Deciphering principles of nucleosome interactions and impact of cancer-associated mutations from comprehensive interaction network analysis.

Nucleosomes represent hubs in chromatin organization and gene regulation and interact with a plethora of chromatin factors through different modes. In addition, alterations in histone proteins such as cancer mutations and post-translational modifications have profound effects on histone/nucleosome interactions. To elucidate the principles of histone interactions and the effects of those alterations, we developed histone interactomes for comprehensive mapping of histone-histone interactions (HHIs), histone-DNA interactions (HDIs), histone-partner interactions (HPIs) and DNA-partner interactions (DPIs) of 37 organisms, which contains a total of 3808 HPIs from 2544 binding proteins and 339 HHIs, 100 HDIs and 142 DPIs across 110 histone variants. With the developed networks, we explored histone interactions at different levels of granularities (protein-, domain- and residue-level) and performed systematic analysis on histone interactions at a large scale. Our analyses have characterized the preferred binding hotspots on both nucleosomal/linker DNA and histone octamer and unraveled diverse binding modes between nucleosome and different classes of binding partners. Last, to understand the impact of histone cancer-associated mutations on histone/nucleosome interactions, we complied one comprehensive cancer mutation dataset including 7940 cancer-associated histone mutations and further mapped those mutations onto 419,125 histone interactions at the residue level. Our quantitative analyses point to histone cancer-associated mutations' strongly disruptive effects on HHIs, HDIs and HPIs. We have further predicted 57 recurrent histone cancer mutations that have large effects on histone/nucleosome interactions and may have driver status in oncogenesis.

Detection of new pioneer transcription factors as cell-type-specific nucleosome binders.

Wrapping of DNA into nucleosomes restricts accessibility to DNA and may affect the recognition of binding motifs by transcription factors. A certain class of transcription factors, the pioneer transcription factors, can specifically recognize their DNA binding sites on nucleosomes, initiate local chromatin opening, and facilitate the binding of co-factors in a cell-type-specific manner. For the majority of human pioneer transcription factors, the locations of their binding sites, mechanisms of binding, and regulation remain unknown. We have developed a computational method to predict the cell-type-specific ability of transcription factors to bind nucleosomes by integrating ChIP-seq, MNase-seq, and DNase-seq data with details of nucleosome structure. We have demonstrated the ability of our approach in discriminating pioneer from canonical transcription factors and predicted new potential pioneer transcription factors in H1, K562, HepG2, and HeLa-S3 cell lines. Last, we systematically analyzed the interaction modes between various pioneer transcription factors and detected several clusters of distinctive binding sites on nucleosomal DNA.

Bound ion effects: Using machine learning method to study the kinesin Ncd's binding with microtubule.

Drosophila Ncd proteins are motor proteins that play important roles in spindle organization. Ncd and the tubulin dimer are highly charged. Thus, it is crucial to investigate Ncd-tubulin dimer interactions in the presence of ions, especially ions that are bound or restricted at the Ncd-tubulin dimer binding interfaces. To consider the ion effects, widely used implicit solvent models treat ions implicitly in the continuous solvent environment without focusing on the individual ions' effects. But highly charged biomolecules such as the Ncd and tubulin dimer may capture some ions at highly charged regions as bound ions. Such bound ions are restricted to their binding sites; thus, they can be treated as part of the biomolecules. By applying multiscale computational methods, including the machine-learning-based Hybridizing Ions Treatment-2 program, molecular dynamics simulations, DelPhi, and DelPhiForce, we studied the interaction between the Ncd motor domain and the tubulin dimer using a hybrid solvent model, which considers the bound ions explicitly and the other ions implicitly in the solvent environment. To identify the importance of treating bound ions explicitly, we also performed calculations using the implicit solvent model without considering the individual bound ions. We found that the calculations of the electrostatic features differ significantly between those of the hybrid solvent model and the pure implicit solvent model. The analyses show that treating bound ions at highly charged regions explicitly is crucial for electrostatic calculations. This work proposes a machine-learning-based approach to handle the bound ions using the hybrid solvent model. Such an approach is not only capable of handling kinesin-tubulin complexes but is also appropriate for other highly charged biomolecules, such as DNA/RNA, viral capsid proteins, etc.

Detection of new pioneer transcription factors as cell-type specific nucleosome binders.

