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Functional divergence of transcription factors (TFs) has driven cellular and organismal complexity throughout evolution, but its mechanistic drivers remain poorly understood. Here we test for new mechanisms using CORONA (CNA) and PHABULOSA (PHB), two functionally diverged paralogs in the CLASS III HOMEODOMAIN LEUCINE ZIPPER (HD-ZIPIII) family of TFs. We show that virtually all genes bound by PHB ( ~ 99%) are also bound by CNA, ruling out occupation of distinct sets of genes as a mechanism of functional divergence. Further, genes bound and regulated by both paralogs are almost always regulated in the same direction, ruling out opposite regulation of shared targets as a mechanistic driver. Functional divergence of CNA and PHB instead results from differential usage of shared binding sites, with hundreds of uniquely regulated genes emerging from a commonly bound genetic network. Regulation of a given gene by CNA or PHB is thus a function of whether a bound site is considered 'responsive' versus 'non-responsive' by each paralog. Discrimination between responsive and non-responsive sites is controlled, at least in part, by their lipid binding START domain. This suggests a model in which HD-ZIPIII TFs use information integrated by their START domain to generate paralog-specific transcriptional outcomes from a shared network architecture. Taken together, our study identifies a mechanism of HD-ZIPIII TF paralog divergence and proposes the ubiquitously distributed START evolutionary module as a driver of functional divergence., Competing Interests: Competing interests The authors declare no competing interests., (© 2024. The Author(s).)

ATAC-seq has emerged as a rich epigenome profiling technique, and is commonly used to identify Transcription Factors (TFs) underlying given phenomena. A number of methods can be used to identify differentially-active TFs through the accessibility of their DNA-binding motif, however little is known on the best approaches for doing so. Here we benchmark several such methods using a combination of curated datasets with various forms of short-term perturbations on known TFs, as well as semi-simulations. We include both methods specifically designed for this type of data as well as some that can be repurposed for it. We also investigate variations to these methods, and identify three particularly promising approaches (a chromVAR-limma workflow with critical adjustments, monaLisa and a combination of GC smooth quantile normalization and multivariate modeling). We further investigate the specific use of nucleosome-free fragments, the combination of top methods, and the impact of technical variation. Finally, we illustrate the use of the top methods on a novel dataset to characterize the impact on DNA accessibility of TRAnscription Factor TArgeting Chimeras (TRAFTAC), which can deplete TFs-in our case NFkB-at the protein level., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Gerbaldo et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Dipicolinic acid is an essential component of bacterial spores for stress resistance, which is released into the environment after spore germination. In a previous study, a dip gene cluster was found to be responsible for the catabolism of dipicolinic acid in Alcaligenes faecalis JQ135. However, the transcriptional regulatory mechanism remains unclear. The present study characterized the new GntR/FadR family transcriptional factor DipR, showing that the dip cluster is transcribed as the six transcriptional units, dipR, dipA, dipBC, dipDEFG, dipH and dipJKLM. The purified DipR protein has six binding sites sharing the 6-bp conserved motif sequence 5'-GWATAC-3'. Site-directed mutations indicated that these motif sequences are essential for DipR binding. Moreover, the four key amino acid residues R63, R67, H196 and H218 of DipR, examined by site-directed mutagenesis, played crucial roles in DipR regulation. Bioinformatics analysis showed that dip clusters including dipR genes are widely distributed in bacteria, are taxon-related, and co-evolved with their hosts. This paper provides new insights into the transcriptional regulatory mechanism of dipicolinic acid degradation by DipR in bacteria., (© The Author(s) 2024. Published by Oxford University Press on behalf of Nucleic Acids Research.)

Promoters play a crucial role in regulating gene transcription. However, our understanding of how genetic variants influence alternative promoter selection is still incomplete. In this study, we implement a framework to identify genetic variants that affect the relative usage of alternative promoters, known as promoter usage quantitative trait loci (puQTLs). By constructing an atlas of human puQTLs across 49 different tissues from 838 individuals, we have identified approximately 76,856 independent loci associated with promoter usage, encompassing 602,009 genetic variants. Our study demonstrates that puQTLs represent a distinct type of molecular quantitative trait loci, effectively uncovering regulatory targets and patterns. Furthermore, puQTLs are regulating in a tissue-specific manner and are enriched with binding sites of epigenetic marks and transcription factors, especially those involved in chromatin architecture formation. Notably, we have also found that puQTLs colocalize with complex traits or diseases and contribute to their heritability. Collectively, our findings underscore the significant role of puQTLs in elucidating the molecular mechanisms underlying tissue development and complex diseases., (© 2024. The Author(s).)

Many enhancers control gene expression by assembling regulatory factor clusters, also referred to as condensates. This process is vital for facilitating enhancer communication and establishing cellular identity. However, how DNA sequence and transcription factor (TF) binding instruct the formation of high regulatory factor environments remains poorly understood. Here we developed a new approach leveraging enhancer-centric chromatin accessibility quantitative trait loci (caQTLs) to nominate regulatory factor clusters genome-wide. By analyzing TF-binding signatures within the context of caQTLs and comparing episomal versus endogenous enhancer activities, we discovered a class of regulators, 'context-only' TFs, that amplify the activity of cell type-specific caQTL-binding TFs, that is, 'context-initiator' TFs. Similar to super-enhancers, enhancers enriched for context-only TF-binding sites display high coactivator binding and sensitivity to bromodomain-inhibiting molecules. We further show that binding sites for context-only and context-initiator TFs underlie enhancer coordination, providing a mechanistic rationale for how a loose TF syntax confers regulatory specificity., (© 2024. The Author(s).)

Phospholamban (PLN) is a 52 amino acid regulin that allosterically modulates the activity of the sarco(endo)plasmic reticulum Ca 2+ -ATPase (SERCA) in the heart muscle. In its unphosphorylated form, PLN binds SERCA within its transmembrane (TM) domains, approximately 20 Å away from the Ca 2+ binding site, reducing SERCA's apparent Ca 2+ affinity (pK Ca ) and decreasing cardiac contractility. During the enzymatic cycle, the inhibitory TM domain of PLN remains anchored to SERCA, whereas its cytoplasmic region transiently binds the ATPase's headpiece. Phosphorylation of PLN at Ser16 by protein kinase A increases the affinity of its cytoplasmic domain to SERCA, weakening the TM interactions with the ATPase, reversing its inhibitory function, and augmenting muscle contractility. How the structural changes caused by pathological mutations in the PLN cytoplasmic region are transmitted to its inhibitory TM domain is still unclear. Using solid-state NMR spectroscopy and activity assays, we analyzed the structural and functional effects of a series of mutations and their phosphorylated forms located in the PLN cytoplasmic region and linked to dilated cardiomyopathy. We found that these missense mutations affect the overall topology and dynamics of PLN and ultimately modulate its inhibitory potency. Also, the changes in the TM tilt angle and cytoplasmic dynamics of PLN caused by these mutations correlate well with the extent of SERCA inhibition. Our study unveils new molecular determinants for designing variants of PLN that outcompete endogenous PLN to regulate SERCA in a tunable manner., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial funding, personal interests or relationships that may appear to influence the work reported in this article., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Tandem repeat proteins (TRPs) are widely distributed and bind to a wide variety of ligands. DNA-binding TRPs such as zinc finger (ZNF) and transcription activator-like effector (TALE) play important roles in biology and biotechnology. In this study, we first conducted an extensive analysis of TRPs in public databases, and found that the enormous diversity of TRPs is largely unexplored. We then focused our efforts on identifying novel TRPs possessing DNA-binding capabilities. We established a protein language model for DNA-binding protein prediction (PLM-DBPPred), and predicted a large number of DNA-binding TRPs. A subset was then selected for experimental screening, leading to the identification of 11 novel DNA-binding TRPs, with six showing sequence specificity. Notably, members of the STAR (Short TALE-like Repeat proteins) family can be programmed to target specific 9 bp DNA sequences with high affinity. Leveraging this property, we generated artificial transcription factors using reprogrammed STAR proteins and achieved targeted activation of endogenous gene sets. Furthermore, the members of novel families such as MOON (Marine Organism-Originated DNA binding protein) and pTERF (prokaryotic mTERF-like protein) exhibit unique features and distinct DNA-binding characteristics, revealing interesting biological clues. Our study expands the diversity of DNA-binding TRPs, and demonstrates that a systematic approach greatly enhances the discovery of new biological insights and tools., (© The Author(s) 2024. Published by Oxford University Press on behalf of Nucleic Acids Research.)

