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To bring new extrachromosomal circular DNA (eccDNA) enrichment technologies closer to the clinic, specifically for screening, early diagnosis, and monitoring of diseases or lifestyle conditions, it is paramount to identify the differential pattern of the genic eccDNA signal between two states. Current studies using short-read sequenced purified eccDNA data are based on absolute numbers of unique eccDNAs per sample or per gene, length distributions, or standard methods for RNA-seq differential analysis. Previous analyses of RNA-seq data found significant transcriptomics difference between sedentary and active life style skeletal muscle (SkM) in young people but very few in old. The first attempt using circulomics data from SkM and blood of aged lifelong sedentary and physically active males found no difference at eccDNA level. To improve the capability of finding differences between circulomics data groups, we designed a computational method to identify Differentially Produced per Gene Circles (DPpGCs) from short-read sequenced purified eccDNA data based on the circular junction, split-read signal, of the eccDNA, and implemented it into a software tool DifCir in Matlab. We employed DifCir to find to the distinctive features of the influence of the physical activity or inactivity in the aged SkM that would have remained undetected by transcriptomics methods. We mapped the data from tissue from SkM and blood from two groups of aged lifelong sedentary and physically active males using Circle_finder and subsequent merging and filtering, to find the number and length distribution of the unique eccDNA. Next, we used DifCir to find up-DPpGCs in the SkM of the sedentary and active groups. We assessed the functional enrichment of the DPpGCs using Disease Gene Network and Gene Set Enrichment Analysis. To find genes that produce eccDNA in a group without comparison with another group, we introduced a method to find Common PpGCs (CPpGCs) and used it to find CPpGCs in the SkM of the sedentary and active group. Finally, we found the eccDNA that carries whole genes. We discovered that the eccDNA in the SkM of the sedentary group is not statistically different from that of physically active aged men in terms of number and length distribution of eccDNA. In contrast, with DifCir we found distinctive gene-associated eccDNA fingerprints. We identified statistically significant up-DPpGCs in the two groups, with the top up-DPpGCs shed by the genes AGBL4 , RNF213 , DNAH7 , MED13 , and WWTR1 in the sedentary group, and ZBTB7C , TBCD , ITPR2 , and DDX11-AS1 in the active group. The up-DPpGCs in both groups carry mostly gene fragments rather than whole genes. Though the subtle transcriptomics difference, we found RYR1 to be both transcriptionally up-regulated and up-DPpGCs gene in sedentary SkM. DifCir emphasizes the high sensitivity of the circulome compared to the transcriptome to detect the molecular fingerprints of exercise in aged SkM. It allows efficient identification of gene hotspots that excise more eccDNA in a health state or disease compared to a control condition.

Urinary DNA is increasingly gaining importance in diagnosis of urological malignancies. Especially cell-free DNA originating from apoptotic and necrotic cells of the early tumor could become a key target for early stage tumor diagnosis. Aberrant DNA methylation forms tumor cell characteristic epigenetic profiles which are covalently established before any tumor related aberration at transcriptional or protein level has occurred. In addition, these epigenetic signatures are alterably adapted to and accompanying the individual stages of multistep, progressive tumorigenesis. Hence, they seem very promising for diagnosis as well as for monitoring the patient's follow-up care and even for decisions regarding personalized therapeutic options. The essential prerequisite at this approach will be a reliable methodological handling of the biological material of interest. In this study we present detailed analyses of LINE-1 DNA methylation profiles and demonstrate the sensitive detection of LINE-1 DNA methylation differences as well as between cancer patients and healthy individuals, between urinary cellular and cell-free DNA. In addition, we show methylome differences between both DNA fractions from a healthy individual and bladder cancer patients. In conclusion, we demonstrate here the unrestricted amenability of urinary cell-free DNA for both, a detailed characterization of a distinct DNA methylation alteration and its sensitive detection and a comprehensive global, array-based screening for DNA methylation differences.

