Lambda CI Binding to Related Phage Operator Sequences Validates Alignment Algorithm and Highlights the Importance of Overlooked Bonds

Bacteriophage λ's CI repressor protein controls a genetic switch between the virus's lysogenic and lytic lifecycles, in part, by selectively binding to six different DNA sequences within the phage genome-collectively referred to as operator sites. However, the minimal level of information needed for CI to recognize and specifically bind these six unique-but-related sequences is unclear. In a previous study, we introduced an algorithm that extracts the minimal direct readout information needed for λ-CI to recognize and bind its six binding sites. We further revealed direct readout information shared among three evolutionarily related lambdoid phages: λ-phage, Enterobacteria phage VT2-Sakai, and Stx2 converting phage I, suggesting that the λ-CI protein could bind to the operator sites of these other phages. In this study, we show that λ-CI can indeed bind the other two phages' cognate binding sites as predicted using our algorithm, validating the hypotheses from that paper. We go on to demonstrate the importance of specific hydrogen bond donors and acceptors that are maintained despite changes to the nucleobase itself, and another that has an important role in recognition and binding. This in vitro validation of our algorithm supports its use as a tool to predict alternative binding sites for DNA-binding proteins.

Atomic Force Microscopy of DNA and DNA-Protein Interactions

Atomic force microscopy (AFM) is a microscopy technique that uses a sharp probe to trace a sample surface at nanometer resolution. For biological applications, one of its key advantages is its ability to visualize the substructure of single molecules and molecular complexes in an aqueous environment. Here, we describe the application of AFM to determine the secondary and tertiary structure of surface-bound DNA, and its interactions with proteins.

SAResNet: self-attention residual network for predicting DNA-protein binding

Knowledge of the specificity of DNA-protein binding is crucial for understanding the mechanisms of gene expression, regulation and gene therapy. In recent years, deep-learning-based methods for predicting DNA-protein binding from sequence data have achieved significant success. Nevertheless, the current state-of-the-art computational methods have some drawbacks associated with the use of limited datasets with insufficient experimental data. To address this, we propose a novel transfer learning-based method, termed SAResNet, which combines the self-attention mechanism and residual network structure. More specifically, the attention-driven module captures the position information of the sequence, while the residual network structure guarantees that the high-level features of the binding site can be extracted. Meanwhile, the pre-training strategy used by SAResNet improves the learning ability of the network and accelerates the convergence speed of the network during transfer learning. The performance of SAResNet is extensively tested on 690 datasets from the ChIP-seq experiments with an average AUC of 92.0%, which is 4.4% higher than that of the best state-of-the-art method currently available. When tested on smaller datasets, the predictive performance is more clearly improved. Overall, we demonstrate that the superior performance of DNA-protein binding prediction on DNA sequences can be achieved by combining the attention mechanism and residual structure, and a novel pipeline is accordingly developed. The proposed methodology is generally applicable and can be used to address any other sequence classification problems.

C-terminal truncation of α-synuclein alters DNA structure from extension to compaction

Parkinson's disease (PD) is linked to aggregation of the protein α-synuclein (aS) into amyloid fibers. aS is proposed to regulate synaptic activity and may also play a role in gene regulation via interaction with DNA in the cell nucleus. Here, we address the role of the negatively-charged C-terminus in the interaction between aS and DNA using single-molecule techniques. Using nanofluidic channels, we demonstrate that truncation of the C-terminus of aS induces differential effects on DNA depending on the extent of the truncation. The DNA extension increases for full-length aS and the (1-119)aS variant, but decreases about 25% upon binding to the (1-97)aS variant. Atomic force microscopy imaging showed full protein coverage of the DNA at high aS concentration. The characterization of biophysical properties of DNA when in complex with aS variants may provide important insights into the role of such interactions in PD, especially since C-terminal aS truncations have been found in clinical samples from PD patients.

