101 Exploring the 3D spatial organization of the genome

Knowledge about the 3D organization of the genome will offer great insights into how cells retrieve and process the genetic information. Knowing the spatial probability distributions of individual genes will provide insights into gene regulatory and replication processes, and fill in the missing links between epigenomics, functional genomics, and structural biology. We will discuss an approach to determine 3D genome structures and structure–function maps of genomes by integrating divers types of data. To address the challenge of modeling highly variable genome structures, we discuss a population-based modeling approach, where we construct a large population of 3D genome structures that together are entirely consistent with all available experimental data including data from genome-wide chromosome conformation capture and imaging experiments. We interpret the result in terms of probabilities of a sample drawn from a population of heterogeneous structures. We will discuss results on the 3D spatial organization of genomes in human lymphoblastoid cells and budding yeast.     

Bridging the gap

Therapeutic monoclonal antibodies (mAbs) currently dominate the biologics marketplace. Development of a new therapeutic mAb candidate is a complex, multistep process and early stages of development typically begin in an academic research environment. Recently, a number of facilities and initiatives have been launched to aid researchers along this difficult path and facilitate progression of the next mAb blockbuster. Complementing this, there has been a renewed interest from the pharmaceutical industry to reconnect with academia in order to boost dwindling pipelines and encourage innovation. In this review, we examine the steps required to take a therapeutic mAb from discovery through early stage preclinical development and toward becoming a feasible clinical candidate. Discussion of the technologies used for mAb discovery, production in mammalian cells and innovations in single-use bioprocessing is included. We also examine regulatory requirements for product quality and characterization that should be considered at the earliest stages of mAb development. We provide details on the facilities available to help researchers and small-biotech build value into early stage product development, and include examples from within our own facility of how technologies are utilized and an analysis of our client base.     

Bridging the information gap: computational tools for intermediate resolution structure interpretation

Due to large sizes and complex nature, few large macromolecular complexes have been solved to atomic resolution. This has lead to an under-representation of these structures, which are composed of novel and/or homologous folds, in the library of known structures and folds. While it is often difficult to achieve a high-resolution model for these structures, X-ray crystallography and electron cryomicroscopy are capable of determining structures of large assemblies at low to intermediate resolutions. To aid in the interpretation and analysis of such structures, we have developed two programs: helixhunter and foldhunter. Helixhunter is capable of reliably identifying helix position, orientation and length using a five-dimensional cross-correlation search of a three-dimensional density map followed by feature extraction. Helixhunter's results can in turn be used to probe a library of secondary structure elements derived from the structures in the Protein Data Bank (PDB). From this analysis, it is then possible to identify potential homologous folds or suggest novel folds based on the arrangement of alpha helix elements, resulting in a structure-based recognition of folds containing alpha helices. Foldhunter uses a six-dimensional cross-correlation search allowing a probe structure to be fitted within a region or component of a target structure. The structural fitting therefore provides a quantitative means to further examine the architecture and organization of large, complex assemblies. These two methods have been successfully tested with simulated structures modeled from the PDB at resolutions between 6 and 12 A. With the integration of helixhunter and foldhunter into sequence and structural informatics techniques, we have the potential to deduce or confirm known or novel folds in domains or components within large complexes.     

The 3D organization of genome in the nucleus: from the nucleosome to the 4D nucleome

正The genetic information, stored in the linear sequences of DNA, encodes all of the genes that a living organism uses to produce proteins and RNAs essential for various cellular functions. In eukaryotes, however, genomic DNA is hierarchically and efficiently packaged into multiple-level chromatin structures within the nucleus, including the nucleosome, 30 nm fibers, chromatin loops, topology asso-     

3D genomics imposes evolution of the domain model of eukaryotic genome organization

The hypothesis that the genome is composed of a patchwork of structural and functional domains (units) that may be either active or repressed was proposed almost 30 years ago. Here, we examine the evolution of the domain model of eukaryotic genome organization in view of the expansion of genome-scale techniques in the twenty-first century that have provided us with a wealth of information on genome organization, folding, and functioning.     