Terminally differentiated cells can be reprogrammed to pluripotency by the forced expression of Oct4, Sox2, Klf4 and c-Myc. However, it remains unknown how this leads to the multitude of epigenetic changes observed during the reprogramming process. Interestingly, Oct4 is the only factor that cannot be replaced by other members of the same family to induce pluripotency. To understand the unique role of Oct4 in reprogramming, we determined the structure of its POU domain bound to DNA. We show that the linker between the two DNA-binding domains is structured as an α-helix and exposed to the protein's surface, in contrast to the unstructured linker of Oct1. Point mutations in this α-helix alter or abolish the reprogramming activity of Oct4, but do not affect its other fundamental properties. On the basis of mass spectrometry studies of the interactome of wild-type and mutant Oct4, we propose that the linker functions as a protein-protein interaction interface and plays a crucial role during reprogramming by recruiting key epigenetic players to Oct4 target genes. Thus, we provide molecular insights to explain how Oct4 contributes to the reprogramming process.

DNA-binding drugs have numerous applications in the engineered gene regulation. However, the drug-DNA recognition mechanism is poorly understood. Drugs can recognize specific DNA sequences not only through direct contacts but also indirectly through sequence-dependent conformation, in a similar manner to the indirect readout mechanism in protein-DNA recognition. We used a knowledge-based technique that takes advantage of known DNA structures to evaluate the conformational energies. We built a dataset of non-redundant free B-DNA crystal structures to calculate the distributions of adjacent base-step and base-pair conformations, and estimated the effective harmonic potentials of mean force (PMF). These PMFs were used to calculate the conformational energy of drug-DNA complexes, and the Z-score as a measure of the binding specificity. Comparing the Z-scores for drug-DNA complexes with those for free DNA structures with the same sequence, we observed that in several cases the Z-scores became more negative upon drug binding. Furthermore, the specificity is position-dependent within the drug-bound region of DNA. These results suggest that DNA conformation plays an important role in the drug-DNA recognition. The presented method provides a tool for the analysis of drug-DNA recognition and can facilitate the development of drugs for targeting a specific DNA sequence.

Protein-DNA interactions play a central role in regulatory processes at the genetic level. DNA-binding proteins recognize their targets by direct base-amino acid interactions and indirect conformational energy contribution from DNA deformations and elasticity. Knowledge-based approach based on the statistical analysis of protein-DNA complex structures has been successfully used to calculate interaction energies and specificities of direct and indirect readouts in protein-DNA recognition. Here, we have implemented the method as a webserver, which calculates direct and indirect readout energies and Z-scores, as a measure of specificity, using atomic coordinates of protein-DNA complexes. This server is freely available at http://gibk26.bse.kyutech.ac.jp/jouhou/readout/. The only input to this webserver is the Protein Data Bank (PDB) style coordinate data of atoms or the PDB code itself. The server returns total energy Z-scores, which estimate the degree of sequence specificity of the protein-DNA complex. This webserver is expected to be useful for estimating interaction energy and DNA conformation energy, and relative contributions to the specificity from direct and indirect readout. It may also be useful for checking the quality of protein-DNA complex structures, and for engineering proteins and target DNAs.

Sequence dependence of DNA conformation plays a crucial role in its recognition by proteins and ligands. To clarify the relationship between sequence and conformation, it is necessary to quantify the conformational energy and specificity of DNA. Here, we make a systematic analysis of dodecamer DNA structures including all the 136 unique tetranucleotide sequences at the center by molecular dynamics simulations. Using a simplified conformational model with six parameters to describe the geometry of adjacent base pairs and harmonic potentials along these coordinates, we estimated the equilibrium conformational parameters and the harmonic potentials of mean force for the central base-pair steps from many trajectories of the simulations. This enabled us to estimate the conformational energy and the specificity for any given DNA sequence and structure. We tested our method by using sequence-structure threading to estimate the conformational energy and the Z-score as a measure of specificity for many B-DNA and A-DNA crystal structures. The average Z-scores were negative for both kinds of structures, indicating that the potential of mean force from the simulation is capable of predicting sequence specificity for the crystal structures and that it may be used to study the sequence specificity of both types of DNA. We also estimated the positional distribution of conformational energy and Z-score within DNA and showed that they are strongly position dependent. This analysis enabled us to identify particular conformations responsible for the specificity. The presented results will provide an insight into the mechanisms of DNA sequence recognition by proteins and ligands.