Using Chou's 5-Step Rule to Predict DNA-Protein Binding with Multi-scale Complementary Feature

It is well known that DNA-protein binding (DPB) prediction is not only beneficial to understand the regulation mechanism of gene expression but also a challenging task in the field of computational biology. Traditional methods for DPB prediction that depend on manually extracted features may lead to classification errors. Recently, deep learning such as convolutional neural network (CNN) has been successfully applied to classification tasks and improved DPB prediction performance significantly. Yet, these methods are based on the original DNA sequence modeling, ignoring the hidden complex dependency and complementarity between multiple sequence features. In consideration of this problem, we propose a method to fuse different sequence features and analyze them systematically through multi-scale CNN. First, sliding windows of specified lengths are set on distinct DNA sequences to generate multiple sequence features with unequal lengths. Second, multiple feature sequences are fused and encoded for feature representation. Third, multi-scale CNN with different binding motif lengths is used to automatically learn and mine the influence of internal attributes and hidden complex relations between the fusion sequence features and make full use of the complementary advantages of extracted CNN features to predict DPB. When our model is applied to 690 ChIP-seq datasets, it achieves an average AUC of 0.9112, which is significantly better than the latest methods. The results show that our method is effective for DPB prediction and is freely available at http://121.5.71.120/mscDPB/.

Functional Analysis of DNMT3A DNA Methyltransferase Mutations Reported in Patients with Acute Myeloid Leukemia

In mammals, DNA methylation is necessary for the maintenance of genomic stability, gene expression regulation, and other processes. During malignant diseases progression, changes in both DNA methylation patterns and DNA methyltransferase (MTase) genes are observed. Human de novo MTase DNMT3A is most frequently mutated in acute myeloid leukemia (AML) with a striking prevalence of R882H mutation, which has been extensively studied. Here, we investigate the functional role of the missense mutations (S714C, R635W, R736H, R771L, P777R, and F752V) found in the catalytic domain of DNMT3A in AML patients. These were accordingly mutated in the murine Dnmt3a catalytic domain (S124C, R45W, R146H, R181L, P187R, and F162V) and in addition, one-site CpG-containing DNA substrates were used as a model system. The 3–15-fold decrease (S124C and P187R) or complete loss (F162V, R45W, and R146H) of Dnmt3a-CD methylation activity was observed. Remarkably, Pro 187 and Arg 146 are not located at or near the Dnmt3a functional motives. Regulatory protein Dnmt3L did not enhance the methylation activity of R45W, R146H, P187R, and F162V mutants. The key steps of the Dnmt3a-mediated methylation mechanism, including DNA binding and transient covalent intermediate formation, were examined. There was a complete loss of DNA-binding affinity for R45W located in the AdoMet binding region and for R146H. Dnmt3a mutants studied in vitro suggest functional impairment of DNMT3A during pathogenesis.

Diastereomeric Recognition of 5',8-cyclo-2'-Deoxyadenosine Lesions by Human Poly(ADP-ribose) Polymerase 1 in a Biomimetic Model

5’,8-Cyclo-2’-deoxyadenosine (cdA), in the 5’R and 5’Sdiastereomeric forms, are typical non strand-break oxidative DNA lesions, induced by hydroxyl radicals, with emerging importance as a molecular marker. These lesions are exclusively repaired by the nucleotide excision repair (NER) mechanism with a low efficiency, thus readily accumulating in the genome. Poly(ADP-ribose) polymerase1 (PARP1) acts as an early responder to DNA damage and plays a key role as a nick sensor in the maintenance of the integrity of the genome by recognizing nicked DNA. So far, it was unknown whether the two diastereomeric cdA lesions could induce specific PARP1 binding. Here, we provide the first evidence of PARP1 to selectively recognize the diastereomeric lesions of 5’S-cdA and 5’R-cdA in vitro as compared to deoxyadenosine in model DNA substrates (23-mers) by using circular dichroism, fluorescence spectroscopy, immunoblotting analysis, and gel mobility shift assay. Several features of the recognition of the damaged and undamaged oligonucleotides by PARP1 were characterized. Remarkably, PARP1 exhibits different affinities in binding to a double strand (ds) oligonucleotide, which incorporates cdA lesions in R and S diastereomeric form. In particular, PARP1 proved to bind oligonucleotides, including a 5’S-cdA, with a higher affinity constant for the 5’S lesion in a model of ds DNA than 5’R-cdA, showing different recognition patterns, also compared with undamaged dA. This new finding highlights the ability of PARP1 to recognize and differentiate the distorted DNA backbone in a biomimetic system caused by different diastereomeric forms of a cdA lesion.

