defining mechanistic principles of affinity regulated by degeneracy, we observed an unusual dependence of the affinity of RelA on the identity of the central base pair, which appears to be noncontacted in the complex crystal structures. The affinity of κB sites with A or T at the central position is ~10-fold higher than with G or C. The crystal structures of neither the complexes nor the free κB DNAs could explain the differences in affinity. Interestingly, differential dynamics of several residues were revealed in molecular dynamics simulation studies, where simulation replicates totaling 148 μs were performed on NF-κB:DNA complexes and free κB DNAs. Notably, Arg187 and Arg124 exhibited selectivity in transient interactions that orchestrated a complex interplay among several DNA-interacting residues in the central region. Binding and simulation studies with mutants supported these observations of transient interactions dictating specificity. In combination with published reports, this work provides insights into the nuanced mechanisms governing the discriminatory binding of NF-κB family TFs to κB DNA elements and sheds light on cancer pathogenesis of cRel, a close homolog of RelA.

PTFSpot: deep co-learning on transcription factors and their binding regions attains impeccable universality in plants

Unlike animals, variability in transcription factors (TFs) and their binding regions (TFBRs) across the plants species is a major problem that most of the existing TFBR finding software fail to tackle, rendering them hardly of any use. This limitation has resulted into underdevelopment of plant regulatory research and rampant use of Arabidopsis-like model species, generating misleading results. Here, we report a revolutionary transformers-based deep-learning approach, PTFSpot, which learns from TF structures and their binding regions' co-variability to bring a universal TF-DNA interaction model to detect TFBR with complete freedom from TF and species-specific models' limitations. During a series of extensive benchmarking studies over multiple experimentally validated data, it not only outperformed the existing software by >30% lead but also delivered consistently >90% accuracy even for those species and TF families that were never encountered during the model-building process. PTFSpot makes it possible now to accurately annotate TFBRs across any plant genome even in the total lack of any TF information, completely free from the bottlenecks of species and TF-specific models.

EGPDI: identifying protein-DNA binding sites based on multi-view graph embedding fusion

Mechanisms of protein-DNA interactions are involved in a wide range of biological activities and processes. Accurately identifying binding sites between proteins and DNA is crucial for analyzing genetic material, exploring protein functions, and designing novel drugs. In recent years, several computational methods have been proposed as alternatives to time-consuming and expensive traditional experiments. However, accurately predicting protein-DNA binding sites still remains a challenge. Existing computational methods often rely on handcrafted features and a single-model architecture, leaving room for improvement. We propose a novel computational method, called EGPDI, based on multi-view graph embedding fusion. This approach involves the integration of Equivariant Graph Neural Networks (EGNN) and Graph Convolutional Networks II (GCNII), independently configured to profoundly mine the global and local node embedding representations. An advanced gated multi-head attention mechanism is subsequently employed to capture the attention weights of the dual embedding representations, thereby facilitating the integration of node features. Besides, extra node features from protein language models are introduced to provide more structural information. To our knowledge, this is the first time that multi-view graph embedding fusion has been applied to the task of protein-DNA binding site prediction. The results of five-fold cross-validation and independent testing demonstrate that EGPDI outperforms state-of-the-art methods. Further comparative experiments and case studies also verify the superiority and generalization ability of EGPDI.

MLDSPP: Bacterial Promoter Prediction Tool Using DNA Structural Properties with Machine Learning and Explainable AI

Bacterial promoters play a crucial role in gene expression by serving as docking sites for the transcription initiation machinery. However, accurately identifying promoter regions in bacterial genomes remains a challenge due to their diverse architecture and variations. In this study, we propose MLDSPP (Machine Learning and Duplex Stability based Promoter prediction in Prokaryotes), a machine learning-based promoter prediction tool, to comprehensively screen bacterial promoter regions in 12 diverse genomes. We leveraged biologically relevant and informative DNA structural properties, such as DNA duplex stability and base stacking, and state-of-the-art machine learning (ML) strategies to gain insights into promoter characteristics. We evaluated several machine learning models, including Support Vector Machines, Random Forests, and XGBoost, and assessed their performance using accuracy, precision, recall, specificity, F1 score, and MCC metrics. Our findings reveal that XGBoost outperformed other models and current state-of-the-art promoter prediction tools, namely Sigma70pred and iPromoter2L, achieving F1-scores >95% in most systems. Significantly, the use of one-hot encoding for representing nucleotide sequences complements these structural features, enhancing our XGBoost model's predictive capabilities. To address the challenge of model interpretability, we incorporated explainable AI techniques using Shapley values. This enhancement allows for a better understanding and interpretation of the predictions of our model. In conclusion, our study presents MLDSPP as a novel, generic tool for predicting promoter regions in bacteria, utilizing original downstream sequences as nonpromoter controls. This tool has the potential to significantly advance the field of bacterial genomics and contribute to our understanding of gene regulation in diverse bacterial systems.

Flanking AT base pairs affect the localization of monovalent cations in DNA A-tracts

Capillary electrophoresis has been used to measure the free solution mobilities of a series of 26-base pair (bp) DNA oligomers containing two phased A4T1in-tracts embedded in flanking sequences containing 0 to 11 additional AT bps. A random-sequence 26-bp oligomer with 12 isolated AT bps was used as the reference. Mobility ratios (A-tract/reference) were measured in background electrolytes (BGEs) containing mixtures of small monovalent cations and tetrabutylammonium (TBA+ ) or tetrapropylammonium (TPA+ ) ions. The mobility ratios observed in 0.3 M TBA+ were >1.00, suggesting that the TBA+ ions had formed electrostatic contact pairs with the AT bp in the reference and in the A-tract flanking sequences, decreasing the mobilities of both oligomers. The TBA-AT pairing interactions could be eliminated by increasing the concentration of small monovalent cations in the BGE. In 0.3 M TPA+ , electrostatic contact pairs were formed with the AT bps in the flanking sequences and in the A-tracts. Interestingly, the shapes of the mobility ratio profiles observed for the A4T1in-tract oligomers depended on the total number of A + T residues in the oligomer.

