A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is
Physical proximity between each pair of genomic loci in a nucleus is measured as a form of contact frequency in chromosome conformation capture-based methods. Complexity of chromosome structure in interphase can be characterized by measuring a statistical property of physical distance between genomic loci according to genomic separation along single chromatids. To find a relationship between the physical distance and the contact frequency, we propose a polymer model derived from the Langevindoi:10.1016/j.bpj.2013.08.043 pmid:24138854 pmcid:PMC3797596 fatcat:26sai6ocajahtppuxndr6whmhy
more »... ation. The model is derived by considering a structure of a chromosome as a trajectory of a particle, where each consecutive segment in the chromosome corresponds to a transient position in the trajectory over time. Using chromosome conformation capture data, we demonstrate the functional relationship between the two quantities. The physical distances derived from the mean contact frequencies by the model show a good correlation with those from experimental data. From the model, we present that the mean contact frequency curve can be divided into three components that arise from different physical origins and show that the contact frequency is proportional to the contact surface area, not to the volume of segments suggested by the fractal globule model. The model explains both a decaying pattern of the contact frequency and the biphasic relationship between the physical distance and the genomic length.
Living cells exhibit multi-mode transport that switches between an active, self-propelled motion and a seemingly passive, random motion. Cellular decision-making over transport mode switching is a stochastic process that depends on the dynamics of the intracellular chemical network regulating the cell migration process. Here, we propose a theory and an exactly solvable model of multi-mode active matter. Our exact model study shows that the reversible transition between a passive mode and anarXiv:1708.00190v1 fatcat:ejgrkpxvnveohpwxo7l3mxdwpa
more »... ve mode is the origin of the anomalous, super-Gaussian transport dynamics, which has been observed in various experiments for multi-mode active matter. We also present the generalization of our model to encompass complex multi-mode matter with arbitrary internal state chemical dynamics and internal state dependent transport dynamics.
Chromosome conformation capture (3C)-based techniques have recently been used to uncover the mystic genomic architecture in the nucleus. These techniques yield indirect data on the distances between genomic loci in the form of contact frequencies that must be normalized to remove various errors. This normalization process determines the quality of data analysis. In this study, we describe two systematic errors that result from the heterogeneous local density of restriction sites and differentdoi:10.1371/journal.pone.0146007 pmid:26717152 pmcid:PMC4696798 fatcat:sqeswsvtzbep7ehh3zxefdiu74
more »... cal chromatin states, methods to identify and remove those artifacts, and three previously described sources of systematic errors in 3C-based data: fragment length, mappability, and local DNA composition. To explain the effect of systematic errors on the results, we used three different published data sets to show the dependence of the results on restriction enzymes and experimental methods. Comparison of the results from different restriction enzymes shows a higher correlation after removing systematic errors. In contrast, using different methods with the same restriction enzymes shows a lower correlation after removing systematic errors. Notably, the improved correlation of the latter case caused by systematic errors indicates that a higher correlation between results does not ensure the validity of the normalization methods. Finally, we suggest a method to analyze random error and provide guidance for the maximum reproducibility of contact frequency maps.
Protein-protein interactions play an essential role in cellular processes. Certain proteins form stable complexes with their partner proteins, whereas others function by forming transient complexes. The conventional protein-protein interaction model describes an interaction between two proteins under the assumption that a protein binds to its partner protein through a single binding site. In this study, we improved the conventional interaction model by developing a Multiple-Site (MS) model indoi:10.1371/journal.pone.0032804 pmid:22457720 pmcid:PMC3310816 fatcat:2yusqjetdrd7ff5gnn2rjhf3lm
more »... ich a protein binds to its partner protein through closely located multiple binding sites on a surface of the partner protein by transiently docking at each binding site with individual binding free energies. To test this model, we used the protein-protein interaction mediated by Src homology 3 (SH3) domains. SH3 domains recognize their partners via a weak, transient interaction and are therefore promiscuous in nature. Because the MS model requires large amounts of data compared with the conventional interaction model, we used experimental data from the positionally addressable syntheses of peptides on cellulose membranes (SPOT-synthesis) technique. From the analysis of the experimental data, individual binding free energies for each binding site of peptides were extracted. A comparison of the individual binding free energies from the analysis with those from atomistic force fields gave a correlation coefficient of 0.66. Furthermore, application of the MS model to 10 SH3 domains lowers the prediction error by up to 9% compared with the conventional interaction model. This improvement in prediction originates from a more realistic description of complex formation than the conventional interaction model. The results suggested that, in many cases, SH3 domains increased the protein complex population through multiple binding sites of their partner proteins. Our study indicates that the consideration of general complex formation is important for the accurate description of protein complex formation, and especially for those of weak or transient protein complexes.
Previously, we reported that inorganic–organic hybrid (C6H5CH2CH2NH3)2MnCl4 (Mn-PEA) is antiferromagnetic below 44 K by using magnetic susceptibility and neutron diffraction measurements. Generally, when an antiferromagnetic system is investigated by the neutron diffraction method, half-integer forbidden peaks, which indicate an enlargement of the magnetic cell compared to the chemical cell, should be present. However, in the case of the title compound, integer forbidden peaks are observed,doi:10.3390/sym12121980 fatcat:356d7433incfrclp6e2urvab3i
more »... esting that the size of the magnetic cell is the same as that of the chemical cell. This phenomenon was until now only theoretically predicted. During our former study, using an irreducible representation method, we suggested that four spin arrangements could be possible candidates and a magnetic cell and chemical cell should coincide. Recently, a magnetic structure analysis employing a magnetic space group has been developed. To confirm our former result by the representation method, in this work we employed a magnetic space group concept, and from this analysis, we show that the magnetic cell must coincide with the nuclear cell because only the Black–White 1 group (equi-translation or same translation group) is possible.
Seungsoo Hahn and Dongsup Kim. ...doi:10.1016/j.bpj.2013.11.001 fatcat:oyglontgnbfjrkktgaideq7644