[Identification of Distinct Amino Acid Composition of Human Cruciform Binding Proteins]

Cruciform structures are preferential targets for many architectural and regulatory proteins, as well as a number of DNA binding proteins with weak sequence specificity. Some of these proteins are also capable of inducing the formation of cruciform structures upon DNA binding. In this paper we analyzed the amino acid composition of eighteen cruciform binding proteins of Homo sapiens. Comparison with general amino acid frequencies in all human proteins revealed unique differences, with notable enrichment for lysine and serine and/or depletion for alanine, glycine, glutamine, arginine, tyrosine and tryptophan residues. Based on bootstrap resampling and fuzzy cluster analysis, multiple molecular mechanisms of interaction with cruciform DNA structures could be suggested, including those involved in DNA repair, transcription and chromatin regulation. The proteins DEK, HMGB1 and TOP1 in particular formed a very distinctive group. Nonetheless, a strong interaction network connecting nearly all the cruciform binding proteins studied was demonstrated. Data reported here will be very useful for future prediction of new cruciform binding proteins or even construction of predictive tool/web-based application.

An Enzyme-Linked Aptamer Sorbent Assay to Evaluate Aptamer Binding

Nucleic acid aptamers are a class of alternative ligands increasingly growing in importance in the face of contemporary detection challenges. Aptamers offer multiple advantages over traditional ligands like antibodies; however, their ability to specifically bind target molecules must first be confirmed after their generation. Use of a plate-based enzyme-linked aptamer sorbent assay (ELASA) is a generally rapid way to screen and characterize aptamer binding to protein targets. ELASA involves directly plating a protein target onto a nonspecific (polystyrene) surface and assessing binding of functionalized (biotinylated) aptamers to those plated proteins using an enzyme conjugate that recognizes the aptamers. Here, we describe an ELASA that was designed and used to evaluate and compare binding of ssDNA aptamers against the capsids of different strains of human norovirus.

In vitro affinity of Deinococcus radiodurans MutS towards mismatched DNA exceeds that of its orthologues from Escherichia coli and Thermus thermophilus

The mismatch binding protein MutS is responsible for the recognition of mispaired and unpaired bases, which is the initial step in DNA repair. Among the MutS proteins most extensively studied in vitro are those derived from Thermus thermophilus, Thermus aquaticus and Escherichia coli. Here, we present the first report on the in vitro examination of DNA mismatch binding activity of MutS protein from Deinococcus radiodurans and confront this with the properties of those from E. coli and T. thermophilus. The analyses which included mobility gel-shift assay, colorimetric and qPCR estimation of MutS-bound DNA clearly showed that D. radiodurans MutS exhibited much higher affinity towards mismatched DNA in vitro than its counterparts from E. coli and T. thermophilus. In addition, D. radiodurans MutS displayed a significantly higher specificity of DNA mismatch binding than the two other orthologues. The specificity expressed as the ratio of mismatched to fully complementary DNA bound reached over 4 and 20-fold higher values for D. radiodurans than for T. thermophilus and E. coli MutS, respectively. The results demonstrate mainly the biotechnological potential of D. radiodurans MutS but the in vitro characteristics of the MutS orthologues could reflect substantial differences in DNA mismatch binding activities existing in vivo.

An Improved Method for Identifying Specific DNA-Protein-Binding Sites In Vitro

Binding of proteins to specific DNA sequences is essential for a variety of cellular processes such as DNA replication, transcription and responses to external stimuli. Chromatin immunoprecipitation is widely used for determining intracellular DNA fragments bound by a specific protein. However, the subsequent specific or accurate DNA-protein-binding sequence is usually determined by DNA footprinting. Here, we report an alternative method for identifying specific sites of DNA-protein-binding (designated SSDP) in vitro. This technique is mainly dependent on antibody-antigen immunity, simple and convenient, while radioactive isotope labeling and optimization of partial degradation by deoxyribonuclease (DNase) are avoided. As an example, the specific binding sequence of a target promoter by DdrO (a DNA damage response protein from Deinococcus radiodurans) in vitro was determined by the developed method. The central sequence of the binding site could be easily located using this technique.

Nucleosome positioning: resources and tools online

Nucleosome positioning is an important process required for proper genome packing and its accessibility to execute the genetic program in a cell-specific, timely manner. In the recent years hundreds of papers have been devoted to the bioinformatics, physics and biology of nucleosome positioning. The purpose of this review is to cover a practical aspect of this field, namely, to provide a guide to the multitude of nucleosome positioning resources available online. These include almost 300 experimental datasets of genome-wide nucleosome occupancy profiles determined in different cell types and more than 40 computational tools for the analysis of experimental nucleosome positioning data and prediction of intrinsic nucleosome formation probabilities from the DNA sequence. A manually curated, up to date list of these resources will be maintained at http://generegulation.info.