While the elements encoding enhancers and promoters have been relatively well studied, the full spectrum of insulator elements which bind the CCCTC binding factor (CTCF), is relatively poorly characterized. This is partly due to the genomic context of CTCF sites greatly influencing their roles and activity. Here we have developed an experimental system to determine the ability of minimal, consistently sized, individual CTCF elements to interpose between enhancers and promoters and thereby reduce gene expression during differentiation. Importantly, each element is tested in the identical location thereby minimising the effect of genomic context. We found no correlation between the ability of CTCF elements to block enhancer-promoter activity with the degree of evolutionary conservation; their resemblance to the consensus core sequences; or the number of CTCF core motifs harboured in the element. Nevertheless, we have shown that the strongest enhancer-promoter blockers include a previously described bound element lying upstream of the CTCF core motif. In addition, we found other uncharacterised DNaseI footprints located close to the core motif that may affect function. We have developed an assay of CTCF sequences which will enable researchers to sub-classify individual CTCF elements in a uniform and unbiased way., (© The Author(s) 2024. Published by Oxford University Press on behalf of Nucleic Acids Research.)

Cross-species prediction of TF binding remains a major challenge due to the rapid evolutionary turnover of individual TF binding sites, resulting in cross-species predictive performance being consistently worse than within-species performance. In this study, a novel Nucleotide-Level Deep Neural Network (NLDNN) is first proposed to predict TF binding within or across species. NLDNN regards the task of TF binding prediction as a nucleotide-level regression task, which takes DNA sequences as input and directly predicts experimental coverage values. Beyond predictive performance, it also assesses model performance by locating potential TF binding regions, discriminating TF-specific single-nucleotide polymorphisms (SNPs), and identifying causal disease-associated SNPs. The experimental results show that NLDNN outperforms the competing methods in these tasks. Then, a dual-path framework is designed for adversarial training of NLDNN to further improve the cross-species prediction performance by pulling the domain space of human and mouse species closer. Through comparison and analysis, it finds that adversarial training not only can improve the cross-species prediction performance between humans and mice but also enhance the ability to locate TF binding regions and discriminate TF-specific SNPs. By visualizing the predictions, it is figured out that the framework corrects some mispredictions by amplifying the coverage values of incorrectly predicted peaks., (© 2024 The Author(s). Advanced Science published by Wiley‐VCH GmbH.)

Transposable elements (TEs) comprise ~50% of our genome, but knowledge of how TEs affect genome evolution remains incomplete. Leveraging ENCODE4 data, we provide the most comprehensive study to date of TE contributions to the regulatory genome. We find 236,181 (~25%) human candidate cis-regulatory elements (cCREs) are TE-derived, with over 90% lineage-specific since the human-mouse split, accounting for 8-36% of lineage-specific cCREs. Except for SINEs, cCRE-associated transcription factor (TF) motifs in TEs are derived from ancestral TE sequence more than expected by chance. We show that TEs may adopt similar regulatory activities of elements near their integration site. Since human-mouse divergence, TEs have contributed 3-56% of TF binding site turnover events across 30 examined TFs. Finally, TE-derived cCREs are similar to non-TE cCREs in terms of MPRA activity and GWAS variant enrichment. Overall, our results substantiate the notion that TEs have played an important role in shaping the human regulatory genome., (© 2024. The Author(s).)

Correct termination of transcription is essential for gene expression. In bacteria, factor-dependent termination relies on the Rho factor, that classically has three conserved domains. Some bacteria also have a functional insertion region. However, the variation in Rho structure among bacteria has not been analyzed in detail. This study determines the distribution, sequence conservation, and predicted features of Rho factors with diverse domain architectures by analyzing 2730 bacterial genomes. About half (49.8%) of the species analyzed have the typical Escherichia coli like Rho while most of the other species (39.8%) have diverse, atypical forms of Rho. Besides conservation of the main domains, we describe a duplicated RNA-binding domain present in specific species and novel variations in the bicyclomycin binding pocket. The additional regions observed in Rho proteins exhibit remarkable diversity. Commonly, however, they have exceptional amino acid compositions and are predicted to be intrinsically disordered, to undergo phase separation, or have prion-like behavior. Phase separation has recently been shown to play roles in Rho function and bacterial fitness during harsh conditions in one species and this study suggests a more widespread role. In conclusion, diverse atypical Rho factors are broadly distributed among bacteria, suggesting additional cellular roles., (© The Author(s) 2024. Published by Oxford University Press on behalf of Nucleic Acids Research.)

Circular RNAs (circRNAs) play vital roles in transcription and translation. Identification of circRNA-RBP (RNA-binding protein) interaction sites has become a fundamental step in molecular and cell biology. Deep learning (DL)-based methods have been proposed to predict circRNA-RBP interaction sites and achieved impressive identification performance. However, those methods cannot effectively capture long-distance dependencies, and cannot effectively utilize the interaction information of multiple features. To overcome those limitations, we propose a DL-based model iCRBP-LKHA using deep hybrid networks for identifying circRNA-RBP interaction sites. iCRBP-LKHA adopts five encoding schemes. Meanwhile, the neural network architecture, which consists of large kernel convolutional neural network (LKCNN), convolutional block attention module with one-dimensional convolution (CBAM-1D) and bidirectional gating recurrent unit (BiGRU), can explore local information, global context information and multiple features interaction information automatically. To verify the effectiveness of iCRBP-LKHA, we compared its performance with shallow learning algorithms on 37 circRNAs datasets and 37 circRNAs stringent datasets. And we compared its performance with state-of-the-art DL-based methods on 37 circRNAs datasets, 37 circRNAs stringent datasets and 31 linear RNAs datasets. The experimental results not only show that iCRBP-LKHA outperforms other competing methods, but also demonstrate the potential of this model in identifying other RNA-RBP interaction sites., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Yuan et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

CCCTC-binding factor (CTCF) is an insulator protein that binds to a highly conserved DNA motif and facilitates regulation of three-dimensional (3D) nuclear architecture and transcription. CTCF binding sites (CTCF-BSs) reside in non-coding DNA and are frequently mutated in cancer. Our previous study identified a small subclass of CTCF-BSs that are resistant to CTCF knock down, termed persistent CTCF binding sites (P-CTCF-BSs). P-CTCF-BSs show high binding conservation and potentially regulate cell-type constitutive 3D chromatin architecture. Here, using ICGC sequencing data we made the striking observation that P-CTCF-BSs display a highly elevated mutation rate in breast and prostate cancer when compared to all CTCF-BSs. To address whether P-CTCF-BS mutations are also enriched in other cell-types, we developed CTCF-INSITE-a tool utilising machine learning to predict persistence based on genetic and epigenetic features of experimentally-determined P-CTCF-BSs. Notably, predicted P-CTCF-BSs also show a significantly elevated mutational burden in all 12 cancer-types tested. Enrichment was even stronger for P-CTCF-BS mutations with predicted functional impact to CTCF binding and chromatin looping. Using in vitro binding assays we validated that P-CTCF-BS cancer mutations, predicted to be disruptive, indeed reduced CTCF binding. Together this study reveals a new subclass of cancer specific CTCF-BS DNA mutations and provides insights into their importance in genome organization in a pan-cancer setting., (© The Author(s) 2024. Published by Oxford University Press on behalf of Nucleic Acids Research.)

Gene regulatory elements drive complex biological phenomena and their mutations are associated with common human diseases. The impacts of human regulatory variants are often tested using model organisms such as mice. However, mapping human enhancers to conserved elements in mice remains a challenge, due to both rapid enhancer evolution and limitations of current computational methods. We analyze distal enhancers across 45 matched human/mouse cell/tissue pairs from a comprehensive dataset of DNase-seq experiments, and show that while cell-specific regulatory vocabulary is conserved, enhancers evolve more rapidly than promoters and CTCF binding sites. Enhancer conservation rates vary across cell types, in part explainable by tissue specific transposable element activity. We present an improved genome alignment algorithm using gapped-kmer features, called gkm-align, and make genome wide predictions for 1,401,803 orthologous regulatory elements. We show that gkm-align discovers 23,660 novel human/mouse conserved enhancers missed by previous algorithms, with strong evidence of conserved functional activity., (© 2024. The Author(s).)