MAE-seq refines regulatory elements across the genome

Proper cell fate determination relies on precise spatial and temporal genome-wide cooperation between regulatory elements (REs) and their targeted genes. However, the lengths of REs defined using different methods vary, which indicates that there is sequence redundancy and that the context of the genome may be unintelligible. We developed a method called MAE-seq (Massive Active Enhancers by Sequencing) to experimentally identify functional REs at a 25-bp scale. In this study, MAE-seq was used to identify 626879, 541617 and 554826 25-bp enhancers in mouse embryonic stem cells (mESCs), C2C12 and HEK 293T, respectively. Using ∼1.6 trillion 25 bp DNA fragments and screening 12 billion cells, we identified 626879 as active enhancers in mESCs as an example. Comparative analysis revealed that most of the histone modification datasets were annotated by MAE-Seq loci. Furthermore, 33.85% (212195) of the identified enhancers were identified as de novo ones with no epigenetic modification. Intriguingly, distinct chromatin states dictate the requirement for dissimilar cofactors in governing novel and known enhancers. Validation results show that these 25-bp sequences could act as a functional unit, which shows identical or similar expression patterns as the previously defined larger elements, Enhanced resolution facilitated the identification of numerous cell-specific enhancers and their accurate annotation as super enhancers. Moreover, we characterized novel elements capable of augmenting gene activity. By integrating with high-resolution Hi-C data, over 55.64% of novel elements may have a distal association with different targeted genes. For example, we found that the Cdh1 gene interacts with one novel and two known REs in mESCs. The biological effects of these interactions were investigated using CRISPR-Cas9, revealing their role in coordinating Cdh1 gene expression and mESC proliferation. Our study presents an experimental approach to refine the REs at 25-bp resolution, advancing the precision of genome annotation and unveiling the underlying genome context. This novel approach not only advances our understanding of gene regulation but also opens avenues for comprehensive exploration of the genomic landscape.

Molecular Characterization and Genome Mechanical Features of Two Newly Isolated Polyvalent Bacteriophages Infecting Pseudomonas syringae pv. garcae

Coffee plants have been targeted by a devastating bacterial disease, a condition known as bacterial blight, caused by the phytopathogen Pseudomonas syringae pv. garcae (Psg). Conventional treatments of coffee plantations affected by the disease involve frequent spraying with copper- and kasugamycin-derived compounds, but they are both highly toxic to the environment and stimulate the appearance of bacterial resistance. Herein, we report the molecular characterization and mechanical features of the genome of two newly isolated (putative polyvalent) lytic phages for Psg. The isolated phages belong to class Caudoviricetes and present a myovirus-like morphotype belonging to the genuses Tequatrovirus (PsgM02F) and Phapecoctavirus (PsgM04F) of the subfamilies Straboviridae (PsgM02F) and Stephanstirmvirinae (PsgM04F), according to recent bacterial viruses' taxonomy, based on their complete genome sequences. The 165,282 bp (PsgM02F) and 151,205 bp (PsgM04F) genomes do not feature any lysogenic-related (integrase) genes and, hence, can safely be assumed to follow a lytic lifestyle. While phage PsgM02F produced a morphogenesis yield of 124 virions per host cell, phage PsgM04F produced only 12 virions per host cell, indicating that they replicate well in Psg with a 50 min latency period. Genome mechanical analyses established a relationship between genome bendability and virion morphogenesis yield within infected host cells.

Probing the role of the protonation state of a minor groove-linker histidine in Exd-Hox-DNA binding

DNA recognition and targeting by transcription factors (TFs) through specific binding are fundamental in biological processes. Furthermore, the histidine protonation state at the TF-DNA binding interface can significantly influence the binding mechanism of TF-DNA complexes. Nevertheless, the role of histidine in TF-DNA complexes remains underexplored. Here, we employed all-atom molecular dynamics simulations using AlphaFold2-modeled complexes based on previously solved co-crystal structures to probe the role of the His-12 residue in the Extradenticle (Exd)-Sex combs reduced (Scr)-DNA complex when binding to Scr and Ultrabithorax (Ubx) target sites. Our results demonstrate that the protonation state of histidine notably affected the DNA minor-groove width profile and binding free energy. Examining flanking sequences of various binding affinities derived from SELEX-seq experiments, we analyzed the relationship between binding affinity and specificity. We uncovered how histidine protonation leads to increased binding affinity but can lower specificity. Our findings provide new mechanistic insights into the role of histidine in modulating TF-DNA binding.

Activity of the pleiotropic drug resistance transcription factors Pdr1p and Pdr3p is modulated by binding site flanking sequences

The transcription factors Pdr1p and Pdr3p regulate pleiotropic drug resistance (PDR) in Saccharomyces cerevisiae via the PDR responsive elements (PDREs) to modulate gene expression. However, the exact mechanisms underlying the differences in their regulons remain unclear. Employing genomic occupancy profiling (CUT&RUN), binding assays, and transcription studies, we characterized the differences in sequence specificity between transcription factors. Findings reveal distinct preferences for core PDRE sequences and the flanking sequences for both proteins. While flanking sequences moderately alter DNA binding affinity, they significantly impact Pdr1/3p transcriptional activity. Notably, both proteins demonstrated the ability to bind half sites, showing potential enhancement of transcription from adjacent PDREs. This insight sheds light on ways Pdr1/3p can differentially regulate PDR.

PAPerFly: Partial Assembly-based Peak Finder for ab initio binding site reconstruction

BACKGROUND

The specific recognition of a DNA locus by a given transcription factor is a widely studied issue. It is generally agreed that the recognition can be influenced not only by the binding motif but by the larger context of the binding site. In this work, we present a novel heuristic algorithm that can reconstruct the unique binding sites captured in a sequencing experiment without using the reference genome.

RESULTS

We present PAPerFly, the Partial Assembly-based Peak Finder, a tool for the binding site and binding context reconstruction from the sequencing data without any prior knowledge. This tool operates without the need to know the reference genome of the respective organism. We employ algorithmic approaches that are used during genome assembly. The proposed algorithm constructs a de Bruijn graph from the sequencing data. Based on this graph, sequences and their enrichment are reconstructed using a novel heuristic algorithm. The reconstructed sequences are aligned and the peaks in the sequence enrichment are identified. Our approach was tested by processing several ChIP-seq experiments available in the ENCODE database and comparing the results of Paperfly and standard methods.

