533 research outputs found
Mass Density Fluctuations in Quantum and Classical descriptions of Liquid Water
First principles molecular dynamics simulation protocol is established using
revised functional of Perdew-Burke-Ernzerhof (revPBE) in conjunction with
Grimme's third generation of dispersion (D3) correction to describe properties
of water at ambient conditions. This study also demonstrates the consistency of
the structure of water across both isobaric (NpT) and isothermal (NVT)
ensembles. Going beyond the standard structural benchmarks for liquid water, we
compute properties that are connected to both local structure and mass density
uctuations that are related to concepts of solvation and hydrophobicity. We
directly compare our revPBE results to the Becke-Lee-Yang-Parr (BLYP) plus
Grimme dispersion corrections (D2) and both the empirical fixed charged model
(SPC/E) and many body interaction potential model (MB-pol) to further our
understanding of how the computed properties herein depend on the form of the
interaction potential
Histone modifications predispose genome regions to breakage and translocation
Chromosome translocations are well-established hallmarks of cancer cells and often occur at nonrandom sites in the genome. The molecular features that define recurrent chromosome breakpoints are largely unknown. Using a combination of bioinformatics, biochemical analysis, and cell-based assays, we identify here specific histone modifications as facilitators of chromosome breakage and translocations. We show enrichment of several histone modifications over clinically relevant translocation-prone genome regions. Experimental modulation of histone marks sensitizes genome regions to breakage by endonuclease challenge or irradiation and promotes formation of chromosome translocations of endogenous gene loci. Our results demonstrate that histone modifications predispose genome regions to chromosome breakage and translocations
In vivo kinetics of Cajal body components
Cajal bodies (CBs) are subnuclear domains implicated in small nuclear ribonucleoprotein (snRNP) biogenesis. In most cell types, CBs coincide with nuclear gems, which contain the survival of motor neurons (SMN) complex, an essential snRNP assembly factor. Here, we analyze the exchange kinetics of multiple components of CBs and gems in living cells using photobleaching microscopy. We demonstrate differences in dissociation kinetics of CB constituents and relate them to their functions. Coilin and SMN complex members exhibit relatively long CB residence times, whereas components of snRNPs, small nucleolar RNPs, and factors shared with the nucleolus have significantly shorter residence times. Comparison of the dissociation kinetics of these shared proteins from either the nucleolus or the CB suggests the existence of compartment-specific retention mechanisms. The dynamic properties of several CB components do not depend on their interaction with coilin because their dissociation kinetics are unaltered in residual nuclear bodies of coilin knockout cells. Photobleaching and fluorescence resonance energy transfer experiments demonstrate that coilin and SMN can interact within CBs, but their interaction is not the major determinant of their residence times. These results suggest that CBs and gems are kinetically independent structures
A dynamical model reveals gene co-localizations in nucleus
Co-localization of networks of genes in the nucleus is thought to play an important role in determining gene expression patterns. Based upon experimental data, we built a dynamical model to test whether pure diffusion could account for the observed co-localization of genes within a defined subnuclear region. A simple standard Brownian motion model in two and three dimensions shows that preferential co-localization is possible for co-regulated genes without any direct interaction, and suggests the occurrence may be due to a limitation in the number of available transcription factors. Experimental data of chromatin movements demonstrates that fractional rather than standard Brownian motion is more appropriate to model gene mobilizations, and we tested our dynamical model against recent static experimental data, using a sub-diffusion process by which the genes tend to colocalize more easily. Moreover, in order to compare our model with recently obtained experimental data, we studied the association level between genes and factors, and presented data supporting the validation of this dynamic model. As further applications of our model, we applied it to test against more biological observations. We found that increasing transcription factor number, rather than factory number and nucleus size, might be the reason for decreasing gene co-localization. In the scenario of frequency-or amplitude-modulation of transcription factors, our model predicted that frequency-modulation may increase the co-localization between its targeted genes
NUP-1 Is a Large Coiled-Coil Nucleoskeletal Protein in Trypanosomes with Lamin-Like Functions
NUP1, the first example of a nuclear lamin analog in nonmetazoans, performs roles similar to those of lamins in maintaining the structure and organization of the nucleus in Trypanosoma brucei
Spatial and topological organization of DNA chains induced by gene co-localization
Transcriptional activity has been shown to relate to the organization of
chromosomes in the eukaryotic nucleus and in the bacterial nucleoid. In
particular, highly transcribed genes, RNA polymerases and transcription factors
gather into discrete spatial foci called transcription factories. However, the
mechanisms underlying the formation of these foci and the resulting topological
order of the chromosome remain to be elucidated. Here we consider a
thermodynamic framework based on a worm-like chain model of chromosomes where
sparse designated sites along the DNA are able to interact whenever they are
spatially close-by. This is motivated by recurrent evidence that there exists
physical interactions between genes that operate together. Three important
results come out of this simple framework. First, the resulting formation of
transcription foci can be viewed as a micro-phase separation of the interacting
sites from the rest of the DNA. In this respect, a thermodynamic analysis
suggests transcription factors to be appropriate candidates for mediating the
physical interactions between genes. Next, numerical simulations of the polymer
reveal a rich variety of phases that are associated with different topological
orderings, each providing a way to increase the local concentrations of the
interacting sites. Finally, the numerical results show that both