Wrapping of DNA into nucleosomes restricts accessibility to the DNA and may affect the recognition of binding motifs by transcription factors. A certain class of transcription factors, the pioneer transcription factors, can specifically recognize their DNA binding sites on nucleosomes, may initiate local chromatin opening and facilitate the binding of co-factors in a cell-type-specific manner. For the majority of human pioneer transcription factors, the locations of their binding sites, mechanisms of binding and regulation remain unknown. We have developed a computational method to predict the cell-type-specific ability of transcription factors to bind nucleosomes by integrating ChIP-seq, MNase-seq and DNase-seq data with details of nucleosome structure. We have demonstrated the ability of our approach in discriminating pioneer from canonical transcription factors and predicted new potential pioneer transcription factors in H1, K562, HepG2 and HeLa cell lines. Lastly, we systemically analyzed the interaction modes between various pioneer transcription factors and detected several clusters of distinctive binding sites on nucleosomal DNA.

Aberrant DNA methylation and expression of EYA4 in gastric cardia intestinal metaplasia.

Background: Intestinal metaplasia (IM) of the gastric cardia is an important premalignant lesion. However, there is limited information concerning its epidemiological and molecular features. Herein, we aimed to provide an overview of the epidemiological data for gastric cardiac IM and evaluate the role of EYA transcriptional coactivator and phosphatase 4 (EYA4) as an epigenetic biomarker for gastric cardiac IM. Methods: The study was conducted in the context of the gastric cardiac precancerous lesion program in southern China, which included 718 non-cancer participants, who undertook endoscopic biopsy and pathological examination in three endoscopy centers, between November 2018 and November 2021. Pyrosequencing and immunohistochemistry were performed to examine the DNA methylation status and protein expression level of EYA4. Results: Gastric cardiac IM presented in 14.1% (101/718) of participants and was more common among older (>50 years; 22.0% [95% CI: 17.8-26.8]) than younger participants (≤50 years; 6.7% [95% CI: 4.5-9.9]; P < 0.001). IM was more common in male participants (16.9% [95% CI: 13.2-21.3] vs. 11.3% [95% CI: 8.3-15.1]; P = 0.04). Pyrosequencing revealed that IM tissues exhibited significantly higher DNA methylation levels in EYA4 gene than normal tissues (P = 0.016). Further, the protein expression level of EYA4 was reduced in IM and absent in intraepithelial neoplasia tissues compared to normal tissues (P < 0.001). Conclusions: Detection rates of gastric cardiac IM increase with age and are higher in men. Our findings highlight the important role of promoter hypermethylation and downregulation of EYA4 in gastric cardiac IM development.

Pharmacogenetics of human sulfotransferases and impact of amino acid exchange on Phase II drug metabolism.

Sulfotransferases (SULTs) are Phase II drug-metabolizing enzymes (DMEs) catalyzing the sulfation of a variety of endogenous compounds, natural products, and drugs. Various drugs, such as nonsteroidal anti-inflammatory drugs (NSAIDS) can inhibit SULTs, affecting drug-drug interactions. Several polymorphisms have been identified for SULTs that might be crucial for interindividual variability in drug response and toxicity or for increased disease risk. Here, we review current knowledge on non-synonymous single nucleotide polymorphisms (nsSNPs) of human SULTs, focusing on the coded SULT allozymes and molecular mechanisms explaining their variable activity, which is essential for personalized medicine. We discuss the structural and dynamic bases of key amino acid (AA) variants implicated in the impacts on drug metabolism in the case of SULT1A1, as revealed by molecular modeling approaches.

DNA methylation: Precise modulation of chromatin structure and dynamics.

DNA methylation plays a vital role in epigenetic regulation in both plants and animals, and typically occurs at the 5-carbon position of the cytosine pyrimidine ring within the CpG dinucleotide steps. Cytosine methylation can alter DNA's geometry, mechanical and physico-chemical properties - thus influencing the molecular signaling events vital for transcription, replication and chromatin remodeling. Despite the profound effect cytosine methylation can have on DNA, the underlying atomistic mechanisms remain enigmatic. Many studies so far have produced controversial findings on how cytosine methylation dictates DNA flexibility and accessibility, nucleosome stability and dynamics. Here, we review the most recent experimental and computational studies that provide precise characterization of structure and function of cytosine methylation and its versatile roles in modulating DNA mechanics, nucleosome and chromatin structure, stability and dynamics. Moreover, the review briefly discusses the relationship between DNA methylation and nucleosome positioning, and the crosstalk between DNA methylation and histone tail modifications.