CONCLUSIONS

We show that PAPerFly, an algorithm tailored for experiment analysis without the reference genome, yields better results than an aggregation of ChIP-seq agnostic tools. Our tool is freely available at https://github.com/Caeph/paperfly/ or on Zenodo ( https://doi.org/10.5281/zenodo.7116424 ).

Cooperative Gsx2-DNA Binding Requires DNA Bending and a Novel Gsx2 Homeodomain Interface

The conserved Gsx homeodomain (HD) transcription factors specify neural cell fates in animals from flies to mammals. Like many HD proteins, Gsx factors bind A/T-rich DNA sequences prompting the question - how do HD factors that bind similar DNA sequences in vitro regulate specific target genes in vivo? Prior studies revealed that Gsx factors bind DNA both as a monomer on individual A/T-rich sites and as a cooperative homodimer to two sites spaced precisely seven base pairs apart. However, the mechanistic basis for Gsx DNA binding and cooperativity are poorly understood. Here, we used biochemical, biophysical, structural, and modeling approaches to (1) show that Gsx factors are monomers in solution and require DNA for cooperative complex formation; (2) define the affinity and thermodynamic binding parameters of Gsx2/DNA interactions; (3) solve a high-resolution monomer/DNA structure that reveals Gsx2 induces a 20° bend in DNA; (4) identify a Gsx2 protein-protein interface required for cooperative DNA binding; and (5) determine that flexible spacer DNA sequences enhance Gsx2 cooperativity on dimer sites. Altogether, our results provide a mechanistic basis for understanding the protein and DNA structural determinants that underlie cooperative DNA binding by Gsx factors, thereby providing a deeper understanding of HD specificity.

Predictions of DNA mechanical properties at a genomic scale reveal potentially new functional roles of DNA flexibility

Mechanical properties of DNA have been implied to influence many of its biological functions. Recently, a new high-throughput method, called loop-seq, which allows measuring the intrinsic bendability of DNA fragments, has been developed. Using loop-seq data, we created a deep learning model to explore the biological significance of local DNA flexibility in a range of different species from different kingdoms. Consistently, we observed a characteristic and largely dinucleotide-composition-driven change of local flexibility near transcription start sites. In the presence of a TATA-box, a pronounced peak of high flexibility can be observed. Furthermore, depending on the transcription factor investigated, flanking-sequence-dependent DNA flexibility was identified as a potential factor influencing DNA binding. Compared to randomized genomic sequences, depending on species and taxa, actual genomic sequences were observed both with increased and lowered flexibility. Furthermore, in Arabidopsis thaliana, mutation rates, both de novo and fixed, were found to be associated with relatively rigid sequence regions. Our study presents a range of significant correlations between characteristic DNA mechanical properties and genomic features, the significance of which with regard to detailed molecular relevance awaits further theoretical and experimental exploration.

Nonspecific vs. specific DNA binding free energetics of a transcription factor domain protein

Transcription factor (TF) proteins regulate gene expression by binding to specific sites on the genome. In the facilitated diffusion model, an optimized search process is achieved by the TF alternating between 3D diffusion in the bulk and 1D diffusion along DNA. While undergoing 1D diffusion, the protein can switch from a search mode for fast diffusion along nonspecific DNA to a recognition mode for stable binding to specific DNA. It was recently noticed that, for a small TF domain protein, reorientations on DNA happen between the nonspecific and specific DNA binding. We here conducted all-atom molecular dynamics simulations with steering forces to reveal the protein-DNA binding free energetics, confirming that the search and recognition modes are distinguished primarily by protein orientations on the DNA. As the binding free energy difference between the specific and nonspecific DNA system slightly deviates from that being estimated directly from dissociation constants on 15-bp DNA constructs, we hypothesize that the discrepancy can come from DNA sequences flanking the 6-bp central binding sites that impact on the dissociation kinetics measurements. The hypothesis is supported by a simplified spherical protein-DNA model along with stochastic simulations and kinetic modeling.

CRISPR/Cas9 screen for genome-wide interrogation of essential MYC-bound E-boxes in cancer cells

The transcription factor MYC is a proto-oncogene with a well-documented essential role in the pathogenesis and maintenance of several types of cancer. MYC binds to specific E-box sequences in the genome to regulate gene expression in a cell-type- and developmental-stage-specific manner. To date, a combined analysis of essential MYC-bound E-boxes and their downstream target genes important for growth of different types of cancer is missing. In this study, we designed a CRISPR/Cas9 library to destroy E-box sequences in a genome-wide fashion. In parallel, we used the Brunello library to knock out protein-coding genes. We performed high-throughput screens with these libraries in four MYC-dependent cancer cell lines-K562, ST486, HepG2, and MCF7-which revealed several essential E-boxes and genes. Among them, we pinpointed crucial common and cell-type-specific MYC-regulated genes involved in pathways associated with cancer development. Extensive validation of our approach confirmed that E-box disruption affects MYC binding, target-gene expression, and cell proliferation in vitro as well as tumor growth in vivo. Our unique, well-validated tool opens new possibilities to gain novel insights into MYC-dependent vulnerabilities in cancer cells.

Deep flanking sequence engineering for efficient promoter design using DeepSEED

Designing promoters with desirable properties is essential in synthetic biology. Human experts are skilled at identifying strong explicit patterns in small samples, while deep learning models excel at detecting implicit weak patterns in large datasets. Biologists have described the sequence patterns of promoters via transcription factor binding sites (TFBSs). However, the flanking sequences of cis-regulatory elements, have long been overlooked and often arbitrarily decided in promoter design. To address this limitation, we introduce DeepSEED, an AI-aided framework that efficiently designs synthetic promoters by combining expert knowledge with deep learning techniques. DeepSEED has demonstrated success in improving the properties of Escherichia coli constitutive, IPTG-inducible, and mammalian cell doxycycline (Dox)-inducible promoters. Furthermore, our results show that DeepSEED captures the implicit features in flanking sequences, such as k-mer frequencies and DNA shape features, which are crucial for determining promoter properties.

