Biology subjects

Onufriev, A. V.

Publications and source records attributed to Onufriev, A. V..

10 recordsLinked to original sources

bioRxiv2026

Reversing aging-like 3D genome disorganization in a Drosophila interphase model

Recent experimental evidence suggests that aging may arise from the progressive deterioration of the epigenetic landscape, while reversing the trend can result in cell and tissue rejuvenation. A mechanistic understanding of how restoration of a key component of this landscape - the 3D structure of the genome - can be accomplished is lacking. Here we investigate lamina-dependent disruption and recovery of the 3D architecture of the Drosophila melanogaster genome at TAD resolution ([~] 100 kb), using a model of the entire nucleus; weakening of chromatin-lamina interactions mimics an aging-associated loss of chromatin organization. We characterize this loss using the Shannon entropy of appropriately normalized Hi-C contact matrices. Our main finding is that lamina-depletion-induced increases in Hi-C map disorder, deterioration of chromosome territories, and cell-to-cell conformational heterogeneity are largely reversible when WT-like LAD-nuclear-envelope interactions are restored. The original and recovered conformational states of chromatin are nearly indistinguishable by bulk Hi-C contact matrix; the corresponding Pearson correlation coefficient is 0.999902. The direct experimentally testable prediction is that restoration of functional LAD-lamina interactions will promote recovery of young/WT-like 3D chromatin architecture after lamina-dependent architectural disruption.

genomics↗

bioRxiv2025

Quantifying Conformational Heterogeneity of 3D Genome Organization in Fruit Fly

The three-dimensional (3D) organization of interphase chromatin in eukaryotes is complex; details of the corresponding genome structures vary stochastically from cell to cell. Here, we propose a metric to quantify the cell-to-cell heterogeneity of the 3D chromatin conformations in ensembles of single cells: Conformational Heterogeneity (C.H.) is defined as the standard deviation of the ensemble distribution of the per cell average Euclidean inter-loci distances [<]Rs[>], for a given genomic separation s between the loci. We have used the metric to examine and quantify in detail the cell-to-cell heterogeneity of conformations of the interphase X chromosome in fruit fly generated via three distinctly different modeling approaches, which take experimental Hi-C data as input. Two of the approaches use bulk Hi-C and lamina-DamID data, while the third relies on single-cell Hi-C maps. An algorithm is proposed to facilitate comparison of C.H. of models constructed at different resolutions, and to examine the behavior of conformational heterogeneity with increasing model resolution. Higher resolution models show a greater C.H., in general. The impact of the model resolution is strongest near the genomic distance s corresponding to the resolution limit of the model, and diminishes for larger genomic distances: extrapolating the resolution from approximately 14 kb to 2 kb has little effect on the C.H. beyond [~]100 kb. All chromatin models examined in this work show a very similar trend of monotonically increasing structural heterogeneity with s, up to the genomic TAD size; beyond that, significant differences arise, with the model based on single-cell Hi-C showing nearly opposite trend compared to the two models that use bulk Hi-C data. We attribute these major differences to relatively subtle differences in the modeling approaches, which we discuss. Based on the analysis, we propose to explore the possibility of inclusion of bulk Hi-C data into training of chromatin models that are based on necessarily limited single-cell Hi-C data. Within our computational approach, depletion of nuclear lamins leads to increased structural heterogeneity at nearly all genomic separations, with the potential implication that cell functions that depend on chromatin structure might be more variable within lamins depleted nuclei compared to the wild type.

genomics↗

bioRxiv2023

Why Na+ has higher propensity than K+ to condense DNA in a crowded environment.

Experimentally, in the presence of crowding agent polyethylene glycol (PEG), sodium ions compact double-stranded DNA more readily than potassium ions. Here we have used molecular dynamics simulations and the "ion binding shells model" of DNA condensation to provide an atomic level picture that explains the observed variations in condensation of short (25 base pairs) DNA duplexes in solutions containing different monovalent cations and PEG; several predictions are made. In general, there are two major modes (shells) of ion binding to DNA, internal and external, distinguished by the proximity of bound ions to the helical axis. Externally bound ions contribute the most to the ion-induced aggregation of DNA duplexes. The simulations reveal that for two adjacent DNA duplexes, as well as for a single DNA duplex, the number of externally bound Na+ ions is larger than the number of K+ ions over a wide range of NaCl and KCl concentrations in the presence of PEG, providing a qualitative explanation for the higher propensity of sodium ions to compact DNA under crowded conditions. The qualitative picture is confirmed by an estimate of the corresponding free energy of DNA aggregation in the presence of different ions: the aggregation free energy is at least 0.2kBT per base pair more favorable in solution with NaCl than with KCl, at the same ion concentration. The estimated attraction free energy of DNA duplexes in the presence of Na+ depends on the DNA sequence noticeably: we predict that AT-rich DNA duplexes are more readily condensed than GC-rich ones in the presence of Na+. The sequence dependence of the DNA aggregation propensity is nearly absent for K+. Counter-intuitively, the addition of a small amount of crowding agent with high affinity for the specific condensing ion may lead to the weakening of the ion-mediated DNA-DNA attraction, shifting the equilibrium away from the DNA condensed phase.