one-dimensional clustering and periodic location of the binding sites along the
DNA, which have been observed in several organisms, make the spatial
co-localization of multiple families of genes particularly efficient.Comment: Figures and Supplementary Material freely available on
http://dx.doi.org/10.1371/journal.pcbi.100067
Interphase chromosome positioning in in vitro porcine cells and ex vivo porcine tissues
Copyright @ 2012 The Authors. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and 85 reproduction in any medium, provided the original author and source are credited. The article was made available through the Brunel University Open Access Publishing Fund.BACKGROUND: In interphase nuclei of a wide range of species chromosomes are organised into their own specific locations termed territories. These chromosome territories are non-randomly positioned in nuclei which is believed to be related to a spatial aspect of regulatory control over gene expression. In this study we have adopted the pig as a model in which to study interphase chromosome positioning and follows on from other studies from our group of using pig cells and tissues to study interphase genome re-positioning during differentiation. The pig is an important model organism both economically and as a closely related species to study human disease models. This is why great efforts have been made to accomplish the full genome sequence in the last decade. RESULTS: This study has positioned most of the porcine chromosomes in in vitro cultured adult and embryonic fibroblasts, early passage stromal derived mesenchymal stem cells and lymphocytes. The study is further expanded to position four chromosomes in ex vivo tissue derived from pig kidney, lung and brain. CONCLUSIONS: It was concluded that porcine chromosomes are also non-randomly positioned within interphase nuclei with few major differences in chromosome position in interphase nuclei between different cell and tissue types. There were also no differences between preferred nuclear location of chromosomes in in vitro cultured cells as compared to cells in tissue sections. Using a number of analyses to ascertain by what criteria porcine chromosomes were positioned in interphase nuclei; we found a correlation with DNA content.This study is partly supported by Sygen International PLC
Can visco-elastic phase separation, macromolecular crowding and colloidal physics explain nuclear organisation?
BACKGROUND: The cell nucleus is highly compartmentalized with well-defined domains, it is not well understood how this nuclear order is maintained. Many scientists are fascinated by the different set of structures observed in the nucleus to attribute functions to them. In order to distinguish functional compartments from non-functional aggregates, I believe is important to investigate the biophysical nature of nuclear organisation. RESULTS: The various nuclear compartments can be divided broadly as chromatin or protein and/or RNA based, and they have very different dynamic properties. The chromatin compartment displays a slow, constrained diffusional motion. On the other hand, the protein/RNA compartment is very dynamic. Physical systems with dynamical asymmetry go to viscoelastic phase separation. This phase separation phenomenon leads to the formation of a long-lived interaction network of slow components (chromatin) scattered within domains rich in fast components (protein/RNA). Moreover, the nucleus is packed with macromolecules in the order of 300 mg/ml. This high concentration of macromolecules produces volume exclusion effects that enhance attractive interactions between macromolecules, known as macromolecular crowding, which favours the formation of compartments. In this paper I hypothesise that nuclear compartmentalization can be explained by viscoelastic phase separation of the dynamically different nuclear components, in combination with macromolecular crowding and the properties of colloidal particles. CONCLUSION: I demonstrate that nuclear structure can satisfy the predictions of this hypothesis. I discuss the functional implications of this phenomenon
An iterative approach of protein function prediction
Background: Current approaches of predicting protein functions from a protein-protein interaction (PPI) dataset are based on an assumption that the available functions of the proteins (a.k.a. annotated proteins) will determine the functions of the proteins whose functions are unknown yet at the moment (a.k.a. un-annotated proteins). Therefore, the protein function prediction is a mono-directed and one-off procedure, i.e. from annotated proteins to un-annotated proteins. However, the interactions between proteins are mutual rather than static and mono-directed, although functions of some proteins are unknown for some reasons at present. That means when we use the similarity-based approach to predict functions of un-annotated proteins, the un-annotated proteins, once their functions are predicted, will affect the similarities between proteins, which in turn will affect the prediction results. In other words, the function prediction is a dynamic and mutual procedure. This dynamic feature of protein interactions, however, was not considered in the existing prediction algorithms.Results: In this paper, we propose a new prediction approach that predicts protein functions iteratively. This iterative approach incorporates the dynamic and mutual features of PPI interactions, as well as the local and global semantic influence of protein functions, into the prediction. To guarantee predicting functions iteratively, we propose a new protein similarity from protein functions. We adapt new evaluation metrics to evaluate the prediction quality of our algorithm and other similar algorithms. Experiments on real PPI datasets were conducted to evaluate the effectiveness of the proposed approach in predicting unknown protein functions.Conclusions: The iterative approach is more likely to reflect the real biological nature between proteins when predicting functions. A proper definition of protein similarity from protein functions is the key to predicting functions iteratively. The evaluation results demonstrated that in most cases, the iterative approach outperformed non-iterative ones with higher prediction quality in terms of prediction precision, recall and F-value
Drosophila histone locus bodies form by hierarchical recruitment of components
An assembly process involving sequential recruitment of components and hierarchical dependency drives formation of the nuclear structures known as histone locus bodies
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