Impact of HMGB1 binding on the structural alterations of platinum drug-treated single dsDNA molecule

High mobility group B1 (HMGB1) is an architectural protein that recognizes the DNA damage sites formed by the platinum anticancer drugs. However, the impact of HMGB1 binding on the structural alterations of the platinum drug-treated single dsDNA molecules has remained largely unknown. Herein, the structural alterations induced by the platinum drugs, the mononuclear cisplatin and it's analog the trinuclear BBR3464, have been probed in presence of HMGB1, by atomic force microscopy (AFM) and AFM-based force spectroscopy. It is observed that the drug-induced DNA loop formation enhanced upon HMGB1 binding, most likely as a result of HMGB1-induced increase in DNA conformational flexibility that allowed the drug-binding sites to come close and form double adducts, thereby resulting in enhanced loop formation via inter-helix cross-linking. Since HMGB1 enhances DNA flexibility, the near-reversible structural transitions as observed in the force-extension curves (for 1 h drug treatment), generally occurred at lower forces in presence of HMGB1. The DNA structural integrity was largely lost after 24 h drug treatment as no reversible transition could be observed. The Young's modulus of the dsDNA molecules, as estimated from the force-extension analysis, increased upon drug treatment, due to formation of the drug-induced covalent cross-links and consequent reduction in DNA flexibility. The Young's modulus increased further in presence of HMGB1 due to HMGB1-induced enhancement in DNA flexibility that could ease formation of the drug-induced covalent cross-links. To our knowledge, this is the first report that shows an increase in the stiffness of the platinum drug-treated DNA molecules in presence of HMGB1.

Unraveling the Half and Full Site Sequence Specificity of the Saccharomyces cerevisiae Pdr1p and Pdr3p Transcription Factors

The transcription factors Pdr1p and Pdr3p regulate pleotropic drug resistance (PDR) in Saccharomyces cerevisiae , via the PDR responsive elements (PDREs) to modulate gene expression. However, the exact mechanisms underlying the differences in their regulons remain unclear. Employing genomic occupancy profiling (CUT&RUN), binding assays, and transcription studies, we characterized the differences in sequence specificity between transcription factors. Findings reveal distinct preferences for core PDRE sequences and the flanking sequences for both proteins. While flanking sequences moderately alter DNA binding affinity, they significantly impact Pdr1/3p transcriptional activity. Notably, both proteins demonstrated the ability to bind half sites, showing potential enhancement of transcription from adjacent PDREs. This insight sheds light on ways Pdr1/3 can differentially regulate PDR.

Prediction of cooperative homeodomain DNA binding sites from high-throughput-SELEX data

Homeodomain proteins constitute one of the largest families of metazoan transcription factors. Genetic studies have demonstrated that homeodomain proteins regulate many developmental processes. Yet, biochemical data reveal that most bind highly similar DNA sequences. Defining how homeodomain proteins achieve DNA binding specificity has therefore been a long-standing goal. Here, we developed a novel computational approach to predict cooperative dimeric binding of homeodomain proteins using High-Throughput (HT) SELEX data. Importantly, we found that 15 of 88 homeodomain factors form cooperative homodimer complexes on DNA sites with precise spacing requirements. Approximately one third of the paired-like homeodomain proteins cooperatively bind palindromic sequences spaced 3 bp apart, whereas other homeodomain proteins cooperatively bind sites with distinct orientation and spacing requirements. Combining structural models of a paired-like factor with our cooperativity predictions identified key amino acid differences that help differentiate between cooperative and non-cooperative factors. Finally, we confirmed predicted cooperative dimer sites in vivo using available genomic data for a subset of factors. These findings demonstrate how HT-SELEX data can be computationally mined to predict cooperativity. In addition, the binding site spacing requirements of select homeodomain proteins provide a mechanism by which seemingly similar AT-rich DNA sequences can preferentially recruit specific homeodomain factors.

DNA structural properties of DNA binding sites for 21 transcription factors in the mycobacterial genome

Mycobacterium tuberculosis, the causative agent of tuberculosis, has evolved over time into a multidrug resistance strain that poses a serious global pandemic health threat. The ability to survive and remain dormant within the host macrophage relies on multiple transcription factors contributing to virulence. To date, very limited structural insights from crystallographic and NMR studies are available for TFs and TF-DNA binding events. Understanding the role of DNA structure in TF binding is critical to deciphering MTB pathogenicity and has yet to be resolved at the genome scale. In this work, we analyzed the compositional and conformational preference of 21 mycobacterial TFs, evident at their DNA binding sites, in local and global scales. Results suggest that most TFs prefer binding to genomic regions characterized by unique DNA structural signatures, namely, high electrostatic potential, narrow minor grooves, high propeller twist, helical twist, intrinsic curvature, and DNA rigidity compared to the flanking sequences. Additionally, preference for specific trinucleotide motifs, with clear periodic signals of tetranucleotide motifs, are observed in the vicinity of the TF-DNA interactions. Altogether, our study reports nuanced DNA shape and structural preferences of 21 TFs.

Zinc cluster transcription factors frequently activate target genes using a non-canonical half-site binding mode

Gene expression changes are orchestrated by transcription factors (TFs), which bind to DNA to regulate gene expression. It remains surprisingly difficult to predict basic features of the transcriptional process, including in vivo TF occupancy. Existing thermodynamic models of TF function are often not concordant with experimental measurements, suggesting undiscovered biology. Here, we analyzed one of the most well-studied TFs, the yeast zinc cluster Gal4, constructed a Shea-Ackers thermodynamic model to describe its binding, and compared the results of this model to experimentally measured Gal4p binding in vivo. We found that at many promoters, the model predicted no Gal4p binding, yet substantial binding was observed. These outlier promoters lacked canonical binding motifs, and subsequent investigation revealed Gal4p binds unexpectedly to DNA sequences with high densities of its half site (CGG). We confirmed this novel mode of binding through multiple experimental and computational paradigms; we also found most other zinc cluster TFs we tested frequently utilize this binding mode, at 27% of their targets on average. Together, these results demonstrate a novel mode of binding where zinc clusters, the largest class of TFs in yeast, bind DNA sequences with high densities of half sites.