A novel yeast strain Geotrichum sp. CS-67 capable of accumulating heavy metal ions.

Bioremediation, which has several advantages over traditional methods, represents an alternative means of dealing with heavy metal pollution. We screened for microorganisms showing heavy metal tolerance in polluted mangrove soils. A novel yeast, Geotrichum sp. CS-67, was discovered and tested for tolerance of Cu2+, Zn2+, and Ni2+. Zn2+ was the most efficiently sequestered by Geotrichum sp. CS-67 followed by Ni2+ and Cu2+. Zn2+ and Ni2+ were actively taken up into the cell, while Cu2+ was adsorbed to the cell wall. We used RNA-Seq to show that a large number of genes involved in the physiological and biochemical processing of heavy metals were differentially expressed in this yeast when it was subjected to Zn2+ and Ni2+ stress. From this panel, we selected the SED1, GDI1 and ZRT1 genes for validation by qRT-PCR and discovered that, during Zn2+ and Ni2+ stress, SED1 and GDI1 were upregulated, while ZRT1 was downregulated, which was consistent with the RNA-Seq results and the biochemical function of these genes. In conclusion, the novel yeast Geotrichum sp. CS-67 has a marked ability to accumulate heavy metal ions, making it of great interest as a possible microbial agent for heavy metal pollution remediation in the future.

DNA methylation cues in nucleosome geometry, stability and unwrapping.

Cytosine methylation at the 5-carbon position is an essential DNA epigenetic mark in many eukaryotic organisms. Although countless structural and functional studies of cytosine methylation have been reported, our understanding of how it influences the nucleosome assembly, structure, and dynamics remains obscure. Here, we investigate the effects of cytosine methylation at CpG sites on nucleosome dynamics and stability. By applying long molecular dynamics simulations on several microsecond time scale, we generate extensive atomistic conformational ensembles of full nucleosomes. Our results reveal that methylation induces pronounced changes in geometry for both linker and nucleosomal DNA, leading to a more curved, under-twisted DNA, narrowing the adjacent minor grooves, and shifting the population equilibrium of sugar-phosphate backbone geometry. These DNA conformational changes are associated with a considerable enhancement of interactions between methylated DNA and the histone octamer, doubling the number of contacts at some key arginines. H2A and H3 tails play important roles in these interactions, especially for DNA methylated nucleosomes. This, in turn, prevents a spontaneous DNA unwrapping of 3-4 helical turns for the methylated nucleosome with truncated histone tails, otherwise observed in the unmethylated system on several microseconds time scale.

Computational Analysis of Chemical Space of Natural Compounds Interacting with Sulfotransferases.

The aim of this study was to investigate the chemical space and interactions of natural compounds with sulfotransferases (SULTs) using ligand- and structure-based in silico methods. An in-house library of natural ligands (hormones, neurotransmitters, plant-derived compounds and their metabolites) reported to interact with SULTs was created. Their chemical structures and properties were compared to those of compounds of non-natural (synthetic) origin, known to interact with SULTs. The natural ligands interacting with SULTs were further compared to other natural products for which interactions with SULTs were not known. Various descriptors of the molecular structures were calculated and analyzed. Statistical methods (ANOVA, PCA, and clustering) were used to explore the chemical space of the studied compounds. Similarity search between the compounds in the different groups was performed with the ROCS software. The interactions with SULTs were additionally analyzed by docking into different experimental and modeled conformations of SULT1A1. Natural products with potentially strong interactions with SULTs were outlined. Our results contribute to a better understanding of chemical space and interactions of natural compounds with SULT enzymes and help to outline new potential ligands of these enzymes.

Binding of regulatory proteins to nucleosomes is modulated by dynamic histone tails.

