Investigating the antibacterial mechanism of Ampelopsis cantoniensis extracts against methicillin-resistant Staphylococcus aureus via in vitro and in silico analysis.

Methicillin-resistant Staphylococcus aureus (MRSA) is a critical pathogen responsible for a wide variety of serious infectious diseases in humans. The accelerated phenomena of drug tolerance, drug resistance, and dysbacteriosis provoked by antibiotic misuse are impeding the effectiveness of contemporary antibiotic therapies primarily used to treat this common worldwide pathogen. In this study, the antibacterial activity of 70% ethanol extract and multiple polar solvents of Ampelopsis cantoniensis were measured against the clinical MRSA isolate. The agar diffusion technique was employed to determine the zone of inhibition (ZOI), accompanied by the use of a microdilution series to identify the minimal inhibitory concentration (MIC) and minimal bactericidal concentration (MBC). Our results revealed that the ethyl acetate fraction exhibited the most significant antibacterial activity, which was determined to be bacteriostatic based on the MBC/MIC ratio 8. A list of compounds isolated from A. cantoniensis was computationally studied to further investigate the mechanism of action with the bacterial membrane protein PBP2a. The combination of molecular docking and molecular dynamics methods showed that the main compound, dihydromyricetin (DHM), is expected to bind to PBP2a at allosteric site. In addition, DHM was identified as the major compound of ethyl acetate fraction, which accounts for 77.03 ± 2.44% by high performance liquid chromatography (HPLC) analysis. As a concluding remark, our study addressed the antibacterial mechanism and suggested the prioritization of natural products derived from A. cantoniensis as a potential therapy for MRSA.Communicated by Ramaswamy H. Sarma.

Developmental chromatin programs determine oncogenic competence in melanoma.

Oncogenes only transform cells under certain cellular contexts, a phenomenon called oncogenic competence. Using a combination of a human pluripotent stem cell­derived cancer model along with zebrafish transgenesis, we demonstrate that the transforming ability of BRAFV600E along with additional mutations depends on the intrinsic transcriptional program present in the cell of origin. In both systems, melanocytes are less responsive to mutations, whereas both neural crest and melanoblast populations are readily transformed. Profiling reveals that progenitors have higher expression of chromatin-modifying enzymes such as ATAD2, a melanoma competence factor that forms a complex with SOX10 and allows for expression of downstream oncogenic and neural crest programs. These data suggest that oncogenic competence is mediated by regulation of developmental chromatin factors, which then allow for proper response to those oncogenes.

Whole-genome characterization of lung adenocarcinomas lacking the RTK/RAS/RAF pathway.

RTK/RAS/RAF pathway alterations (RPAs) are a hallmark of lung adenocarcinoma (LUAD). In this study, we use whole-genome sequencing (WGS) of 85 cases found to be RPA(-) by previous studies from The Cancer Genome Atlas (TCGA) to characterize the minority of LUADs lacking apparent alterations in this pathway. We show that WGS analysis uncovers RPA(+) in 28 (33%) of the 85 samples. Among the remaining 57 cases, we observe focal deletions targeting the promoter or transcription start site of STK11 (n = 7) or KEAP1 (n = 3), and promoter mutations associated with the increased expression of ILF2 (n = 6). We also identify complex structural variations associated with high-level copy number amplifications. Moreover, an enrichment of focal deletions is found in TP53 mutant cases. Our results indicate that RPA(-) cases demonstrate tumor suppressor deletions and genome instability, but lack unique or recurrent genetic lesions compensating for the lack of RPAs. Larger WGS studies of RPA(-) cases are required to understand this important LUAD subset.

DeepMILO: a deep learning approach to predict the impact of non-coding sequence variants on 3D chromatin structure.

