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Oliveira Junior, A. B.

Publications and source records attributed to Oliveira Junior, A. B..

6 recordsLinked to original sources

Learning from Hi-C reveals nuclear dynamical reorganization in budding yeast across the cell cycle

Hi-C contact maps provide population-averaged measurements of chromosomal contacts. Converting these measurements, however, into three-dimensional structures and associated dynamics remains an underdetermined problem. Existing approaches broadly fall into two classes. Data-driven reconstruction methods that infer either a consensus structure or an ensemble of conformations, but do not inform on chromosome dynamics. Physics-based models, which generate dynamical trajectories, but require prior assumptions about nuclear geometry, chromatin mechanics, tethering, or molecular interactions. Here, we bridge these approaches using the Full-Inversion Chromatin model, a data-driven whole-genome polymer framework that learns an effective force field directly from Hi-C contact probabilities, integrated with Serpentine, a tool to quantify contact-map discrepancies while accounting for differences in sequencing coverage and sparsity. This generates structural ensembles of chromosomes and effective chromatin dynamics. We apply this method at 5-kb resolution to Saccharomyces cerevisiae in G1, mid-S, S/G2, G2/M, anaphase, and quiescence. Without explicitly imposing the spindle pole body, centromere or telomere tethering, predefined chromatin states, or nuclear-envelope interactions, the inferred ensembles recover these major features of yeast nuclear organization. Importantly, although dynamical information is not used during model training, the resulting polymer trajectories reproduce the subdiffusive scaling and chromosomal variations of independently measured chromatin motion. The model further predicts heterogeneous mobility along chromosomes and a distinctive telomere-dependent dynamical organization. Thus, population-averaged Hi-C contacts contain sufficient information to infer not only three-dimensional genome organization, but also effective, locus-dependent chromatin dynamics.

biophysics↗

ELViM: Understanding Molecular Energy Landscape

AbstractMolecular dynamics (MD) simulations provide a powerful means to explore the dynamic behavior of biomolecular systems at the atomic level. However, analyzing the vast datasets generated by MD simulations poses significant challenges. This manuscript discusses the Energy Landscape Visualization Method (ELViM), a multidimensional reduction technique inspired by energy landscape theory. ELViM transcends one-dimensional representations, offering a comprehensive analysis of the effective conformational phase space without the need for predefined reaction coordinates. We apply ELViM to study the folding landscape of the antimicrobial peptide Polybia-MP1, showcasing its versatility in capturing complex biomolecular dynamics. Using dissimilarity matrices and a force-scheme approach, ELViM provides intuitive visualizations, revealing structural correlations, and local conformational signatures. The method is demonstrated to be adaptable, robust, and applicable to various biomolecular systems.

biophysics↗

Three-dimensional genome architecture persists in a 52,000-year-old woolly mammoth skin sample

Ancient DNA (aDNA) sequencing analysis typically involves alignment to a modern reference genome assembly from a related species. Since aDNA molecules are fragmentary, these alignments yield information about small-scale differences, but provide no information about larger features such as the chromosome structure of ancient species. We report the genome assembly of a female Late Pleistocene woolly mammoth (Mammuthus primigenius) with twenty-eight chromosome-length scaffolds, generated using mammoth skin preserved in permafrost for roughly 52,000 years. We began by creating a modified Hi-C protocol, dubbed PaleoHi-C, optimized for ancient samples, and using it to map chromatin contacts in a woolly mammoth. Next, we developed "reference-assisted 3D genome assembly," which begins with a reference genome assembly from a related species, and uses Hi-C and DNA-Seq data from a target species to split, order, orient, and correct sequences on the basis of their 3D proximity, yielding accurate chromosome-length scaffolds for the target species. By means of this reference-assisted 3D genome assembly, PaleoHi-C data reveals the 3D architecture of a woolly mammoth genome, including chromosome territories, compartments, domains, and loops. The active (A) and inactive (B) genome compartments in mammoth skin more closely resemble those observed in Asian elephant skin than the compartmentalization patterns seen in other Asian elephant tissues. Differences in compartmentalization between these skin samples reveal sequences whose transcription was potentially altered in mammoth. We observe a tetradic structure for the inactive X chromosome in mammoth, distinct from the bipartite architecture seen in human and mouse. Generating chromosome-length genome assemblies for two other elephantids (Asian and African elephant), we find that the overall karyotype, and this tetradic Xi structure, are conserved throughout the clade. These results illustrate that cell-type specific epigenetic information can be preserved in ancient samples, in the form of DNA geometry, and that it may be feasible to perform de novo genome assembly of some extinct species.