Dense arrangements of binding sites within nucleotide sequences can collectively influence downstream transcription rates or initiate biomolecular interactions. For example, natural promoter regions can harbor many overlapping transcription factor binding sites that influence the rate of transcription initiation. Despite the prevalence of overlapping binding sites in nature, rapid design of nucleotide sequences with many overlapping sites remains a challenge. Here, we show that this is an NP-hard problem, coined here as the nucleotide String Packing Problem (SPP). We then introduce a computational technique that efficiently assembles sets of DNA-protein binding sites into dense, contiguous stretches of double-stranded DNA. For the efficient design of nucleotide sequences spanning hundreds of base pairs, we reduce the SPP to an Orienteering Problem with integer distances, and then leverage modern integer linear programming solvers. Our method optimally packs sets of 20-100 binding sites into dense nucleotide arrays of 50-300 base pairs in 0.05-10 seconds. Unlike approximation algorithms or meta-heuristics, our approach finds provably optimal solutions. We demonstrate how our method can generate large sets of diverse sequences suitable for library generation, where the frequency of binding site usage across the returned sequences can be controlled by modulating the objective function. As an example, we then show how adding additional constraints, like the inclusion of sequence elements with fixed positions, allows for the design of bacterial promoters. The nucleotide string packing approach we present can accelerate the design of sequences with complex DNA-protein interactions. When used in combination with synthesis and high-throughput screening, this design strategy could help interrogate how complex binding site arrangements impact either gene expression or biomolecular mechanisms in varied cellular contexts., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Andreani et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Mutations in the tyrosine phosphatase Src homology-2 domain-containing protein tyrosine phosphatase-2 (SHP2) are associated with a variety of human diseases. Most mutations in SHP2 increase its basal catalytic activity by disrupting autoinhibitory interactions between its phosphatase domain and N-terminal SH2 (phosphotyrosine recognition) domain. By contrast, some disease-associated mutations located in the ligand-binding pockets of the N- or C-terminal SH2 domains do not increase basal activity and likely exert their pathogenicity through alternative mechanisms. We lack a molecular understanding of how these SH2 mutations impact SHP2 structure, activity, and signaling. Here, we characterize five SHP2 SH2 domain ligand-binding pocket mutants through a combination of high-throughput biochemical screens, biophysical and biochemical measurements, and molecular dynamics simulations. We show that while some of these mutations alter binding affinity to phosphorylation sites, the T42A mutation in the N-SH2 domain is unique in that it also substantially alters ligand-binding specificity, despite being 8 to 10 Å from the specificity-determining region of the SH2 domain. This mutation exerts its effect on sequence specificity by remodeling the phosphotyrosine-binding pocket, altering the mode of engagement of both the phosphotyrosine and surrounding residues on the ligand. The functional consequence of this altered specificity is that the T42A mutant has biased sensitivity toward a subset of activating ligands and enhances downstream signaling. Our study highlights an example of a nuanced mechanism of action for a disease-associated mutation, characterized by a change in protein-protein interaction specificity that alters enzyme activation., Competing Interests: Competing interests statement:The authors declare no competing interest.

The substrate-binding domain 2 (SBD2) is an important part of the bacterial glutamine (GLN) transporter and mediates binding and delivery of GLN to the transporter translocation subunit. The SBD2 consists of two domains, D1 and D2, that bind GLN in the space between domains in a closed structure. In the absence of ligand, the SBD2 adopts an open conformation with larger space between domains. The GLN binding and closing are essential for the subsequent transport into the cell. Arginine (ARG) can also bind to SBD2 but does not induce closing and inhibits GLN transport. We use atomistic molecular dynamics (MD) simulations in explicit solvent to study ARG binding in the presence of the open SBD2 structure and observed reversible binding to the native GLN binding site with similar contacts but no transition to a closed SBD2 state. Absolute binding free energy simulations predict a considerable binding affinity of ARG and GLN to the binding site on the D1 domain. Free energy simulations to induce subsequent closing revealed a strong free energy penalty in case of ARG binding in contrast to GLN binding that favors the closed SBD2 state but still retains a free energy barrier for closing. The simulations allowed the identification of the molecular origin of the closing penalty in case of bound ARG and suggested a mutation of lysine at position 373 to alanine that strongly reduced the penalty and allowed closing even in the presence of bound ARG. The study offers an explanation of the molecular mechanism of how ARG competitively inhibits GLN from binding to SBD2 and from triggering the transition to a closed conformation. The proposed Lys373Ala mutation shows promise as a potential tool to validate whether a conformational mismatch between open SBD2 and the translocator is responsible for preventing ARG uptake to the cell., (© 2024 The Author(s). Protein Science published by Wiley Periodicals LLC on behalf of The Protein Society.)

Gene regulatory elements, such as enhancers, greatly influence cell identity by tuning the transcriptional activity of specific cell types. Dynamics of enhancer landscape during early human Th17 cell differentiation remains incompletely understood. Leveraging ATAC-seq-based profiling of chromatin accessibility and comprehensive analysis of key histone marks, we identified a repertoire of enhancers that potentially exert control over the fate specification of Th17 cells. We found 23 SNPs associated with autoimmune diseases within Th17-enhancers that precisely overlapped with the binding sites of transcription factors actively engaged in T-cell functions. Among the Th17-specific enhancers, we identified an enhancer in the intron of RORA and demonstrated that this enhancer positively regulates RORA transcription. Moreover, CRISPR-Cas9-mediated deletion of a transcription factor binding site-rich region within the identified RORA enhancer confirmed its role in regulating RORA transcription. These findings provide insights into the potential mechanism by which the RORA enhancer orchestrates Th17 differentiation., Competing Interests: Declaration of competing interest Alexander Marson is a co-founder of Arsenal Biosciences, Spotlight Therapeutics, and Survey Genomics, serves on the boards of directors at Spotlight Therapeutics and Survey Genomics, is a board observer (and former member of the board of directors) at Arsenal Biosciences, is a member of the scientific advisory boards of Arsenal Biosciences, Spotlight Therapeutics, Survey Genomics, NewLimit, Amgen, Tenaya, and Lightcast, owns stock in Arsenal Biosciences, Spotlight Therapeutics, NewLimit, Survey Genomics, PACT Pharma, Tenaya, and Lightcast, and has received fees from Arsenal Biosciences, Spotlight Therapeutics, NewLimit, 23andMe, PACT Pharma, Juno Therapeutics, Tenaya, Lightcast, Trizell, Vertex, Merck, Amgen, Genentech, AlphaSights, Rupert Case Management, Bernstein, and ALDA. A.M. is an investor in and informal advisor to Offline Ventures and a client of EPIQ. The Marson laboratory has received research support from Juno Therapeutics, Epinomics, Sanofi, GlaxoSmithKline, Gilead, and Anthem. All other authors declare no competing interests. The ChIP-seq and ATAC-seq raw and processed data has been submitted to GEO and can be accessed with the following super-series accession number: GSE243064., (Copyright © 2023. Published by Elsevier Inc.)

Glutamate is traditionally viewed as the first messenger to activate NMDAR (N-methyl-D-aspartate receptor)-dependent cell death pathways in stroke 1,2 , but unsuccessful clinical trials with NMDAR antagonists implicate the engagement of other mechanisms 3-7 . Here we show that glutamate and its structural analogues, including NMDAR antagonist L-AP5 (also known as APV), robustly potentiate currents mediated by acid-sensing ion channels (ASICs) associated with acidosis-induced neurotoxicity in stroke 4 . Glutamate increases the affinity of ASICs for protons and their open probability, aggravating ischaemic neurotoxicity in both in vitro and in vivo models. Site-directed mutagenesis, structure-based modelling and functional assays reveal a bona fide glutamate-binding cavity in the extracellular domain of ASIC1a. Computational drug screening identified a small molecule, LK-2, that binds to this cavity and abolishes glutamate-dependent potentiation of ASIC currents but spares NMDARs. LK-2 reduces the infarct volume and improves sensorimotor recovery in a mouse model of ischaemic stroke, reminiscent of that seen in mice with Asic1a knockout or knockout of other cation channels 4-7 . We conclude that glutamate functions as a positive allosteric modulator for ASICs to exacerbate neurotoxicity, and preferential targeting of the glutamate-binding site on ASICs over that on NMDARs may be strategized for developing stroke therapeutics lacking the psychotic side effects of NMDAR antagonists., (© 2024. The Author(s).)