Non-coding variants have been shown to be related to disease by alteration of 3D genome structures. We propose a deep learning method, DeepMILO, to predict the effects of variants on CTCF/cohesin-mediated insulator loops. Application of DeepMILO on variants from whole-genome sequences of 1834 patients of twelve cancer types revealed 672 insulator loops disrupted in at least 10% of patients. Our results show mutations at loop anchors are associated with upregulation of the cancer driver genes BCL2 and MYC in malignant lymphoma thus pointing to a possible new mechanism for their dysregulation via alteration of insulator loops.

Spatial Genome Re-organization between Fetal and Adult Hematopoietic Stem Cells.

Fetal hematopoietic stem cells (HSCs) undergo a developmental switch to become adult HSCs with distinct functional properties. To better understand the molecular mechanisms underlying the developmental switch, we have conducted deep sequencing of the 3D genome, epigenome, and transcriptome of fetal and adult HSCs in mouse. We find that chromosomal compartments and topologically associating domains (TADs) are largely conserved between fetal and adult HSCs. However, there is a global trend of increased compartmentalization and TAD boundary strength in adult HSCs. In contrast, intra-TAD chromatin interactions are much more dynamic and widespread, involving over a thousand gene promoters and distal enhancers. These developmental-stage-specific enhancer-promoter interactions are mediated by different sets of transcription factors, such as TCF3 and MAFB in fetal HSCs, versus NR4A1 and GATA3 in adult HSCs. Loss-of-function studies of TCF3 confirm the role of TCF3 in mediating condition-specific enhancer-promoter interactions and gene regulation in fetal HSCs.

Hierarchical Reconstruction of High-Resolution 3D Models of Large Chromosomes.

Eukaryotic chromosomes are often composed of components organized into multiple scales, such as nucleosomes, chromatin fibers, topologically associated domains (TAD), chromosome compartments, and chromosome territories. Therefore, reconstructing detailed 3D models of chromosomes in high resolution is useful for advancing genome research. However, the task of constructing quality high-resolution 3D models is still challenging with existing methods. Hence, we designed a hierarchical algorithm, called Hierarchical3DGenome, to reconstruct 3D chromosome models at high resolution (<=5 Kilobase (KB)). The algorithm first reconstructs high-resolution 3D models at TAD level. The TAD models are then assembled to form complete high-resolution chromosomal models. The assembly of TAD models is guided by a complete low-resolution chromosome model. The algorithm is successfully used to reconstruct 3D chromosome models at 5 KB resolution for the human B-cell (GM12878). These high-resolution models satisfy Hi-C chromosomal contacts well and are consistent with models built at lower (i.e. 1 MB) resolution, and with the data of fluorescent in situ hybridization experiments. The Java source code of Hierarchical3DGenome and its user manual are available here https://github.com/BDM-Lab/Hierarchical3DGenome .

GenomeFlow: a comprehensive graphical tool for modeling and analyzing 3D genome structure.

MOTIVATION: Three-dimensional (3D) genome organization plays important functional roles in cells. User-friendly tools for reconstructing 3D genome models from chromosomal conformation capturing data and analyzing them are needed for the study of 3D genome organization. RESULTS: We built a comprehensive graphical tool (GenomeFlow) to facilitate the entire process of modeling and analysis of 3D genome organization. This process includes the mapping of Hi-C data to one-dimensional (1D) reference genomes, the generation, normalization and visualization of two-dimensional (2D) chromosomal contact maps, the reconstruction and the visualization of the 3D models of chromosome and genome, the analysis of 3D models and the integration of these models with functional genomics data. This graphical tool is the first of its kind in reconstructing, storing, analyzing and annotating 3D genome models. It can reconstruct 3D genome models from Hi-C data and visualize them in real-time. This tool also allows users to overlay gene annotation, gene expression data and genome methylation data on top of 3D genome models. AVAILABILITY AND IMPLEMENTATION: The source code and user manual: https://github.com/jianlin-cheng/GenomeFlow. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

3D genome structure modeling by Lorentzian objective function.