Structural basis of DNA binding by the NAC transcription factor ORE1, a master regulator of plant senescence

Plants use sophisticated mechanisms of gene expression to control senescence in response to environmental stress or aging. ORE1 (Arabidopsis thaliana NAC092) is a master regulator of senescence that belongs to the plant-specific NAC transcription factor protein family. ORE1 has been reported to bind to multiple DNA targets to orchestrate leaf senescence, yet the mechanistic basis for recognition of the cognate gene sequence remains unclear. Here, we report the crystal structure of the ORE1-NAC domain alone and its DNA-binding form. The structure of DNA-bound ORE1-NAC revealed the molecular basis for nucleobase recognition and phosphate backbone interactions. We show that local versatility in the DNA-binding site, in combination with domain flexibility of the ORE-NAC homodimer, is crucial for the maintenance of binding to intrinsically flexible DNA. Our results provide a platform for understanding other plant-specific NAC protein-DNA interactions as well as insight into the structural basis of NAC regulators in plants of agronomic and scientific importance.

Moderation of Structural DNA Properties by Coupled Dinucleotide Contents in Eukaryotes

Dinucleotides are known as determinants for various structural and physiochemical properties of DNA and for binding affinities of proteins to DNA. These properties (e.g., stiffness) and bound proteins (e.g., transcription factors) are known to influence important biological functions, such as transcription regulation and 3D chromatin organization. Accordingly, the question arises of how the considerable variations in dinucleotide contents of eukaryotic chromosomes could still provide consistent DNA properties resulting in similar functions and 3D conformations. In this work, we investigate the hypothesis that coupled dinucleotide contents influence DNA properties in opposite directions to moderate each other's influences. Analyzing all 2478 chromosomes of 155 eukaryotic species, considering bias from coding sequences and enhancers, we found sets of correlated and anti-correlated dinucleotide contents. Using computational models, we estimated changes of DNA properties resulting from this coupling. We found that especially pure A/T dinucleotides (AA, TT, AT, TA), known to influence histone positioning and AC/GT contents, are relevant moderators and that, e.g., the Roll property, which is known to influence histone affinity of DNA, is preferably moderated. We conclude that dinucleotide contents might indirectly influence transcription and chromatin 3D conformation, via regulation of histone occupancy and/or other mechanisms.

Deciphering the structural and functional impact of missense mutations in Egr1-DNA interacting interface: an integrative computational approach

Early growth response-1 (Egr1) is a zinc-finger transcription factor that plays a critical role in controlling cell growth, proliferation, differentiation, angiogenesis, and apoptosis. Egr1 is induced by many growth factors, cytokines, and stress signals and is also known to be involved in several pathological conditions like cancer, neurological and ocular disorders. The DNA binding domain of Egr1 is a highly conserved Cys2His2 (C2H2) zinc finger (ZNF) domain which specifically binds to GC-rich consensus sequence GcG (G/T) GGGCG and activates transcription. As the C2H2 domain specifically recognizes its DNA target, the mutations spanning this region shall perturb DNA recognition and may hinder transcription of target genes. Therefore, in this study, the missense mutations occurring specifically at the DNA binding domain (DBD) of Egr1 were probed by computational approaches involving in silico screening of pathogenic and functional mutants coupled with extensive molecular dynamics simulations, to determine the mutants that affect its structural stability and interactions with DNA. From the pathogenicity analysis of 38 missense mutations spanning Egr1-DBD, 17 were predicted as pathogenic, and 7 amongst these were found to have functional impact on Egr1. On combined analysis of molecular dynamics simulation, Residue interaction analysis and Egr1-DNA interaction analysis results, the mutants R371C and R375C showed least impact, whilst, H382R tend to increase the structural stability, whereas R360H, H390R, E393V, and H414Y conferred greater impact by altering the structural stability and DNA interactions. Hence, this study exposes the prospects of considering these 4 deleterious mutations for clinical significance, but needs further experimental validation.HighlightsEgr1's DNA binding domain is a highly conserved Cys2His2 (C2H2) zinc finger domain that specifically recognizes its DNA target.Mutations spanning in the DNA binding domain shall perturb DNA recognition and may hinder transcription.Among the missense mutations, mutants R360H, H390R, E393V, and H414Y were inferred to have a greater impact on Egr1 by altering the structural stability and DNA interactions.

Structural basis of direct and inverted DNA sequence repeat recognition by helix-turn-helix transcription factors

Some transcription factors bind DNA motifs containing direct or inverted sequence repeats. Preference for each of these DNA topologies is dictated by structural constraints. Most prokaryotic regulators form symmetric oligomers, which require operators with a dyad structure. Binding to direct repeats requires breaking the internal symmetry, a property restricted to a few regulators, most of them from the AraC family. The KorA family of transcriptional repressors, involved in plasmid propagation and stability, includes members that form symmetric dimers and recognize inverted repeats. Our structural analyses show that ArdK, a member of this family, can form a symmetric dimer similar to that observed for KorA, yet it binds direct sequence repeats as a non-symmetric dimer. This is possible by the 180° rotation of one of the helix-turn-helix domains. We then probed and confirmed that ArdK shows affinity for an inverted repeat, which, surprisingly, is also recognized by a non-symmetrical dimer. Our results indicate that structural flexibility at different positions in the dimerization interface constrains transcription factors to bind DNA sequences with one of these two alternative DNA topologies.

Flexibility of flanking DNA is a key determinant of transcription factor affinity for the core motif

Selective gene regulation is mediated by recognition of specific DNA sequences by transcription factors (TFs). The extremely challenging task of searching out specific cognate DNA binding sites among several million putative sites within the eukaryotic genome is achieved by complex molecular recognition mechanisms. Elements of this recognition code include the core binding sequence, the flanking sequence context, and the shape and conformational flexibility of the composite binding site. To unravel the extent to which DNA flexibility modulates TF binding, in this study, we employed experimentally guided molecular dynamics simulations of ternary complex of closely related Hox heterodimers Exd-Ubx and Exd-Scr with DNA. Results demonstrate that flexibility signatures embedded in the flanking sequences impact TF binding at the cognate binding site. A DNA sequence has intrinsic shape and flexibility features. While shape features are localized, our analyses reveal that flexibility features of the flanking sequences percolate several basepairs and allosterically modulate TF binding at the core. We also show that lack of flexibility in the motif context can render the cognate site resistant to protein-induced shape changes and subsequently lower TF binding affinity. Overall, this study suggests that flexibility-guided DNA shape, and not merely the static shape, is a key unexplored component of the complex DNA-TF recognition code.