Rational design of plant cis -regulatory DNA sequences without expert intervention or prior domain knowledge is still a daunting task. Here, we developed PhytoExpr, a deep learning framework capable of predicting both mRNA abundance and plant species using the proximal regulatory sequence as the sole input. PhytoExpr was trained over 17 species representative of major clades of the plant kingdom to enhance its generalizability. Via input perturbation, quantitative functional annotation of the input sequence was achieved at single-nucleotide resolution, revealing an abundance of predicted high-impact nucleotides in conserved noncoding sequences and transcription factor binding sites. Evaluation of maize HapMap3 single-nucleotide polymorphisms (SNPs) by PhytoExpr demonstrates an enrichment of predicted high-impact SNPs in cis -eQTL. Additionally, we provided two algorithms that harnessed the power of PhytoExpr in designing functional cis -regulatory variants, and de novo creation of species-specific cis -regulatory sequences through in silico evolution of random DNA sequences. Our model represents a general and robust approach for functional variant discovery in population genetics and rational design of regulatory sequences for genome editing and synthetic biology., Competing Interests: Competing interests statement:The authors declare no competing interest.

Tandem donor splice sites (5'ss) are unique regions with at least two GU dinucleotides serving as splicing cleavage sites. The Δ3 tandem 5'ss are a specific subclass of 5'ss separated by 3 nucleotides which can affect protein function by inserting/deleting a single amino acid. One 5'ss is typically preferred, yet factors governing particular 5'ss choice are not fully understood. A highly conserved exon 21 of the STAT3 gene was chosen as a model to study Δ3 tandem 5'ss splicing mechanisms. Based on multiple lines of experimental evidence, endogenous U1 snRNA most likely binds only to the upstream 5'ss. However, the downstream 5'ss is used preferentially, and the splice site choice is not dependent on the exact U1 snRNA binding position. Downstream 5'ss usage was sensitive to exact nucleotide composition and dependent on the presence of downstream regulatory region. The downstream 5'ss usage could be best explained by two novel interactions with endogenous U6 snRNA. U6 snRNA enables the downstream 5'ss usage in STAT3 exon 21 by two mechanisms: (i) binding in a novel non-canonical register and (ii) establishing extended Watson-Crick base pairing with the downstream regulatory region. This study suggests that U6:5'ss interaction is more flexible than previously thought., (© The Author(s) 2024. Published by Oxford University Press on behalf of Nucleic Acids Research.)

Male development in mammals depends on the activity of the two SOX gene: Sry and Sox9, in the embryonic testis. As deletion of Enhancer 13 (Enh13) of the Sox9 gene results in XY male-to-female sex reversal, we explored the critical elements necessary for its function and hence, for testis and male development. Here, we demonstrate that while microdeletions of individual transcription factor binding sites (TFBS) in Enh13 lead to normal testicular development, combined microdeletions of just two SRY/SOX binding motifs can alone fully abolish Enh13 activity leading to XY male-to-female sex reversal. This suggests that for proper male development to occur, these few nucleotides of non-coding DNA must be intact. Interestingly, we show that depending on the nature of these TFBS mutations, dramatically different phenotypic outcomes can occur, providing a molecular explanation for the distinct clinical outcomes observed in patients harboring different variants in the same enhancer., (© The Author(s) 2024. Published by Oxford University Press on behalf of Nucleic Acids Research.)

Aims: Evaluating the association between a single nucleotide polymorphism in the 3' untranslated region (3'UTR) of the miRNA binding site of the NLRP3 gene and the occurrence and development of chronic obstructive pulmonary disease (COPD) and providing information to aid in the early detection and treatment of COPD. Materials and Methods: The regulatory single nuclear polymorphisms (SNPs) located in NLRP3 3'UTR were searched by using the dbSNP database and miRNA binding site prediction database. Meanwhile, samples from COPD patients and healthy controls in the same period were used for verification. The clinical baseline information of all subjects was collected, and the transcription level and protein expression level of NLRP3 and the expression level of inflammatory factors downstream of NLRP3 were detected. The effects of SNPs' single nucleotide changes on the transcription and expression of inflammatory factors were analyzed. Results: The study included 418 participants (249 in the COPD group and 169 in the control group). NLRP3 SNPs with miRNA binding sites include rs10754558 (G > C), rs1664774076 (ATAT > del), and rs1664775106 (C > G). Furthermore, two genotypes, GCG and GCA, were discovered to have a linkage mutation at 3'UTR 459-461. COPD susceptibility is tightly associated with the expression of the rs1664774076 del/del genotype, and the risk of COPD increased by 2.770 times ( p = 0.003). Type 459-461 GCA was substantially related to the likelihood of developing COPD at various stages ( p < 0.05). Except for rs10754558, all homozygous mutants increased NLRP3 mRNA and protein levels. NLRP3 had the greatest area under the receiver operating characteristic (ROC) curve for predicting the development and diagnosis of COPD when compared with its downstream inflammatory variables (AUC = 0.9291). Conclusions: The NLRP3 rs1664774076 del/del genotype is a COPD susceptibility gene, and the GCA genotype at 459-461 can be used as an early predictor of COPD exacerbation. The NLRP3 3'UTR polymorphism may alter the loss of miRNA binding sites, leading to an increase in NLRP3 expression. In the development of COPD, NLRP3 has a better diagnostic value than traditional inflammatory factors. The Clinical Trials Registration number Z: protocol KY01-2020-11-06.

SLC45A1 encodes a glucose transporter protein highly expressed in the brain. Mutations in SLC45A1 may lead to neurological diseases and developmental disorders, but its exact role is poorly understood. DNA G-quadruplexes (DNA G4s) are stable structures formed by four guanine bases and play a role in gene regulation and genomic stability. Changes in DNA G4s may affect brain development and function. The mechanism linking alterations in DNA G-quadruplex structures to SLC45A1 pathogenicity remains unknown. In this study, we identify a functional DNA G-quadruplex and its key binding site on SLC45A1 (NM&#95;001080397.3: exon 2: c.449 G>A: p.R150K). This variant results in the upregulation of mRNA and protein expression, which may lead to intellectual developmental disorder with neuropsychiatric features. Mechanistically, the mutation is found to disrupt DNA G-quadruplex structures on SLC45A1 , leading to transcriptional enhancement and a gain-of-function mutation, which further causes increased expression and function of the SLC45A1 protein. The identification of the functional DNA G-quadruplex and its effects on DNA G4s may provide new insights into the genetic basis of SLC45A1 pathogenicity and highlight the importance of DNA G4s of SLC45A1 in regulating gene expression and brain development.

We integrate evolutionary predictions based on the neutral theory of molecular evolution with protein dynamics to generate mechanistic insight into the molecular adaptations of the SARS-COV-2 spike (S) protein. With this approach, we first identified candidate adaptive polymorphisms (CAPs) of the SARS-CoV-2 S protein and assessed the impact of these CAPs through dynamics analysis. Not only have we found that CAPs frequently overlap with well-known functional sites, but also, using several different dynamics-based metrics, we reveal the critical allosteric interplay between SARS-CoV-2 CAPs and the S protein binding sites with the human ACE2 (hACE2) protein. CAPs interact far differently with the hACE2 binding site residues in the open conformation of the S protein compared to the closed form. In particular, the CAP sites control the dynamics of binding residues in the open state, suggesting an allosteric control of hACE2 binding. We also explored the characteristic mutations of different SARS-CoV-2 strains to find dynamic hallmarks and potential effects of future mutations. Our analyses reveal that Delta strain-specific variants have non-additive (i.e., epistatic) interactions with CAP sites, whereas the less pathogenic Omicron strains have mostly additive mutations. Finally, our dynamics-based analysis suggests that the novel mutations observed in the Omicron strain epistatically interact with the CAP sites to help escape antibody binding., Competing Interests: NO, PC, TM, IK, SK, SO No competing interests declared, (© 2023, Ose et al.)