genomics↗

Structural Reorganization and Relaxation Dynamics of Axially Stressed Chromosomes

Micromechanical studies of mitotic chromosomes have revealed them to be remarkably extensible objects and informed early models of mitotic chromosome organization. We use a data-driven, coarsegrained polymer modeling approach, capable of generating ensembles of chromosome structures that are quantitatively consistent with experiments, to explore the relationship between the spatial organization of individual chromosomes and their emergent mechanical properties. In particular, we investigate the mechanical properties of our model chromosomes by axially stretching them. Simulated stretching led to a linear force-extension curve for small strain, with mitotic chromosomes behaving about ten-fold stiffer than interphase chromosomes. Studying the relaxation dynamics we found that chromosomes are viscoelastic solids, with a highly liquid-like, viscous behavior in interphase that becomes solid-like in mitosis. This emergent mechanical stiffness in our model originates from lengthwise compaction, an effective potential capturing the activity of loop-extruding SMC complexes. Chromosomes denature under large strains via unraveling, which is characterized by opening of large-scale folding patterns. By quantifying the effect of mechanical perturbations on the chromosomes structural features, our model provides a nuanced understanding of in vivo mechanics of chromosomes.

biophysics↗

Examining the Ensembles of Amyloid-β Monomer Variants and their Propensities to Form Fibers Using an Energy Landscape Visualization Method

The amyloid-{beta} (A{beta}) monomer, an intrinsically disordered peptide, is produced by the cleavage of the amyloid precursor protein, leading to A{beta}40 and A{beta}42 as major products. These two isoforms generate pathological aggregates, whose accumulation correlates with Alzheimers disease (AD). Experiments have shown that even though the natural abundance of A{beta}42 is smaller than that for A{beta}40, the A{beta}42 is more aggregation-prone compared to A{beta}40. Moreover, several single-point mutations are associated with early-onset forms of AD. This work analyzes coarse-grained AWSEM simulations of normal A{beta}40 and A{beta}42 monomers, along with six single-point mutations associated with early on set disease. We analyzed the simulations using the Energy Landscape Visualization Method (ELViM), a reaction coordinate-free approach suited to explore the frustrated energy landscapes of intrinsically disordered proteins. ELViM is shown to distinguish the monomer ensembles of variants that rapidly form fibers from those that do not form fibers as readily. It also delineates the amino-acid contacts characterizing each ensemble. The results shed light on the potential of ELViM to probe intrinsically disordered proteins.

biophysics↗

Exploring Energy Landscapes of Intrinsically Disordered Proteins: Insights into Functional Mechanisms

Intrinsically disordered proteins (IDPs) lack a rigid 3D structure and populate a polymorphic ensemble of conformations. Because of the lack of a reference conformation, their energy landscape representation in terms of reaction coordinates presents a daunting challenge. Here, our newly developed Energy Landscape Visualization Method (ELViM), a reaction coordinate-free approach, shows its prime application to explore frustrated energy landscapes of an intrinsically disordered protein, Prostate-Associated Gene 4 (PAGE4). PAGE4 is a transcriptional coactivator that potentiates the oncogene c-Jun. Two kinases, namely HIPK1 and CLK2, phosphorylate PAGE4 generating variants phosphorylated at different serine/threonine residues (HIPK1-PAGE4 and CLK2-PAGE4, respectively) with opposing functions. While HIPK1-PAGE4 predominantly phosphorylates Thr51 and potentiates c-Jun, CLK2-PAGE4 hyper-phosphorylates PAGE4 and attenuates transactivation. To understand the underlying mechanisms of conformational diversity among different phosphoforms, we have analyzed their atomistic trajectories simulated using AWSEM forcefield and the energy landscapes were elucidated using ELViM. This method allows us to identify and compare the population distributions of different conformational ensembles of PAGE4 phosphoforms using the same effective phase space. The results reveal a predominant conformational ensemble with an extended C-terminal segment of WT PAGE4, which exposes a functional residue Thr51, implying its potential of undertaking a fly-casting mechanism while binding to its cognate partner. In contrast, for HIPK1-PAGE4, a compact conformational ensemble enhances its population sequestering phosphorylated-Thr51. This clearly explains the experimentally observed weaker affinity of HIPK1-PAGE4 for c-Jun. ELViM appears as a powerful tool especially to analyze the highly-frustrated energy landscape representation of IDPs where appropriate reaction coordinates are hard to apprehend.

biophysics↗