A simple knowledge-based method for DNA atomic structure prediction from nucleic sequence is presented. We used free B-DNA crystal structures to estimate the distribution of trinucleotide base pairs and tetranucleotide base-pair steps conformational coordinates. We used these distributions as a basis to predict the 3D position of the non-hydrogen atoms of the nucleic bases of any arbitrary DNA sequence of any length. The only constraint imposed was that the structure is a B-DNA one with Watson-Crick complementary base pairs. The method was tested on not seen DNA structures with sequence lengths varying from 6bp to 12bp. The obtained predictions have RMSE around 0.5 A for the translational conformational coordinates, and around 5 degrees for the rotational. For the estimation of the nucleic base non-hydrogen atom coordinates the RMSE is around 1.1 A. The knowledge-based method outperformed a technique based on genetic algorithms in the prediction of B-DNA structures.

Cell-free (cf) extrachromosomal circular DNA (eccDNA) has a potential clinical application as a biomarker. Systemic lupus erythematosus (SLE) is a systemic autoimmune disease with a complex immunological pathogenesis, associated with autoantibody synthesis. A previous study found that SLE patients with deoxyribonuclease 1-like 3 (DNASE1L3) deficiency exhibit changes in the frequency of short and long eccDNA in plasma compared to controls. Here, using the DifCir method for differential analysis of short-read sequenced purified eccDNA data based on the split-read signal of the eccDNA on circulomics data, we show that SLE patients with DNASE1L3 deficiency have a distinctive profile of eccDNA excised by gene regions compared to controls. Moreover, this profile is specific; cf-eccDNA from the top 93 genes is detected in all SLE with DNASE1L3 deficiency samples, and none in the control plasma. The top protein coding gene producing eccDNA-carrying gene fragments is the transcription factor BARX2, which is involved in skeletal muscle morphogenesis and connective tissue development. The top gene ontology terms are 'positive regulation of torc1 signaling' and 'chondrocyte development'. The top Harmonizome terms are 'lymphopenia', 'metabolic syndrome x', 'asthma', 'cardiovascular system disease', 'leukemia', and 'immune system disease'. Here, we show that gene associations of cf-eccDNA can serve as a biomarker in the autoimmune rheumatic diseases. [ABSTRACT FROM AUTHOR]

With approximately 1.4 million men annually diagnosed with prostate cancer (PCa) worldwide, PCa remains a dreaded threat to life and source of devastating morbidity. In recent decades, a significant decrease in age-specific PCa mortality has been achieved by increasing prostate-specific antigen (PSA) screening and improving treatments. Nevertheless, upcoming, augmented recommendations against PSA screening underline an escalating disproportion between the benefit and harm of current diagnosis/prognosis and application of radical treatment standards. Undoubtedly, new potent diagnostic and prognostic tools are urgently needed to alleviate this tensed situation. They should allow a more reliable early assessment of the upcoming threat, in order to enable applying timely adjusted and personalized therapy and monitoring. Here, we present a basic study on an epigenetic screening approach by Methylated DNA Immunoprecipitation (MeDIP). We identified genes associated with hypomethylated CpG islands in three PCa sample cohorts. By adjusting our computational biology analyses to focus on single CpG-enriched 60-nucleotide-long DNA probes, we revealed numerous consistently differential methylated DNA segments in PCa. They were associated among other genes with NOTCH3, CDK2AP1, KLK4, and ADAM15. These can be used for early discrimination, and might contribute to a new epigenetic tumor classification system of PCa. Our analysis shows that we can dissect short, differential methylated CpG-rich DNA fragments and combinations of them that are consistently present in all tumors. We name them tumor cell-specific differential methylated CpG dinucleotide signatures (TUMS). [ABSTRACT FROM AUTHOR]