The human enzyme 2'-deoxynucleoside 5'-phosphate N-hydrolase 1 (HsDNPH1) catalyses the hydrolysis of 5-hydroxymethyl-2'-deoxyuridine 5'-phosphate to generate 5-hydroxymethyluracil and 2-deoxyribose-5-phosphate via a covalent 5-phospho-2-deoxyribosylated enzyme intermediate. HsDNPH1 is a promising target for inhibitor development towards anticancer drugs. Here, site-directed mutagenesis of conserved active-site residues, followed by HPLC analysis of the reaction and steady-state kinetics are employed to reveal the importance of each of these residues in catalysis, and the reaction pH-dependence is perturbed by each mutation. Solvent deuterium isotope effects indicate no rate-limiting proton transfers. Crystal structures of D80N-HsDNPH1 in unliganded and substrate-bound states, and of unliganded D80A- and Y24F-HsDNPH1 offer atomic level insights into substrate binding and catalysis. The results reveal a network of hydrogen bonds involving the substrate and the E104-Y24-D80 catalytic triad and are consistent with a proposed mechanism whereby D80 is important for substrate positioning, for helping modulate E104 nucleophilicity, and as the general acid in the first half-reaction. Y24 positions E104 for catalysis and prevents a catalytically disruptive close contact between E104 and D80., (© 2024 Wiley‐VCH GmbH.)

Adenovirus (AdV) infection of the respiratory epithelium is common but poorly understood. Human AdV species C types, such as HAdV-C5, utilize the Coxsackie-adenovirus receptor (CAR) for attachment and subsequently integrins for entry. CAR and integrins are however located deep within the tight junctions in the mucosa where they would not be easily accessible. Recently, a model for CAR-independent AdV entry was proposed. In this model, human lactoferrin (hLF), an innate immune protein, aids the viral uptake into epithelial cells by mediating interactions between the major capsid protein, hexon, and yet unknown host cellular receptor(s). However, a detailed understanding of the molecular interactions driving this mechanism is lacking. Here, we present a new cryo-EM structure of HAdV-5C hexon at high resolution alongside a hybrid structure of HAdV-5C hexon complexed with human lactoferrin (hLF). These structures reveal the molecular determinants of the interaction between hLF and HAdV-C5 hexon. hLF engages hexon primarily via its N-terminal lactoferricin (Lfcin) region, interacting with hexon's hypervariable region 1 (HVR-1). Mutational analyses pinpoint critical Lfcin contacts and also identify additional regions within hLF that critically contribute to hexon binding. Our study sheds more light on the intricate mechanism by which HAdV-C5 utilizes soluble hLF/Lfcin for cellular entry. These findings hold promise for advancing gene therapy applications and inform vaccine development., Importance: Our study delves into the structural aspects of adenovirus (AdV) infections, specifically HAdV-C5 in the respiratory epithelium. It uncovers the molecular details of a novel pathway where human lactoferrin (hLF) interacts with the major capsid protein, hexon, facilitating viral entry, and bypassing traditional receptors such as CAR and integrins. The study's cryo-EM structures reveal how hLF engages hexon, primarily through its N-terminal lactoferricin (Lfcin) region and hexon's hypervariable region 1 (HVR-1). Mutational analyses identify critical Lfcin contacts and other regions within hLF vital for hexon binding. This structural insight sheds light on HAdV-C5's mechanism of utilizing soluble hLF/Lfcin for cellular entry, holding promise for gene therapy and vaccine development advancements in adenovirus research., Competing Interests: The authors declare no conflict of interest.

Eukaryotic tRNA guanine transglycosylase (TGT) is an RNA-modifying enzyme which catalyzes the base exchange of the genetically encoded guanine 34 of tRNAs Asp,Asn,His,Tyr for queuine, a hypermodified 7-deazaguanine derivative. Eukaryotic TGT is a heterodimer comprised of a catalytic and a non-catalytic subunit. While binding of the tRNA anticodon loop to the active site is structurally well understood, the contribution of the non-catalytic subunit to tRNA binding remained enigmatic, as no complex structure with a complete tRNA was available. Here, we report a cryo-EM structure of eukaryotic TGT in complex with a complete tRNA, revealing the crucial role of the non-catalytic subunit in tRNA binding. We decipher the functional significance of these additional tRNA-binding sites, analyze solution state conformation, flexibility, and disorder of apo TGT, and examine conformational transitions upon tRNA binding., Competing Interests: Declaration of interests The authors declare no competing interests., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Chloramphenicols (CAPs) are ubiquitous emerging pollutants that threaten ecological environments and human health. Microbial and enzyme-based biodegradation strategies offer a cost-effective environmentally friendly approach for CAPs removal from contaminated sites. Here, CpmO, a novel multifunctional oxidase for CAP degradation was identified from the CAP-degrading strain Sphingobium sp. WTD-1. This enzyme was found to be responsible for both the oxidation of the C3-hydroxyl and oxidative cleavage of the C1-C2 bond of CAP, and the oxidative cleavage pathway of CAP was dominant. The catalytic efficiency of CpmO for CAP was 41.6 times that for thiamphenicol (TAP) under the optimal conditions (40 °C, pH 6.0). CpmO was identified as a member of the glucose-methanol-choline oxidoreductase family. Molecular docking and site-directed mutagenesis analysis indicated that CAP was connected to the key amino acid residues E231/E395, K277, and I273/A276 in CpmO through hydrogen bonding, nonclassical hydrogen bonding, and π-π stacking forces, respectively. The catalytic activities of the A276W, K277P, and E231S mutants were found to be 1.1 times, 6.4 times, and 13.2 times higher than that of the wild type, respectively. These findings provide genetic resources and theoretical guidance for future application in biotechnological and metabolic engineering efforts for the remediation of CAPs-contaminated environments., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier B.V. All rights reserved.)

Cell-type-Specific Chromatin Loops (CSCLs) are crucial for gene regulation and cell fate determination. However, the mechanisms governing their establishment remain elusive. Here, we present SpecLoop, a network regularization-based machine learning framework, to investigate the role of transcription factors (TFs) cooperation in CSCL formation. SpecLoop integrates multi-omics data, including gene expression, chromatin accessibility, sequence, protein-protein interaction, and TF binding motif data, to predict CSCLs and identify TF cooperations. Using high resolution Hi-C data as the gold standard, SpecLoop accurately predicts CSCL in GM12878, IMR90, HeLa-S3, K562, HUVEC, HMEC, and NHEK seven cell types, with the AUROC values ranging from 0.8645 to 0.9852 and AUPR values ranging from 0.8654 to 0.9734. Notably SpecLoop demonstrates improved accuracy in predicting long-distance CSCLs and identifies TF complexes with strong predictive ability. Our study systematically explores the TFs and TF pairs associated with CSCL through effective integration of diverse omics data. SpecLoop is freely available at https://github.com/AMSSwanglab/SpecLoop., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Objectives: Krüppel-like factor (KLF)5, which is overexpressed in carcinomas such as oral cancer, inhibits epidermal differentiation. KLF5 induces dedifferentiation of carcinoma cells, which effectuates carcinoma progression; nevertheless, the regulatory mechanism affecting the transcription of the KLF5 gene remains ambiguous., Methods: Transcriptional activity of the KLF5 silencer, specifically the 425-bp region (425-region), was examined using reporter assays. An additional analysis was conducted to assess the impact of the minimal essential region (MER) of KLF5 on its basal expression. The affinity of cAMP responsive element binding protein 1 (CREB1) for three potential CREB1-binding sites in the 425-region was analyzed using DNA pull-down and quantitative chromatin immunoprecipitation assays. Reporter assays employing a human oral squamous carcinoma cell line, HSC2, transfected with small interfering RNA or complementary DNA for CREB1, were performed to investigate the effect of CREB1 binding sites on MER activity., Results: The 425-region exhibited no transcriptional activity and suppressed MER transcriptional activity. This region encodes three putative CREB1-binding sites, and CREB1 demonstrated equal binding affinity for all three sites. The deletion of each of these binding sites reduced CREB1 precipitation and enhanced MER activity. Endogenous CREB1 knockdown and overexpression elevated and reduced MER activity, respectively, at the intact sites. Conversely, site deletion hampered and improved MER activity upon CREB1 knockdown and overexpression, respectively., Conclusions: Suppression of KLF5 basal expression via CREB1 binding to the 425-region requires all three CREB1-binding sites to remain intact in oral carcinoma cells. Consequently, deletion of the CREB1-binding site relieves suppression of KLF5 basal expression., Competing Interests: Declaration of competing interest The authors have no conflicts of interest to report., (Copyright © 2023 Japanese Association for Oral Biology. Published by Elsevier B.V. All rights reserved.)