Little is known about the roles of histone tails in modulating nucleosomal DNA accessibility and its recognition by other macromolecules. Here we generate extensive atomic level conformational ensembles of histone tails in the context of the full nucleosome, totaling 65 microseconds of molecular dynamics simulations. We observe rapid conformational transitions between tail bound and unbound states, and characterize kinetic and thermodynamic properties of histone tail-DNA interactions. Different histone types exhibit distinct binding modes to specific DNA regions. Using a comprehensive set of experimental nucleosome complexes, we find that the majority of them target mutually exclusive regions with histone tails on nucleosomal/linker DNA around the super-helical locations ± 1, ± 2, and ± 7, and histone tails H3 and H4 contribute most to this process. These findings are explained within competitive binding and tail displacement models. Finally, we demonstrate the crosstalk between different histone tail post-translational modifications and mutations; those which change charge, suppress tail-DNA interactions and enhance histone tail dynamics and DNA accessibility.

SAMPDI-3D: predicting the effects of protein and DNA mutations on protein-DNA interactions.

MOTIVATION: Mutations that alter protein-DNA interactions may be pathogenic and cause diseases. Therefore, it is extremely important to quantify the effect of mutations on protein-DNA binding free energy to reveal the molecular origin of diseases and to assist the development of treatments. Although several methods that predict the change of protein-DNA binding affinity upon mutations in the binding protein were developed, the effect of DNA mutations was not considered yet. RESULTS: Here, we report a new version of SAMPDI, the SAMPDI-3D, which is a gradient boosting decision tree machine learning method to predict the change of the protein-DNA binding free energy caused by mutations in both the binding protein and the bases of the corresponding DNA. The method is shown to achieve Pearson correlation coefficient of 0.76 and 0.80 in a benchmarking test against experimentally determined change of the binding free energy caused by mutations in the binding protein or DNA, respectively. Furthermore, three datasets collected from literature were used to do blind benchmark for SAMPDI-3D and it is shown that it outperforms all existing state-of-the-art methods. The method is very fast allowing for genome-scale investigations. AVAILABILITYAND IMPLEMENTATION: It is available as a web server and a stand-code at http://compbio.clemson.edu/SAMPDI-3D/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Increased p53 signaling impairs neural differentiation in HUWE1-promoted intellectual disabilities.

Essential E3 ubiquitin ligase HUWE1 (HECT, UBA, and WWE domain containing 1) regulates key factors, such as p53. Although mutations in HUWE1 cause heterogenous neurodevelopmental X-linked intellectual disabilities (XLIDs), the disease mechanisms common to these syndromes remain unknown. In this work, we identify p53 signaling as the central process altered in HUWE1-promoted XLID syndromes. By focusing on Juberg-Marsidi syndrome (JMS), one of the severest XLIDs, we show that increased p53 signaling results from p53 accumulation caused by HUWE1 p.G4310R destabilization. This further alters cell-cycle progression and proliferation in JMS cells. Modeling of JMS neurodevelopment reveals majorly impaired neural differentiation accompanied by increased p53 signaling. The neural differentiation defects can be successfully rescued by reducing p53 levels and restoring the expression of p53 target genes, in particular CDKN1A/p21. In summary, our findings suggest that increased p53 signaling underlies HUWE1-promoted syndromes and impairs XLID JMS neural differentiation.

Human Histone Interaction Networks: An Old Concept, New Trends.

To elucidate the properties of human histone interactions on the large scale, we perform a comprehensive mapping of human histone interaction networks by using data from structural, chemical cross-linking and various high-throughput studies. Histone interactomes derived from different data sources show limited overlap and complement each other. It inspires us to integrate these data into the combined histone global interaction network which includes 5308 proteins and 10,330 interactions. The analysis of topological properties of the human histone interactome reveals its scale free behavior and high modularity. Our study of histone binding interfaces uncovers a remarkably high number of residues involved in interactions between histones and non-histone proteins, 80-90% of residues in histones H3 and H4 have at least one binding partner. Two types of histone binding modes are detected: interfaces conserved in most histone variants and variant specific interfaces. Finally, different types of chromatin factors recognize histones in nucleosomes via distinct binding modes, and many of these interfaces utilize acidic patches among other sites. Interaction networks are available at https://github.com/Panchenko-Lab/Human-histone-interactome.

Histone tails as signaling antennas of chromatin.