Many of the structural and mechanistic requirements of oocyte-mediated nuclear reprogramming remain elusive. Previous accounts that transcriptional reprogramming of somatic nuclei in mouse zygotes may be complete in 24–36 hours, far more rapidly than in other reprogramming systems, raise the question of whether the mere exposure to the activated mouse ooplasm is sufficient to enact reprogramming in a nucleus. We therefore prevented DNA replication and cytokinesis, which ensue after nuclear transfer, in order to assess their requirement for transcriptional reprogramming of the key pluripotency genes Oct4 (Pou5f1) and Nanog in cloned mouse embryos. Using transcriptome and allele-specific analysis, we observed that hundreds of mRNAs, but not Oct4 and Nanog, became elevated in nucleus-transplanted oocytes without DNA replication. Progression through the first round of DNA replication was essential but not sufficient for transcriptional reprogramming of Oct4 and Nanog, whereas cytokinesis and thereby cell-cell interactions were dispensable for transcriptional reprogramming. Responses similar to clones also were observed in embryos produced by fertilization in vitro. Our results link the occurrence of reprogramming to a previously unappreciated requirement of oocyte-mediated nuclear reprogramming, namely DNA replication. Nuclear transfer alone affords no immediate transition from a somatic to a pluripotent gene expression pattern unless DNA replication is also in place. This study is therefore a resource to appreciate that the quest for always faster reprogramming methods may collide with a limit that is dictated by the cell cycle. [ABSTRACT FROM AUTHOR]

Simple Summary: A diagnostic biomarker for the detection of breast cancer remains an unmet clinical need despite decades of intensive research efforts. Herein, we describe, for the first time, the use of nuclease activity as a biomarker to discriminate between healthy and cancer biopsy samples. We have identified a panel of three nucleic acid probes able to target nucleases derived from breast cancer tumors with high sensitivity and specificity. These results are in good agreement with histopathological analysis as the diagnostic gold standard. Moreover, these findings support nuclease activity as a potential adjacent diagnostic tool and shed light on the use of nuclease activity as a detection biomarker in breast cancer. Breast cancer is one of the most common pathologies diagnosed in the clinical practice. Despite major advancements in diagnostic approaches, there is no widely accepted biomarker in the clinical practice that can diagnose breast malignancy. Confirmatory diagnosis still relies on the pathological assessment of tissue biopsies by expert pathologists. Thus, there is an unmet need for new types of biomarkers and novel platform technologies that can be easily and robustly integrated into the clinic and that can assist pathologists. Herein, we show that nuclease activity associated to malignant tumors can be used as a novel biomarker in breast cancer, which can be detected via specific degradation of nucleic acid probes. In this study we have identified a set of three chemically modified nucleic acid probes that can diagnose malignancy in biopsy samples with high accuracy (89%), sensitivity (82%) and specificity (94%). This work represents a breakthrough for the potential clinical use of nuclease activity as biomarker, which can be detected via nucleic acids probes, for the clinical diagnosis of malignancy in breast tissue biopsies. This platform technology could be readily implemented into the clinic as adjunct to histopathological diagnostic. [ABSTRACT FROM AUTHOR]

The transcription factors OCT4 and SOX2 are required for generating induced pluripotent stem cells (iPSCs) and for maintaining embryonic stem cells (ESCs). OCT4 and SOX2 associate and bind to DNA in different configurations depending on the arrangement of their individual DNA binding elements. Here we have investigated the role of the different OCT4-SOX2-DNA assemblies in regulating and inducing pluripotency. To this end, we have generated SOX2 mutants that interfere with specific OCT4-SOX2 heterodimer configurations and assessed their ability to generate iPSCs and to rescue ESC self-renewal. Our results demonstrate that the OCT4-SOX2 configuration that dimerizes on a Hoxb1-like composite, a canonical element with juxtaposed individual binding sites, plays a more critical role in the induction and maintenance of pluripotency than any other OCT4-SOX2 configuration. Overall, the results of this study provide new insight into the protein interactions required to establish a de novo pluripotent network and to maintain a true pluripotent cell fate. [ABSTRACT FROM AUTHOR]