A large-scale search for the genetic variants with a bias in the representation of alleles in transcriptome data (AE SNPs) and the binding sites in microRNA 3'-UTRs was performed and their functional significance was assessed using massively parallel reporter assay (MPRA). Of the 629,559 associated "SNP-gene" pairs (eQTLs) discovered in the human liver tissue according to the GTEx Analysis V8 data, 4394 polymorphic positions in the 3'-UTRs of the genes, which represent the eQTLs for these genes were selected. The TargetScanHuman 7.0 algorithm and PolymiRTS database were searched for the potential microRNA-binding sites. Of the predicted microRNA sites affected by eQTL-SNPs, we selected 51 sites with the best evidence of functionality according to Ago2-CLIP-seq, CLEAR-CLIP, and eCLIP-seq for RNA-binding proteins. For MPRA, a library of the plasmids carrying the main and alternative alleles for each AE SNP (in total, 102 constructs) was created. Allele-specific expression for 6 SNPs was detected by transfection of the HepG2 cell line with the constructed plasmid library and sequencing of target DNA and RNA sequences using the Illumina (MiSeq) platform., (© 2024. Springer Science+Business Media, LLC, part of Springer Nature.)

A mutant of ubiquitin C-terminal hydrolase L1 (UCHL1) detected in early-onset neurodegenerative patients, UCHL1 R178Q , showed higher catalytic activity than wild-type UCHL1 (UCHL1 WT ). Lying within the active-site pocket, the arginine is part of an interaction network that holds the catalytic histidine in an inactive arrangement. However, the structural basis and mechanism of enzymatic activation upon glutamine substitution was not understood. We combined X-ray crystallography, protein nuclear magnetic resonance (NMR) analysis, enzyme kinetics, covalent inhibition analysis, and biophysical measurements to delineate activating factors in the mutant. While the crystal structure of UCHL1 R178Q showed nearly the same arrangement of the catalytic residues and active-site pocket, the mutation caused extensive alteration in the chemical environment and dynamics of more than 30 residues, some as far as 15 Å away from the site of mutation. Significant broadening of backbone amide resonances in the HSQC spectra indicates considerable backbone dynamics changes in several residues, in agreement with solution small-angle X-ray scattering (SAXS) analyses which indicate an overall increase in protein flexibility. Enzyme kinetics show the activation is due to a k cat effect despite a slightly weakened substrate affinity. In line with this, the mutant shows a higher second-order rate constant (k inact /K i ) in a reaction with a substrate-derived irreversible inhibitor, Ub-VME, compared to the wild-type enzyme, an observation indicative of a more reactive catalytic cysteine in the mutant. Together, the observations underscore structural plasticity as a factor contributing to enzyme kinetic behavior which can be modulated through mutational effects., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Genome-wide association studies (GWAS) are a powerful tool for detecting variants associated with complex traits and can help risk stratification and prevention strategies against pancreatic ductal adenocarcinoma (PDAC). However, the strict significance threshold commonly used makes it likely that many true risk loci are missed. Functional annotation of GWAS polymorphisms is a proven strategy to identify additional risk loci. We aimed to investigate single-nucleotide polymorphisms (SNP) in regulatory regions [transcription factor binding sites (TFBSs) and enhancers] that could change the expression profile of multiple genes they act upon and thereby modify PDAC risk. We analyzed a total of 12,636 PDAC cases and 43,443 controls from PanScan/PanC4 and the East Asian GWAS (discovery populations), and the PANDoRA consortium (replication population). We identified four associations that reached study-wide statistical significance in the overall meta-analysis: rs2472632(A) (enhancer variant, OR 1.10, 95%CI 1.06,1.13, p = 5.5 × 10 -8 ), rs17358295(G) (enhancer variant, OR 1.16, 95%CI 1.10,1.22, p = 6.1 × 10 -7 ), rs2232079(T) (TFBS variant, OR 0.88, 95%CI 0.83,0.93, p = 6.4 × 10 -6 ) and rs10025845(A) (TFBS variant, OR 1.88, 95%CI 1.50,1.12, p = 1.32 × 10 -5 ). The SNP with the most significant association, rs2472632, is located in an enhancer predicted to target the coiled-coil domain containing 34 oncogene. Our results provide new insights into genetic risk factors for PDAC by a focused analysis of polymorphisms in regulatory regions and demonstrating the usefulness of functional prioritization to identify loci associated with PDAC risk., (© 2024. The Author(s).)

Neuropilin-1 (NRP1) which is a main transmembrane cell surface receptor acts as a host cell mediator resulting in increasing the SARS-Cov-2 infectivity and also plays a role in neuronal development, angiogenesis and axonal outgrowth. The goal of this study is to estimate the impact of single nucleotide polymorphisms (SNPs) in the NRP1 gene on the function, structure and stabilization of protein as well as on the miRNA-mRNA binding regions using bioinformatical tools. It is also aimed to investigate the changes caused by SNPs in NRP1 on interactions with drug molecule and spike protein. The missense type of SNPs was analyzed using SIFT, PolyPhen-2, SNAP2, PROVEAN, Mutation Assessor, SNPs&GO, PhD-SNP, I-Mutant 3.0, MUpro, STRING, Project HOPE, ConSurf, and PolymiRTS. Docking analyses were conducted by AutoDock Vina program. As a result, a total of 733 missense SNPs were determined within the NRP1 gene and nine SNPs were specified as damaging to the protein. The modelling results showed that wild and mutant type amino acids had some different properties such as size, charge, and hydrophobicity. Additionally, their three-dimensional structures of protein were utilized for confirmation of these differences. After evaluating the results, nine polymorphisms rs141633354, rs142121081, rs145954532, rs200028992, rs200660300, rs369312020, rs370117610, rs370551432, rs370641686 were determined to be damaging on the structure and function of NRP1 protein and located in conserved regions. The results of molecular docking showed that the binding affinity values are nearly the same for wild-type and mutant structures support that the mutations carried out are not in the focus of the binding site, therefore the ligand does not affect the binding energy. It is expected that the results will be useful for future studies., (© 2023. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

RNA-binding proteins (RBPs) regulate diverse cellular processes by dynamically interacting with RNA targets. However, effective methods to capture both stable and transient interactions between RBPs and their RNA targets are still lacking, especially when the interaction is dynamic or samples are limited. Here we present an assay of reverse transcription-based RBP binding site sequencing (ARTR-seq), which relies on in situ reverse transcription of RBP-bound RNAs guided by antibodies to identify RBP binding sites. ARTR-seq avoids ultraviolet crosslinking and immunoprecipitation, allowing for efficient and specific identification of RBP binding sites from as few as 20 cells or a tissue section. Taking advantage of rapid formaldehyde fixation, ARTR-seq enables capturing the dynamic RNA binding by RBPs over a short period of time, as demonstrated by the profiling of dynamic RNA binding of G3BP1 during stress granule assembly on a timescale as short as 10 minutes., (© 2024. The Author(s).)