biophysics↗

bioRxiv2023

Multi-plateau force-extension curves of long double-stranded DNA

When highly stretched, double-stranded DNA exhibits a plateau region in its force-extension curve. Using a bead-spring coarse-grained dynamic model based on a non-convex potential, we predict that a long double-stranded DNA fragment made of several consecutive segments with substantially different plateau force values for each segment will exhibit multiple distinct plateau regions in the force-extension curve under physiologically relevant solvent conditions. For example, a long composite double-stranded (ds) DNA fragment consisting of two equal-length segments characterized by two different plateau force values, such as the poly(dA-dT)-poly(dG-dC) fragment, is predicted to exhibit two distinct plateau regions in its force-extension curve; a long composite dsDNA fragment consisting of three segments having three different plateau force values is predicted to have three distinct plateau regions. The formation of mixed states of slightly and highly stretched DNA, co-existing with macroscopically distinct phases of uniformly stretched DNA is also predicted. When one of the segments overstretches, the extensions of the segments can differ drastically. For example, for the poly(dA-dT)-poly(dG-dC) composite fragment, in the middle of the first plateau, 96.7 % of the total extension of the fragment (relative to Lx/L0{approx} 1.0) comes from the poly(dA-dT) segment, while only 3.3 % of it comes from the poly(dG-dC) segment. The order of the segments has little effect on the force-extension curve or the distribution of conformational states. We speculate that the distinct structural states of stretched double-stranded DNA may have functional importance. For example, these states may modulate, in a sequence-dependent manner, the rate of double-stranded DNA processing by key cellular machines. TOC Graphic O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=114 SRC="FIGDIR/small/532320v2_ufig1.gif" ALT="Figure 1"> View larger version (11K): org.highwire.dtl.DTLVardef@fc52forg.highwire.dtl.DTLVardef@15abedaorg.highwire.dtl.DTLVardef@a7fbbborg.highwire.dtl.DTLVardef@7fc8e4_HPS_FORMAT_FIGEXP M_FIG C_FIG

biophysics↗

bioRxiv2022

Stretching of long double-stranded DNA and RNA described by the same model.

We propose a bead-spring model that accurately reproduces a variety of experimental force-extension curves of long double-stranded DNA and RNA, including torsionally constrained and unconstrained DNA, and negatively supercoiled DNA. A key feature of the model is a specific non-convex energy function of the spring. We provide an algorithm for obtaining five required parameters of the model from experimental force-extension curves. In the plateau region of the force-extension curves, our molecular dynamics simulations show that the polymer separates into a mix of weakly and strongly stretched states without forming macroscopically distinct phases.

biophysics↗

bioRxiv2022

The probability of chromatin to be at the nuclear lamina has no systematic effect on its transcription level.

Multiple studies have demonstrated a negative correlation between gene expression and the positioning of genes at the nuclear envelope (NE) lined by nuclear lamina. In this paper, we ask whether there is a causal, systematic relationship between the expression level of the groups of genes in topologically associating domains (TADs) of Drosophila nuclei and the probabilities of TADs to be found at the NE. To investigate the nature of this possible relationship, we combine a coarse-grained dynamic model of the entire Drosophila nucleus with genome-wide gene expression data; we analyze the TAD averaged transcription levels of genes against the probabilities of individual TADs to be near the NE in the control and lamins-depleted nuclei. Our findings demonstrate that, within the statistical error margin, the stochastic positioning of Drosophila melanogaster TADs at the NE does not, by itself, systematically affects the mean level of gene expression in these TADs, while the expected negative correlation is confirmed. The correlation is weak and disappears completely for TADs not containing lamina-associated domains (LADs) or TADs containing LADs, considered separately. Verifiable hypotheses of the underlying mechanism for the presence of correlation without causality are discussed.

cell biology↗

bioRxiv2022

Strong interactions between highly-dynamic lamina-associated domains and the nuclear envelope stabilize the 3D architecture of Drosophila interphase chromatin

BackgroundInteractions among topologically associating domains (TADs), and between the nuclear envelope (NE) and lamina-associated domains (LADs) are expected to shape various aspects of 3D chromatin structure and dynamics; however, relevant genome-wide experiments that may provide statistically significant conclusions remain difficult. ResultsWe have developed a coarse-grained dynamical model of the Drosophila melanogaster nuclei at TAD resolution that explicitly accounts for four distinct epigenetic classes of TADs and LAD-NE interactions. The model is parameterized to reproduce the experimental Hi-C map of the wild type (WT) nuclei; it describes time evolution of the chromatin over the G1 phase of the interphase. Best agreement with the experiment is achieved when the simulations include an ensemble of nuclei, corresponding to the experimentally observed set of several possible mutual arrangements of chromosomal arms. The model is validated against multiple structural features of chromatin from several different experiments not used in model development, including those that describe changes in chromatin induced by lamin depletion. Predicted positioning of all LADs at the NE is highly dynamic - the same LAD can attach, detach and move far away from the NE multiple times during interphase. The probabilities of LADs to be in contact with the NE vary by an order of magnitude, despite all having the same affinity to the NE in the model. These probabilities are mostly determined by a highly variable local linear density of LADs along the genome which also has a strong effect on the predicted radial positioning of individual TADs. Higher probability of a TAD to be near NE is largely determined by a higher linear density of LADs surrounding this TAD. The distribution of LADs along the chromosome chains plays a notable role in maintaining a non-random average global structure of chromatin. Relatively high affinity of LADs to the NE in the WT nuclei substantially reduces sensitivity of the global radial chromatin distribution to variations in the strength of TAD-TAD interactions compared to the lamin depleted nuclei, where a 0.5 kT increase of cross-type TAD-TAD interactions doubles the chromatin density in the central nucleus region. ConclusionsA dynamical model of the entire fruit fly genome makes multiple genome-wide predictions of biological interest. The distribution of LADs along the chromatin chains affects their probabilities to be in contact with the NE and radial positioning of highly mobile TADs, playing a notable role in creating a non-random average global structure of the chromatin. We conjecture that an important role of attractive LAD-NE interactions is to stabilize global chromatin structure against inevitable cell-to-cell variations in TAD-TAD interactions.