Characterization of sequence determinants of enhancer function using natural genetic variation

Sequence variation in enhancers that control cell-type-specific gene transcription contributes significantly to phenotypic variation within human populations. However, it remains difficult to predict precisely the effect of any given sequence variant on enhancer function due to the complexity of DNA sequence motifs that determine transcription factor (TF) binding to enhancers in their native genomic context. Using F₁-hybrid cells derived from crosses between distantly related inbred strains of mice, we identified thousands of enhancers with allele-specific TF binding and/or activity. We find that genetic variants located within the central region of enhancers are most likely to alter TF binding and enhancer activity. We observe that the AP-1 family of TFs (Fos/Jun) are frequently required for binding of TEAD TFs and for enhancer function. However, many sequence variants outside of core motifs for AP-1 and TEAD also impact enhancer function, including sequences flanking core TF motifs and AP-1 half sites. Taken together, these data represent one of the most comprehensive assessments of allele-specific TF binding and enhancer function to date and reveal how sequence changes at enhancers alter their function across evolutionary timescales.

Structural determinants of DNA recognition by the NO sensor NsrR and related Rrf2-type [FeS]-transcription factors

Several transcription factors of the Rrf2 family use an iron-sulfur cluster to regulate DNA binding through effectors such as nitric oxide (NO), cellular redox status and iron levels. [4Fe-4S]-NsrR from Streptomyces coelicolor (ScNsrR) modulates expression of three different genes via reaction and complex formation with variable amounts of NO, which results in detoxification of this gas. Here, we report the crystal structure of ScNsrR complexed with an hmpA1 gene operator fragment and compare it with those previously reported for [2Fe-2S]-RsrR/rsrR and apo-IscR/hyA complexes. Important structural differences reside in the variation of the DNA minor and major groove widths. In addition, different DNA curvatures and different interactions with the protein sensors are observed. We also report studies of NsrR binding to four hmpA1 variants, which indicate that flexibility in the central region is not a key binding determinant. Our study explores the promotor binding specificities of three closely related transcriptional regulators.

The crystal structure of the iron-sulfur protein NsrR from Streptomyces coelicolor bound to a gene operator fragment is reported and compared with other structures, giving insight into the structural determinants of DNA recognition by the NO sensor.

Pseudomonas-tailed lytic phages: genome mechanical analysis and putative correlation with virion morphogenesis yield

Aim: To unveil a putative correlation between phage genome flexibility and virion morphogenesis yield. Materials & methods: A deeper analysis of the mechanical properties of three Pseudomonas aeruginosa lytic phage genomes was undertaken, together with full genome cyclizability calculations. Results & conclusion: A putative correlation was established among phage genome flexibility, eclipse timeframe and virion particle morphogenesis yield, with a more flexible phage genome leading to a higher burst size and a more rigid phage genome leading to lower burst sizes. The results obtained are highly relevant to understand the influence of the phage genome plasticity on the virion morphogenesis yield inside the infected bacterial host cells and assumes particular relevance in the actual context of bacterial resistance to antibiotics.

New aspects of DNA recognition by group II WRKY transcription factor revealed by structural and functional study of AtWRKY18 DNA binding domain

WRKY transcription factors (TFs) constitute one of the largest families of plant TFs. Based on the organization of domains and motifs, WRKY TFs are divided into three Groups (I-III). The WRKY subgroup IIa includes three representatives in A. thaliana, AtWRKY18, AtWRKY40, and AtWRKY60, that participate in biotic and abiotic stress responses. Here we present crystal structures of the DNA binding domain (DBD) of AtWRKY18 alone and in the complex with a DNA duplex containing the WRKY-recognition sequence, W-box. Subgroup IIa WRKY TFs are known to form homo and heterodimers. Our data suggest that the dimerization interface of the full-length AtWRKY18 involves contacts between the DBD subunits. DNA binding experiments and structural analysis point out novel aspects of DNA recognition by WRKY TFs. In particular, AtWRKY18-DBD preferentially binds an overlapping tandem of W-boxes accompanied by a quasi-W-box motif. The binding of DNA deforms the B-type double helix, which suggests that the DNA fragment must be prone to form a specific structure. This can explain why despite the short W-box consensus, WRKY TFs can precisely control gene expression. Finally, this first experimental structure of a Group II WRKY TF allowed us to compare Group I-III representatives.

Delineation of the DNA Structural Features of Eukaryotic Core Promoter Classes

The eukaryotic transcription is orchestrated from a chunk of the DNA region stated as the core promoter. Multifarious and punctilious core promoter signals, viz., TATA-box, Inr, BREs, and Pause Button, are associated with a subset of genes and regulate their spatiotemporal expression. However, the core promoter architecture linked with these signals has not been investigated exhaustively for several species. In this study, we attempted to envisage the adaptive binding landscape of the transcription initiation machinery as a function of DNA structure. To this end, we deployed a set of k-mer based DNA structural estimates and regular expression models derived from experiments, molecular dynamic simulations, and theoretical frameworks, and high-throughout promoter data sets retrieved from the eukaryotic promoter database. We categorized protein-coding gene core promoters based on characteristic motifs at precise locations and analyzed the B-DNA structural properties and non-B-DNA structural motifs for 15 different eukaryotic genomes. We observed that Inr, BREd, and no-motif classes display common patterns of DNA sequence and structural environment. TATA-containing, BREu, and Pause Button classes show a deviant behavior with the TATA class displaying varied axial and twisting flexibility while BREu and Pause Button leaned toward G-quadruplex motif enrichment. Intriguingly, DNA meltability and shape signals are conserved irrespective of the presence or absence of distinct core promoter motifs in the majority of species. Altogether, here we delineated the conserved DNA structural signals associated with several promoter classes that may contribute to the chromatin configuration, orchestration of transcription machinery, and DNA duplex melting during the transcription process.

Large-scale analysis of Drosophila core promoter function using synthetic promoters

The core promoter plays a central role in setting metazoan gene expression levels, but how exactly it "computes" expression remains poorly understood. To dissect its function, we carried out a comprehensive structure-function analysis in Drosophila. First, we performed a genome-wide bioinformatic analysis, providing an improved picture of the sequence motifs architecture. We then measured synthetic promoters' activities of ~3,000 mutational variants with and without an external stimulus (hormonal activation), at large scale and with high accuracy using robotics and a dual luciferase reporter assay. We observed a strong impact on activity of the different types of mutations, including knockout of individual sequence motifs and motif combinations, variations of motif strength, nucleosome positioning, and flanking sequences. A linear combination of the individual motif features largely accounts for the combinatorial effects on core promoter activity. These findings shed new light on the quantitative assessment of gene expression in metazoans.