RNA binding proteins (RBPs) are key regulators of RNA processing and cellular function. Technologies to discover RNA targets of RBPs such as TRIBE (targets of RNA binding proteins identified by editing) and STAMP (surveying targets by APOBEC1 mediated profiling) utilize fusions of RNA base-editors (rBEs) to RBPs to circumvent the limitations of immunoprecipitation (CLIP)-based methods that require enzymatic digestion and large amounts of input material. To broaden the repertoire of rBEs suitable for editing-based RBP-RNA interaction studies, we have devised experimental and computational assays in a framework called PRINTER (protein-RNA interaction-based triaging of enzymes that edit RNA) to assess over thirty A-to-I and C-to-U rBEs, allowing us to identify rBEs that expand the characterization of binding patterns for both sequence-specific and broad-binding RBPs. We also propose specific rBEs suitable for dual-RBP applications. We show that the choice between single or multiple rBEs to fuse with a given RBP or pair of RBPs hinges on the editing biases of the rBEs and the binding preferences of the RBPs themselves. We believe our study streamlines and enhances the selection of rBEs for the next generation of RBP-RNA target discovery., (© 2024. The Author(s).)

The transcriptional regulatory network (TRN) of E. coli consists of thousands of interactions between regulators and DNA sequences. Regulons are typically determined either from resource-intensive experimental measurement of functional binding sites, or inferred from analysis of high-throughput gene expression datasets. Recently, independent component analysis (ICA) of RNA-seq compendia has shown to be a powerful method for inferring bacterial regulons. However, it remains unclear to what extent regulons predicted by ICA structure have a biochemical basis in promoter sequences. Here, we address this question by developing machine learning models that predict inferred regulon structures in E. coli based on promoter sequence features. Models were constructed successfully (cross-validation AUROC > = 0.8) for 85% (40/47) of ICA-inferred E. coli regulons. We found that: 1) The presence of a high scoring regulator motif in the promoter region was sufficient to specify regulatory activity in 40% (19/47) of the regulons, 2) Additional features, such as DNA shape and extended motifs that can account for regulator multimeric binding, helped to specify regulon structure for the remaining 60% of regulons (28/47); 3) investigating regulons where initial machine learning models failed revealed new regulator-specific sequence features that improved model accuracy. Finally, we found that strong regulatory binding sequences underlie both the genes shared between ICA-inferred and experimental regulons as well as genes in the E. coli core pan-regulon of Fur. This work demonstrates that the structure of ICA-inferred regulons largely can be understood through the strength of regulator binding sites in promoter regions, reinforcing the utility of top-down inference for regulon discovery., Competing Interests: The authors declare that there are no competing interests., (Copyright: © 2024 Qiu et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Non-coding variants associated with complex traits can alter the motifs of transcription factor (TF)-deoxyribonucleic acid binding. Although many computational models have been developed to predict the effects of non-coding variants on TF binding, their predictive power lacks systematic evaluation. Here we have evaluated 14 different models built on position weight matrices (PWMs), support vector machines, ordinary least squares and deep neural networks (DNNs), using large-scale in vitro (i.e. SNP-SELEX) and in vivo (i.e. allele-specific binding, ASB) TF binding data. Our results show that the accuracy of each model in predicting SNP effects in vitro significantly exceeds that achieved in vivo. For in vitro variant impact prediction, kmer/gkm-based machine learning methods (deltaSVM&#95;HT-SELEX, QBiC-Pred) trained on in vitro datasets exhibit the best performance. For in vivo ASB variant prediction, DNN-based multitask models (DeepSEA, Sei, Enformer) trained on the ChIP-seq dataset exhibit relatively superior performance. Among the PWM-based methods, tRap demonstrates better performance in both in vitro and in vivo evaluations. In addition, we find that TF classes such as basic leucine zipper factors could be predicted more accurately, whereas those such as C2H2 zinc finger factors are predicted less accurately, aligning with the evolutionary conservation of these TF classes. We also underscore the significance of non-sequence factors such as cis-regulatory element type, TF expression, interactions and post-translational modifications in influencing the in vivo predictive performance of TFs. Our research provides valuable insights into selecting prioritization methods for non-coding variants and further optimizing such models., (© The Author(s) 2024. Published by Oxford University Press.)

The effects of transcription factor binding sites (TFBSs) on the activity of a cis-regulatory element (CRE) depend on the local sequence context. In rod photoreceptors, binding sites for the transcription factor (TF) Cone-rod homeobox (CRX) occur in both enhancers and silencers, but the sequence context that determines whether CRX binding sites contribute to activation or repression of transcription is not understood. To investigate the context-dependent activity of CRX sites, we fit neural network-based models to the activities of synthetic CREs composed of photoreceptor TFBSs. The models revealed that CRX binding sites consistently make positive, independent contributions to CRE activity, while negative homotypic interactions between sites cause CREs composed of multiple CRX sites to function as silencers. The effects of negative homotypic interactions can be overcome by the presence of other TFBSs that either interact cooperatively with CRX sites or make independent positive contributions to activity. The context-dependent activity of CRX sites is thus determined by the balance between positive heterotypic interactions, independent contributions of TFBSs, and negative homotypic interactions. Our findings explain observed patterns of activity among genomic CRX-bound enhancers and silencers, and suggest that enhancers may require diverse TFBSs to overcome negative homotypic interactions between TFBSs., Competing Interests: I have read the journal’s policy and the authors of this manuscript have the following competing interests: BAC is on the scientific advisory board of Patch Biosciences. Neither any reagent nor any funding from this organizations was used in this study. Other co-authors have no competing interests to declare., (Copyright: © 2024 Loell et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

We present a major update of the HOCOMOCO collection that provides DNA binding specificity patterns of 949 human transcription factors and 720 mouse orthologs. To make this release, we performed motif discovery in peak sets that originated from 14 183 ChIP-Seq experiments and reads from 2554 HT-SELEX experiments yielding more than 400 thousand candidate motifs. The candidate motifs were annotated according to their similarity to known motifs and the hierarchy of DNA-binding domains of the respective transcription factors. Next, the motifs underwent human expert curation to stratify distinct motif subtypes and remove non-informative patterns and common artifacts. Finally, the curated subset of 100 thousand motifs was supplied to the automated benchmarking to select the best-performing motifs for each transcription factor. The resulting HOCOMOCO v12 core collection contains 1443 verified position weight matrices, including distinct subtypes of DNA binding motifs for particular transcription factors. In addition to the core collection, HOCOMOCO v12 provides motif sets optimized for the recognition of binding sites in vivo and in vitro, and for annotation of regulatory sequence variants. HOCOMOCO is available at https://hocomoco12.autosome.org and https://hocomoco.autosome.org., (© The Author(s) 2023. Published by Oxford University Press on behalf of Nucleic Acids Research.)

Evolution of gene expression mediated by cis-regulatory changes is thought to be an important contributor to organismal adaptation, but identifying adaptive cis-regulatory changes is challenging due to the difficulty in knowing the expectation under no positive selection. A new approach for detecting positive selection on transcription factor binding sites (TFBSs) was recently developed, thanks to the application of machine learning in predicting transcription factor (TF) binding affinities of DNA sequences. Given a TFBS sequence from a focal species and the corresponding inferred ancestral sequence that differs from the former at n sites, one can predict the TF-binding affinities of many n-step mutational neighbors of the ancestral sequence and obtain a null distribution of the derived binding affinity, which allows testing whether the binding affinity of the real derived sequence deviates significantly from the null distribution. Applying this test genomically to all experimentally identified binding sites of 3 TFs in humans, a recent study reported positive selection for elevated binding affinities of TFBSs. Here, we show that this genomic test suffers from an ascertainment bias because, even in the absence of positive selection for strengthened binding, the binding affinities of known human TFBSs are more likely to have increased than decreased in evolution. We demonstrate by computer simulation that this bias inflates the false positive rate of the selection test. We propose several methods to mitigate the ascertainment bias and show that almost all previously reported positive selection signals disappear when these methods are applied., (© The Author(s) 2023. Published by Oxford University Press on behalf of Society for Molecular Biology and Evolution.)