molecular biology↗

bioRxiv2021

How to count your bugs?

Ability to estimate local population density of an insect is critical in many fields, from pest management to conservation. No method currently exists that reliably connects trap catch with the insect population density, including the corresponding uncertainty. Here we report a simple and universal predictive relationship for a probability of catching an insect located a given distance away from the trap. This relationship allows to estimate, from a single catch, the most likely population density along with its statistical upper and lower bounds. To test the generality of this equation we used 10 distinct trapping data sets collected on insects from 5 different orders and major trapping methods: chemical-baited and light. For all of the datasets the equation faithfully [Formula] describes the relationship between location of an insect and probability to catch it. The ability to estimate absolute population density from a single trap catch will significantly improve our understanding of insect population dynamics and allow for more effective research, management, and conservation programs.

ecology↗

bioRxiv2020

MMGB/SA Consensus Estimate of the Binding Free Energy Between the Novel Coronavirus Spike Protein to the Human ACE2 Receptor

The ability to estimate protein-protein binding free energy in a computationally efficient via a physics-based approach is beneficial to research focused on the mechanism of viruses binding to their target proteins. Implicit solvation methodology may be particularly useful in the early stages of such research, as it can offer valuable insights into the binding process, quickly. Here we evaluate the potential of the related molecular mechanics generalized Born surface area (MMGB/SA) approach to estimate the binding free energy {Delta}Gbind between the SARS-CoV-2 spike receptor-binding domain and the human ACE2 receptor. The calculations are based on a recent flavor of the generalized Born model, GBNSR6. Two estimates of {Delta}Gbind are performed: one based on standard bondi radii, and the other based on a newly developed set of atomic radii (OPT1), optimized specifically for protein-ligand binding. We take the average of the resulting two {Delta}Gbind values as the consensus estimate. For the well-studied Ras-Raf protein-protein complex, which has similar binding free energy to that of the SARS-CoV-2/ACE2 complex, the consensus {Delta}Gbind = -11.8 {+/-} 1 kcal/mol, vs. experimental -9.7 {+/-} 0.2 kcal/mol. The consensus estimates for the SARS-CoV-2/ACE2 complex is {Delta}Gbind = -9.4 {+/-} 1.5 kcal/mol, which is in near quantitative agreement with experiment (-10.6 kcal/mol). The availability of a conceptually simple MMGB/SA-based protocol for analysis of the SARS-CoV-2 /ACE2 binding may be beneficial in light of the need to move forward fast.

biophysics↗

bioRxiv2017

Linear relationship between peak and season-long abundances in insects

O_LIAn accurate quantitative relationship between key characteristics of an insect population, such as season-long and peak abundances, can be very useful in pest management programs. To the best of our knowledge, no such relationship yet has been established.\nC_LIO_LIHere we establish a predictive linear relationship between insect catch Mpw during the week of peak abundance, the length of seasonal flight period, F (number of weeks) and season-long cumulative catch (abundance) A =0.41 MpwF. The derivation of the equation is based on several general assumptions, and does not involve fitting to experimental data, which implies generality of the result. A quantitative criterion for the validity of the model is presented.\nC_LIO_LIThe equation was tested using extensive data collected on captures of male gypsy moths Lymantria dispar (L.) (Lepidoptera: Erebidae) in pheromone-baited traps during 15 years.\nC_LIO_LIThe model was also tested using trap catch data for two species of mosquitoes, Culex pipiens (L.) (Diptera: Culicidae) and Aedes albopictus (Skuse) (Diptera: Culicidae), in Gravid and BG-sentinel mosquito traps, respectively.\nC_LIO_LIThe simple, parameter-free equation approximates experimental data points with relative error of 13% and R2 = 0.997, across all of the species tested.\nC_LIO_LIFor gypsy moth, we also related season-long and weekly trap catches to the daily trap catches during peak flight.\nC_LIO_LIWe describe several usage scenarios, in which the derived relationships are employed to help link results of small-scale field studies to the operational pest management programs.\nC_LI

ecology↗