Characterization and in vitro testing of newly isolated lytic bacteriophages for the biocontrol of Pseudomonas aeruginosa

Aim: Two lytic phages were isolated using P. aeruginosa DSM19880 as host and fully characterized. Materials & methods: Phages were characterized physicochemically, biologically and genomically. Results & conclusion: Host range analysis revealed that the phages also infect some multidrug-resistant (MDR) P. aeruginosa clinical isolates. Increasing MOI from 1 to 1000 significantly increased phage efficiency and retarded bacteria regrowth, but phage ph0034 (reduction of 7.5 log CFU/ml) was more effective than phage ph0031 (reduction of 5.1 log CFU/ml) after 24 h. Both phages belong to Myoviridae family. Genome sequencing of phages ph0031 and ph0034 showed that they do not carry toxin, virulence, antibiotic resistance and integrase genes. The results obtained are highly relevant in the actual context of bacterial resistance to antibiotics.

Correlation in Domain Fluctuations Navigates Target Search of a Viral Peptide along RNA

Biological macromolecules often exhibit correlations in fluctuations involving distinct domains. This study decodes their functional implications in RNA-protein recognition and target-specific binding. The target search of a peptide along RNA in a viral TAR-Tat complex is closely monitored using atomistic simulations, steered molecular dynamics simulations, free energy calculations, and a machine-learning-based clustering technique. An anticorrelated domain fluctuation is identified between the tetraloop and the bulge region in the apo form of TAR RNA that sets a hierarchy in the domain-specific fluctuations at each binding event and that directs the succeeding binding footsteps. Thus, at each binding footstep, the dynamic partner selects an RNA location for binding where it senses a higher fluctuation, which is conventionally reduced upon binding. This event stimulates an alternate domain fluctuation, which then dictates sequential binding footstep/s and thus the search progresses. Our cross-correlation maps show that the fluctuations relay from one domain to another specific domain until the anticorrelation between those interdomain fluctuations sustains. Artificial attenuation of that hierarchical domain fluctuation inhibits specific RNA binding. The binding is completed with the arrival of a few long-lived water molecules that mediate slightly distant RNA-protein sites and finally stabilize the overall complex. The study underscores the functional importance of naturally designed fluctuating RNA motifs (bulge, tetraloop) and their interplay in dictating the directionality of the search in a highly dynamic environment.

Analysis of nucleoid-associated protein-binding regions reveals DNA structural features influencing genome organization in Mycobacterium tuberculosis

Nucleoid-associated proteins (NAPs) maintain bacterial nucleoid configuration through their architectural properties of DNA bending, wrapping, and bridging. However, the contribution of DNA structural alterations to DNA-NAP recognition at the genomic scale remains unresolved. Present work dissects the DNA sequence, shape and altered structural preferences at a genomic scale for six NAPs in Mycobacterium tuberculosis. Results suggest narrower minor groove width (MGW) and higher DNA rigidity are marked for the binding sites of EspR and Lsr2, while mIHF, MtHU and NapM have heterogeneous DNA structural predilections. In contrast, WhiB4-DNA-binding sites were characterized by wider MGW, highly deformable and less curved DNA. This work provides systematic insight into NAP-mediated genome organization as a function of DNA structural features.

Destruction of DNA-Binding Proteins by Programmable Oligonucleotide PROTAC (O'PROTAC): Effective Targeting of LEF1 and ERG

DNA-binding proteins, including transcription factors (TFs), play essential roles in various cellular processes and pathogenesis of diseases, deeming to be potential therapeutic targets. However, these proteins are generally considered undruggable as they lack an enzymatic catalytic site or a ligand-binding pocket. Proteolysis-targeting chimera (PROTAC) technology has been developed by engineering a bifunctional molecule chimera to bring a protein of interest (POI) to the proximity of an E3 ubiquitin ligase, thus inducing the ubiquitination of POI and further degradation through the proteasome pathway. Here, the development of oligonucleotide-based PROTAC (O'PROTACs), a class of noncanonical PROTACs in which a TF-recognizing double-stranded oligonucleotide is incorporated as a binding moiety of POI is reported. It is demonstrated that O'PROTACs of lymphoid enhancer-binding factor 1 (LEF1) and ETS-related gene (ERG), two highly cancer-related transcription factors, successfully promote degradation of these proteins, impede their transcriptional activity, and inhibit cancer cell growth in vitro and in vivo. The programmable nature of O'PROTACs indicates that this approach is also applicable to destruct other TFs. O'PROTACs not only can serve as a research tool but also can be harnessed as a therapeutic arsenal to target DNA binding proteins for effective treatment of diseases such as cancer.

Sequence-specific dynamics of DNA response elements and their flanking sites regulate the recognition by AP-1 transcription factors

Activator proteins 1 (AP-1) comprise one of the largest families of eukaryotic basic leucine zipper transcription factors. Despite advances in the characterization of AP-1 DNA-binding sites, our ability to predict new binding sites and explain how the proteins achieve different gene expression levels remains limited. Here we address the role of sequence-specific DNA flexibility for stability and specific binding of AP-1 factors, using microsecond-long molecular dynamics simulations. As a model system, we employ yeast AP-1 factor Yap1 binding to three different response elements from two genetic environments. Our data show that Yap1 actively exploits the sequence-specific flexibility of DNA within the response element to form stable protein–DNA complexes. The stability also depends on the four to six flanking nucleotides, adjacent to the response elements. The flanking sequences modulate the conformational adaptability of the response element, making it more shape-efficient to form specific contacts with the protein. Bioinformatics analysis of differential expression of the studied genes supports our conclusions: the stability of Yap1–DNA complexes, modulated by the flanking environment, influences the gene expression levels. Our results provide new insights into mechanisms of protein–DNA recognition and the biological regulation of gene expression levels in eukaryotes.