Uncovering the statistical physics of 3D chromosomal organization using data-driven modeling

In recent years, much effort has been devoted to understanding the three-dimensional (3D) organization of the genome and how genomic structure mediates nuclear function. The development of experimental techniques that combine DNA proximity ligation with high-throughput sequencing, such as Hi-C, have substantially improved our knowledge about chromatin organization. Numerous experimental advancements, not only utilizing DNA proximity ligation but also high-resolution genome imaging (DNA tracing), have required theoretical modeling to determine the structural ensembles consistent with such data. These 3D polymer models of the genome provide an understanding of the physical mechanisms governing genome architecture. Here, we present an overview of the recent advances in modeling the ensemble of 3D chromosomal structures by employing the maximum entropy approach combined with polymer physics. Particularly, we discuss the minimal chromatin model (MiChroM) along with the “maximum entropy genomic annotations from biomarkers associated with structural ensembles” (MEGABASE) model, which have been remarkably successful in the accurate modeling of chromosomes consistent with both Hi-C and DNA-tracing data.     

3D genome organization in the central nervous system,implications for neuropsychological disorders

Chromosomes in eukaryotic cell nuclei are highly compacted and finely organized into hierarchical three-dimensional (3D) configuration. In recent years, scientists have gained deeper understandings of 3D genome structures and revealed novel evidence linking 3D genome organization to various important cell events on the molecular level. Most importantly, alteration of 3D genome architecture has emerged as an intriguing higher order mechanism that connects disease-related genetic variants in multiple heterogenous and polygenic neuropsychological disorders, delivering novel insights into the etiology. In this review, we provide a brief overview of the hierarchical structures of 3D genome and two proposed regulatory models, loop extrusion and phase separation. We then focus on recent Hi-C data in the central nervous system and discuss 3D genome alterations during normal brain development and in mature neurons. Most importantly, we make a comprehensive review on current knowledge and discuss the role of 3D genome in multiple neuropsychological disorders, including schizophrenia, repeat expansion disorders, 22q11 deletion syndrome, and others.     

Specific features of the structural organization of the mitochondrial genome in RAT liver

Summary The nature of intramolecular heterogeneity of mtDNA in the liver of white rats has been studied. The peculiarities of the melting curve, and the possibility of DNA fractionation of nucleotide compounds with hydroxylapatite (HA) column chromatography has shown the presence of sequences differing in the mean nucleotide content. A section of about 350 pairs in size repeated four times was found in the reassociation of most thermolabile fraction with a mean composition of 28% GC. These sections are well seen on the denaturation map of the recorded molecules formed in the range of temperature transition helix-coil. The distance between the centers of fusible sections (in percentage of total length) is 32.5, 32, 14.0 and 21.5.     

New local potential useful for genome annotation and 3D modeling

A new potential energy function representing the conformational preferences of sequentially local regions of a protein backbone is presented. This potential is derived from secondary structure probabilities such as those produced by neural network-based prediction methods. The potential is applied to the problem of remote homolog identification, in combination with a distance-dependent inter-residue potential and position-based scoring matrices. This fold recognition jury is implemented in a Java application called JThread. These methods are benchmarked on several test sets, including one released entirely after development and parameterization of JThread. In benchmark tests to identify known folds structurally similar to (but not identical with) the native structure of a sequence, JThread performs significantly better than PSI-BLAST, with 10% more structures identified correctly as the most likely structural match in a fold library, and 20% more structures correctly narrowed down to a set of five possible candidates. JThread also improves the average sequence alignment accuracy significantly, from 53% to 62% of residues aligned correctly. Reliable fold assignments and alignments are identified, making the method useful for genome annotation. JThread is applied to predicted open reading frames (ORFs) from the genomes of Mycoplasma genitalium and Drosophila melanogaster, identifying 20 new structural annotations in the former and 801 in the latter.     

Bridging the gap in RNA structure prediction

The field of RNA structure prediction has experienced significant advances in the past several years, thanks to the availability of new experimental data and improved computational methodologies. These methods determine RNA secondary structures and pseudoknots from sequence alignments, thermodynamics-based dynamic programming algorithms, genetic algorithms and combined approaches. Computational RNA three-dimensional modeling uses this information in conjunction with manual manipulation, constraint satisfaction methods, molecular mechanics and molecular dynamics. The ultimate goal of automatically producing RNA three-dimensional models from given secondary and tertiary structure data, however, is still not fully realized. Recent developments in the computational prediction of RNA structure have helped bridge the gap between RNA secondary structure prediction, including pseudoknots, and three-dimensional modeling of RNA.