Protein-protein interactions (PPIs) drive many cellular processes. Some interactions are directed by Src homology 3 (SH3) domains that bind proline-rich motifs on other proteins. The evolution of the binding specificity of SH3 domains is not completely understood, particularly following gene duplication. Paralogous genes accumulate mutations that can modify protein functions and, for SH3 domains, their binding preferences. Here, we examined how the binding of the SH3 domains of 2 paralogous yeast type I myosins, Myo3 and Myo5, evolved following duplication. We found that the paralogs have subtly different SH3-dependent interaction profiles. However, by swapping SH3 domains between the paralogs and characterizing the SH3 domains freed from their protein context, we find that very few of the differences in interactions, if any, depend on the SH3 domains themselves. We used ancestral sequence reconstruction to resurrect the preduplication SH3 domains and examined, moving back in time, how the binding preference changed. Although the most recent ancestor of the 2 domains had a very similar binding preference as the extant ones, older ancestral domains displayed a gradual loss of interaction with the modern interaction partners when inserted in the extant paralogs. Molecular docking and experimental characterization of the free ancestral domains showed that their affinity with the proline motifs is likely not the cause for this loss of binding. Taken together, our results suggest that a SH3 and its host protein could create intramolecular or allosteric interactions essential for the SH3-dependent PPIs, making domains not functionally equivalent even when they have the same binding specificity., Competing Interests: Conflicts of interest The author(s) declare no conflict of interest., (© The Author(s) 2023. Published by Oxford University Press on behalf of The Genetics Society of America.)

Many non-coding variants associated with phenotypes occur in 3' untranslated regions (3' UTRs), and may affect interactions with RNA-binding proteins (RBPs) to regulate gene expression post-transcriptionally. However, identifying functional 3' UTR variants has proven difficult. We use allele frequencies from the Genome Aggregation Database (gnomAD) to identify classes of 3' UTR variants under strong negative selection in humans. We develop intergenic mutability-adjusted proportion singleton (iMAPS), a generalized measure related to MAPS, to quantify negative selection in non-coding regions. This approach, in conjunction with in vitro and in vivo binding data, identifies precise RBP binding sites, miRNA target sites, and polyadenylation signals (PASs) under strong selection. For each class of sites, we identify thousands of gnomAD variants under selection comparable to missense coding variants, and find that sites in core 3' UTR regions upstream of the most-used PAS are under strongest selection. Together, this work improves our understanding of selection on human genes and validates approaches for interpreting genetic variants in human 3' UTRs., (© 2024. The Author(s).)

MicroRNAs are a class of regulatory, non-coding small ribonucleic acid (RNA) molecules found in eukaryotes. Dysregulated expression of microRNAs can lead to downregulation or upregulation of their target gene. In general, microRNAs bind with the Argonaute protein and its interacting partners to form a silencing complex. This silencing complex binds with fully or partial complementary sequences in the 3'-UTR of their cognate target mRNAs and leads to degradation of the transcripts or translational inhibition, respectively. However, recent developments point towards the ability of these microRNAs to bind to the promoters, enhancers or coding sequences, leading to upregulation of their target genes. This review briefly summarizes the various non-canonical binding sites of microRNAs and their regulatory roles in various diseased conditions., (Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.net.)

Transcription factors (TFs) bind to specific regions of DNA known as transcription factor binding sites (TFBSs) and modulate gene expression by interacting with the transcriptional machinery. TFBSs are typically located upstream of target genes, within a few thousand base pairs of the transcription start site. The binding of TFs to TFBSs influences the recruitment of the transcriptional machinery, thereby regulating gene transcription in a precise and specific manner. This chapter provides practical examples and case studies demonstrating the extraction of upstream gene regions from the genome, identification of TFBSs using PWMEnrich R/Bioconductor package, interpretation of results, and preparation of publication-ready figures and tables. The EOMES promoter is used as a case study for single DNA sequence analysis, revealing potential regulation by the LHX9-FOXP1 complex during embryonic development. Additionally, an example is presented on how to investigate TFBSs in the upstream regions of a group of genes, using a case study of differentially expressed genes in response to human parainfluenza virus type 1 (HPIV1) infection and interferon-beta. Key regulators identified in this context include the STAT1:STAT2 heterodimer and interferon regulatory factor family proteins. The presented protocol is designed to be accessible to individuals with basic computer literacy. Understanding the interactions between TFs and TFBSs provides insights into the complex transcriptional regulatory networks that govern gene expression, with broad implications for several fields such as developmental biology, immunology, and disease research., (© 2024. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.)

Insect embryonic development and morphology are characterized by their anterior-posterior and dorsal-ventral (DV) patterning. In Drosophila embryos, DV patterning is mediated by a dorsal protein gradient which activates twist and snail proteins, the important regulators of DV patterning. To activate or repress gene expression, some regulatory proteins bind in clusters to their target gene at sites known as cis-regulatory elements or enhancers. To understand how variations in gene expression in different lineages might lead to different phenotypes, it is necessary to understand enhancers and their evolution. Drosophila melanogaster has been widely studied to understand the interactions between transcription factors and the transcription factor binding sites. Tribolium castaneum is an upcoming model animal which is catching the interest of biologists and the research on the enhancer mechanisms in the insect's axes patterning is still in infancy. Therefore, the current study was designed to compare the enhancers of DV patterning in the two insect species. The sequences of ten proteins involved in DV patterning of D. melanogaster were obtained from Flybase. The protein sequences of T. castaneum orthologous to those obtained from D. melanogaster were acquired from NCBI BLAST, and these were then converted to DNA sequences which were modified by adding 20 kb sequences both upstream and downstream to the gene. These modified sequences were used for further analysis. Bioinformatics tools (Cluster-Buster and MCAST) were used to search for clusters of binding sites (enhancers) in the modified DV genes. The results obtained showed that the transcription factors in Drosophila melanogaster and Tribolium castaneum are nearly identical; however, the number of binding sites varies between the two species, indicating transcription factor binding site evolution, as predicted by two different computational tools. It was observed that dorsal, twist, snail, zelda, and Supressor of Hairless are the transcription factors responsible for the regulation of DV patterning in the two insect species., (© 2023. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Transcription factors contain a DNA-binding domain ensuring specific recognition of DNA target sequences. The family of forkhead (FOX) transcription factors is composed of dozens of paralogs in mammals. The forkhead domain (FHD) is a segment of about 100 amino acids that binds an A-rich DNA sequence. Using DNA and RNA PCR-SELEX, we show that recombinant FOXL2 proteins, either wild-type or carrying the oncogenic variant C134W, recognize similar DNA-binding sites. This suggests that the oncogenic variant does not alter the intrinsic sequence-specificity of FOXL2. Most importantly, we show that FOXL2 binds G2-rich RNA sequences whereas it virtually fails to bind similar sequences in DNA chemistry. Interestingly, a statistically significant subset of genes responding to the knock-down of FOXL2/Foxl2 harbor such G2-rich sequences and are involved in crucial signaling pathways and cellular processes. In addition, we show that FOXA1, FOXO3a and chimeric FOXL2 proteins containing the FHD of the former are also able to interact with some of the preferred FOXL2-binding sequences. Our results point to an unexpected and novel characteristic of the forkhead domain, the biological relevance of which remains to be explored., (© The Author(s) 2023. Published by Oxford University Press on behalf of Nucleic Acids Research.)

Proteins often regulate their activities via allostery-or action at a distance-in which the binding of a ligand at one binding site influences the affinity for another ligand at a distal site. Although less studied than in proteins, allosteric effects have been observed in experiments with DNA as well. In these experiments two or more proteins bind at distinct DNA sites and interact indirectly with each other, via a mechanism mediated by the linker DNA molecule. We develop a mechanical model of DNA/protein interactions which predicts three distinct mechanisms of allostery. Two of these involve an enthalpy-mediated allostery, while a third mechanism is entropy driven. We analyze experiments of DNA allostery and highlight the distinctive signatures allowing one to identify which of the proposed mechanisms best fits the data.

GCLiPP is a global RNA interactome capture method that detects RNA-binding protein (RBP) occupancy transcriptome-wide. GCLiPP maps RBP-occupied sites at a higher resolution than phase separation-based techniques. GCLiPP sequence tags correspond with known RBP binding sites and are enriched for sites detected by RBP-specific crosslinking immunoprecipitation (CLIP) for abundant cytosolic RBPs. Comparison of human Jurkat T cells and mouse primary T cells uncovers shared peaks of GCLiPP signal across homologous regions of human and mouse 3' UTRs, including a conserved mRNA-destabilizing cis-regulatory element. GCLiPP signal overlapping with immune-related SNPs uncovers stabilizing cis-regulatory regions in CD5, STAT6, and IKZF1., (© 2023. The Author(s).)