Symphony of the DNA flexibility and sequence environment orchestrates p53 binding to its responsive elements

The p53 tumor suppressor protein maintains the genome fidelity and integrity by modulating several cellular activities. It regulates these events by interacting with a heterogeneous set of response elements (REs) of regulatory genes in the background of chromatin configuration. At the p53-RE interface, both the base readout and torsional-flexibility of DNA account for high-affinity binding. However, DNA structure is an entanglement of a multitude of physicochemical features, both local and global structure should be considered for dealing with DNA-protein interactions. The goal of current research work is to conceptualize and abstract basic principles of p53-RE binding affinity as a function of structural alterations in DNA such as bending, twisting, and stretching flexibility and shape. For this purpose, we have exploited high throughput in-vitro relative affinity information of responsive elements and genome binding events of p53 from HT-Selex and ChIP-Seq experiments respectively. Our results confirm the role of torsional flexibility in p53 binding, and further, we reveal that DNA axial bending, stretching stiffness, propeller twist, and wedge angles are intimately linked to p53 binding affinity when compared to homeodomain, bZIP, and bHLH proteins. Besides, a similar DNA structural environment is observed in the distal sequences encompassing the actual binding sites of p53 cistrome genes. Additionally, we revealed that p53 cistrome target genes have unique promoter architecture, and the DNA flexibility of genomic sequences around REs in cancer and normal cell types display major differences. Altogether, our work provides a keynote on DNA structural features of REs that shape up the in-vitro and in-vivo high-affinity binding of the p53 transcription factor.

Bayesian Markov models improve the prediction of binding motifs beyond first order

Transcription factors (TFs) regulate gene expression by binding to specific DNA motifs. Accurate models for predicting binding affinities are crucial for quantitatively understanding of transcriptional regulation. Motifs are commonly described by position weight matrices, which assume that each position contributes independently to the binding energy. Models that can learn dependencies between positions, for instance, induced by DNA structure preferences, have yielded markedly improved predictions for most TFs on in vivo data. However, they are more prone to overfit the data and to learn patterns merely correlated with rather than directly involved in TF binding. We present an improved, faster version of our Bayesian Markov model software, BaMMmotif2. We tested it with state-of-the-art motif discovery tools on a large collection of ChIP-seq and HT-SELEX datasets. BaMMmotif2 models of fifth-order achieved a median false-discovery-rate-averaged recall 13.6% and 12.2% higher than the next best tool on 427 ChIP-seq datasets and 164 HT-SELEX datasets, respectively, while being 8 to 1000 times faster. BaMMmotif2 models showed no signs of overtraining in cross-cell line and cross-platform tests, with similar improvements on the next-best tool. These results demonstrate that dependencies beyond first order clearly improve binding models for most TFs.

Immune Regulation in Time and Space: The Role of Local- and Long-Range Genomic Interactions in Regulating Immune Responses

Mammals face and overcome an onslaught of endogenous and exogenous challenges in order to survive. Typical immune cells and barrier cells, such as epithelia, must respond rapidly and effectively to encountered pathogens and aberrant cells to prevent invasion and eliminate pathogenic species before they become overgrown and cause harm. On the other hand, inappropriate initiation and failed termination of immune cell effector function in the absence of pathogens or aberrant tissue gives rise to a number of chronic, auto-immune, and neoplastic diseases. Therefore, the fine control of immune effector functions to provide for a rapid, robust response to challenge is essential. Importantly, immune cells are heterogeneous due to various factors relating to cytokine exposure and cell-cell interaction. For instance, tissue-resident macrophages and T cells are phenotypically, transcriptionally, and functionally distinct from their circulating counterparts. Indeed, even the same cell types in the same environment show distinct transcription patterns at the single cell level due to cellular noise, despite being robust in concert. Additionally, immune cells must remain quiescent in a naive state to avoid autoimmunity or chronic inflammatory states but must respond robustly upon activation regardless of their microenvironment or cellular noise. In recent years, accruing evidence from next-generation sequencing, chromatin capture techniques, and high-resolution imaging has shown that local- and long-range genome architecture plays an important role in coordinating rapid and robust transcriptional responses. Here, we discuss the local- and long-range genome architecture of immune cells and the resultant changes upon pathogen or antigen exposure. Furthermore, we argue that genome structures contribute functionally to rapid and robust responses under noisy and distinct cellular environments and propose a model to explain this phenomenon.

Probabilistic divergence of a template-based modelling methodology from the ideal protocol

Protein structural information is essential for the detailed mapping of a functional protein network. For a higher modelling accuracy and quicker implementation, template-based algorithms have been extensively deployed and redefined. The methods only assess the predicted structure against its native state/template and do not estimate the accuracy for each modelling step. A divergence measure is therefore postulated to estimate the modelling accuracy against its theoretical optimal benchmark. By freezing the domain boundaries, the divergence measures are predicted for the most crucial steps of a modelling algorithm. To precisely refine the score using weighting constants, big data analysis could further be deployed.

Allosteric Response of DNA Recognition Helices of Catabolite Activator Protein to cAMP and DNA Binding

The homodimeric catabolite activator protein (CAP) regulates the transcription of several bacterial genes based on the cellular concentration of cyclic adenosine monophosphate (cAMP). The binding of cAMP to CAP triggers allosteric communication between the cAMP binding domains (CBD) and DNA binding domains (DBD) of CAP, which entails repositioning of DNA recognition helices (F-helices) in the DBD to dock favorably to the target DNA. Despite considerable progress, much remains to be understood about the mechanistic details of DNA recognition by CAP and about the map of allosteric pathways involved in CAP-mediated gene transcription. The present study uses molecular dynamics and umbrella sampling simulations to investigate the mechanism of cAMP- and DNA-induced changes in the conformation and energetics of F-helices observed during the allosteric regulation of CAP by cAMP and the subsequent binding to the DNA promoter region. Using novel collective variables, the free energy profiles associated with the orientation and dynamics of F-helices in the unliganded, cAMP-bound, and cAMP-DNA-bound states of CAP are calculated and compared. The binding-induced alterations in the resultant free energy profiles reveal important flexibility constraints imposed on DBD upon cAMP and DNA binding. A comprehensive analysis of residue-wise interaction maps reveals potential allosteric pathways between CBD and DBD that facilitate the allosteric transduction of regulatory signals in CAP. The revelation that the predicted allosteric pathways crisscross the intersubunit interface offers important clues on the microscopic origin of the intersubunit cooperativity and dimer stability of CAP.