Histone tails, representing the N-terminal or C-terminal regions flanking the histone core, play essential roles in chromatin signaling networks. Intrinsic disorder of histone tails and their propensity for post-translational modifications allow them to serve as hubs in coordination of epigenetic processes within the nucleosomal context. Deposition of histone variants with distinct histone tail properties further enriches histone tails' repertoire in epigenetic signaling. Given the advances in experimental techniques and in silico modelling, we review the most recent data on histone tails' effects on nucleosome stability and dynamics, their function in regulating chromatin accessibility and folding. Finally, we discuss different molecular mechanisms to understand how histone tails are involved in nucleosome recognition by binding partners and formation of higher-order chromatin structures.

Data sets on human histone interaction networks.

Here, we present the data of human histone interactomes generated and analysed in the research article by Peng et al., 2020 [1]. The histone interactome data provide a comprehensive mapping of human histone/nucleosome interaction networks by using different data sources from the structural, chemical cross-linking, and high-throughput studies. The histone interactions are presented at different levels of granularity in networks, including protein, domain, and residue-levels. All human histone interactome Cytoscape session files are available at https://github.com/Panchenko-Lab/Human-histone-interactome.

Mutations in FAM50A suggest that Armfield XLID syndrome is a spliceosomopathy.

Intellectual disability (ID) is a heterogeneous clinical entity and includes an excess of males who harbor variants on the X-chromosome (XLID). We report rare FAM50A missense variants in the original Armfield XLID syndrome family localized in Xq28 and four additional unrelated males with overlapping features. Our fam50a knockout (KO) zebrafish model exhibits abnormal neurogenesis and craniofacial patterning, and in vivo complementation assays indicate that the patient-derived variants are hypomorphic. RNA sequencing analysis from fam50a KO zebrafish show dysregulation of the transcriptome, with augmented spliceosome mRNAs and depletion of transcripts involved in neurodevelopment. Zebrafish RNA-seq datasets show a preponderance of 3' alternative splicing events in fam50a KO, suggesting a role in the spliceosome C complex. These data are supported with transcriptomic signatures from cell lines derived from affected individuals and FAM50A protein-protein interaction data. In sum, Armfield XLID syndrome is a spliceosomopathy associated with aberrant mRNA processing during development.

Novel Genetic Markers for Early Detection of Elevated Breast Cancer Risk in Women.

This study suggests that two newly discovered variants in the MSH2 gene, which codes for a DNA mismatch repair (MMR) protein, can be associated with a high risk of breast cancer. While variants in the MSH2 gene are known to be linked with an elevated cancer risk, the MSH2 gene is not a part of the standard kit for testing patients for elevated breast cancer risk. Here we used the results of genetic testing of women diagnosed with breast cancer, but who did not have variants in BRCA1 and BRCA2 genes. Instead, the test identified four variants with unknown significance (VUS) in the MSH2 gene. Here, we carried in silico analysis to develop a classifier that can distinguish pathogenic from benign mutations in MSH2 genes taken from ClinVar. The classifier was then used to classify VUS in MSH2 genes, and two of them, p.Ala272Val and p.Met592Val, were predicted to be pathogenic mutations. These two mutations were found in women with breast cancer who did not have mutations in BRCA1 and BRCA2 genes, and thus they are suggested to be considered as new bio-markers for the early detection of elevated breast cancer risk. However, before this is done, an in vitro validation of mutation pathogenicity is needed and, moreover, the presence of these mutations should be demonstrated in a higher number of patients or in families with breast cancer history.

DFMD: Fast and Effective DelPhiForce Steered Molecular Dynamics Approach to Model Ligand Approach Toward a Receptor: Application to Spermine Synthase Enzyme.

Here we report a novel approach, the DelPhiForce Molecular Dynamics (DFMD) method, for steered molecular dynamics simulations to model receptor-ligand association involving charged species. The main purpose of developing DFMD is to simulate ligand's trajectory toward the receptor and thus to predict the "entrance" of the binding pocket and conformational changes associated with the binding. We demonstrate that the DFMD is superior compared with molecular dynamics simulations applying standard cut-offs, provides correct binding forces, allows for modeling the ligand approach at long distances and thus guides the ligand toward the correct binding spot, and it is very fast (frequently the binding is completed in <1 ns). The DFMD is applied to model the binding of two ligands to a receptor (spermine synthase) and it is demonstrated that it guides the ligands toward the corresponding pockets despite of the initial ligand's position with respect to the receptor. Predicted conformational changes and the order of ligand binding are experimentally verified.