The 3D structure of the genome plays a vital role in biological processes such as gene interaction, gene regulation, DNA replication and genome methylation. Advanced chromosomal conformation capture techniques, such as Hi-C and tethered conformation capture, can generate chromosomal contact data that can be used to computationally reconstruct 3D structures of the genome. We developed a novel restraint-based method that is capable of reconstructing 3D genome structures utilizing both intra-and inter-chromosomal contact data. Our method was robust to noise and performed well in comparison with a panel of existing methods on a controlled simulated data set. On a real Hi-C data set of the human genome, our method produced chromosome and genome structures that are consistent with 3D FISH data and known knowledge about the human chromosome and genome, such as, chromosome territories and the cluster of small chromosomes in the nucleus center with the exception of the chromosome 18. The tool and experimental data are available at https://missouri.box.com/v/LorDG.

Chromosome3D: reconstructing three-dimensional chromosomal structures from Hi-C interaction frequency data using distance geometry simulated annealing.

BACKGROUND: Reconstructing three-dimensional structures of chromosomes is useful for visualizing their shapes in a cell and interpreting their function. In this work, we reconstruct chromosomal structures from Hi-C data by translating contact counts in Hi-C data into Euclidean distances between chromosomal regions and then satisfying these distances using a structure reconstruction method rigorously tested in the field of protein structure determination. RESULTS: We first evaluate the robustness of the overall reconstruction algorithm on noisy simulated data at various levels of noise by comparing with some of the state-of-the-art reconstruction methods. Then, using simulated data, we validate that Spearman's rank correlation coefficient between pairwise distances in the reconstructed chromosomal structures and the experimental chromosomal contact counts can be used to find optimum conversion rules for transforming interaction frequencies to wish distances. This strategy is then applied to real Hi-C data at chromosome level for optimal transformation of interaction frequencies to wish distances and for ranking and selecting structures. The chromosomal structures reconstructed from a real-world human Hi-C dataset by our method were validated by the known two-compartment feature of the human chromosome organization. We also show that our method is robust with respect to the change of the granularity of Hi-C data, and consistently produces similar structures at different chromosomal resolutions. CONCLUSION: Chromosome3D is a robust method of reconstructing chromosome three-dimensional models using distance restraints obtained from Hi-C interaction frequency data. It is available as a web application and as an open source tool at http://sysbio.rnet.missouri.edu/chromosome3d/ .

GMOL: An Interactive Tool for 3D Genome Structure Visualization.

It has been shown that genome spatial structures largely affect both genome activity and DNA function. Knowing this, many researchers are currently attempting to accurately model genome structures. Despite these increased efforts there still exists a shortage of tools dedicated to visualizing the genome. Creating a tool that can accurately visualize the genome can aid researchers by highlighting structural relationships that may not be obvious when examining the sequence information alone. Here we present a desktop application, known as GMOL, designed to effectively visualize genome structures so that researchers may better analyze genomic data. GMOL was developed based upon our multi-scale approach that allows a user to scale between six separate levels within the genome. With GMOL, a user can choose any unit at any scale and scale it up or down to visualize its structure and retrieve corresponding genome sequences. Users can also interactively manipulate and measure the whole genome structure and extract static images and machine-readable data files in PDB format from the multi-scale structure. By using GMOL researchers will be able to better understand and analyze genome structure models and the impact their structural relations have on genome activity and DNA function.

MOGEN: a tool for reconstructing 3D models of genomes from chromosomal conformation capturing data.

MOTIVATION: The three-dimensional (3D) conformation of chromosomes and genomes play an important role in cellular processes such as gene regulation, DNA replication and genome methylation. Several methods have been developed to reconstruct 3D structures of individual chromosomes from chromosomal conformation capturing data such as Hi-C data. However, few methods can effectively reconstruct the 3D structures of an entire genome due to the difficulty of handling noisy and inconsistent inter-chromosomal contact data. RESULTS: We generalized a 3D chromosome reconstruction method to make it capable of reconstructing 3D models of genomes from both intra- and inter-chromosomal Hi-C contact data and implemented it as a software tool called MOGEN. We validated MOGEN on synthetic datasets of a polymer worm-like chain model and a yeast genome at first, and then applied it to generate an ensemble of 3D structural models of the genome of human B-cells from a Hi-C dataset. These genome models not only were validated by some known structural patterns of the human genome, such as chromosome compartmentalization, chromosome territories, co-localization of small chromosomes in the nucleus center with the exception of chromosome 18, enriched center-toward inter-chromosomal interactions between elongated or telomere regions of chromosomes, but also demonstrated the intrinsically dynamic orientations between chromosomes. Therefore, MOGEN is a useful tool for converting chromosomal contact data into 3D genome models to provide a better view into the spatial organization of genomes. AVAILABILITY AND IMPLEMENTATION: The software of MOGEN is available at: http://calla.rnet.missouri.edu/mogen/ CONTACT: : chengji@missouri.edu SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Iterative reconstruction of three-dimensional models of human chromosomes from chromosomal contact data.

BACKGROUND: The entire collection of genetic information resides within the chromosomes, which themselves reside within almost every cell nucleus of eukaryotic organisms. Each individual chromosome is found to have its own preferred three-dimensional (3D) structure independent of the other chromosomes. The structure of each chromosome plays vital roles in controlling certain genome operations, including gene interaction and gene regulation. As a result, knowing the structure of chromosomes assists in the understanding of how the genome functions. Fortunately, the 3D structure of chromosomes proves possible to construct through computational methods via contact data recorded from the chromosome. We developed a unique computational approach based on optimization procedures known as adaptation, simulated annealing, and genetic algorithm to construct 3D models of human chromosomes, using chromosomal contact data. RESULTS: Our models were evaluated using a percentage-based scoring function. Analysis of the scores of the final 3D models demonstrated their effective construction from our computational approach. Specifically, the models resulting from our approach yielded an average score of 80.41%, with a high of 91%, across models for all chromosomes of a normal human B-cell. Comparisons made with other methods affirmed the effectiveness of our strategy. Particularly, juxtaposition with models generated through the publicly available method Markov chain Monte Carlo 5C (MCMC5C) illustrated the outperformance of our approach, as seen through a higher average score for all chromosomes. Our methodology was further validated using two consistency checking techniques known as convergence testing and robustness checking, which both proved successful. CONCLUSIONS: The pursuit of constructing accurate 3D chromosomal structures is fueled by the benefits revealed by the findings as well as any possible future areas of study that arise. This motivation has led to the development of our computational methodology. The implementation of our approach proved effective in constructing 3D chromosome models and proved consistent with, and more effective than, some other methods thereby achieving our goal of creating a tool to help advance certain research efforts. The source code, test data, test results, and documentation of our method, Gen3D, are available at our sourceforge site at: http://sourceforge.net/projects/gen3d/.

Large-scale reconstruction of 3D structures of human chromosomes from chromosomal contact data.

Chromosomes are not positioned randomly within a nucleus, but instead, they adopt preferred spatial conformations to facilitate necessary long-range gene-gene interactions and regulations. Thus, obtaining the 3D shape of chromosomes of a genome is critical for understanding how the genome folds, functions and how its genes interact and are regulated. Here, we describe a method to reconstruct preferred 3D structures of individual chromosomes of the human genome from chromosomal contact data generated by the Hi-C chromosome conformation capturing technique. A novel parameterized objective function was designed for modeling chromosome structures, which was optimized by a gradient descent method to generate chromosomal structural models that could satisfy as many intra-chromosomal contacts as possible. We applied the objective function and the corresponding optimization method to two Hi-C chromosomal data sets of both a healthy and a cancerous human B-cell to construct 3D models of individual chromosomes at resolutions of 1 MB and 200 KB, respectively. The parameters used with the method were calibrated according to an independent fluorescence in situ hybridization experimental data. The structural models generated by our method could satisfy a high percentage of contacts (pairs of loci in interaction) and non-contacts (pairs of loci not in interaction) and were compatible with the known two-compartment organization of human chromatin structures. Furthermore, structural models generated at different resolutions and from randomly permuted data sets were consistent.