Nucleosome spacing controls chromatin spatial structure and accessibility.

Recent research highlights the significance of the three-dimensional structure of chromatin in regulating various cellular processes, particularly transcription. This is achieved through dynamic chromatin structures that facilitate long-range contacts and control spatial accessibility. Chromatin consists of DNA and a variety of proteins, of which histones play an essential structural role by forming nucleosomes. Extensive experimental and theoretical research in recent decades has yielded conflicting results about key factors that regulate the spatial structure of chromatin, which remains enigmatic. By using a computer model that allows us to simulate chromatin volumes containing physiological nucleosome concentrations, we investigated whether nucleosome spacing or nucleosome density is fundamental for three-dimensional chromatin accessibility. Unexpectedly, the regularity of the nucleosome spacing is crucial for determining the accessibility of the chromatin network to diffusive processes, whereas variation in nucleosome concentrations has only minor effects. Using only the basic physical properties of DNA and nucleosomes was sufficient to generate chromatin structures consistent with published electron microscopy data. Contrary to other work, we found that nucleosome density did not substantially alter the properties of chromatin fibers or contact probabilities of genomic loci. No breakup of fiber-like structures was observed at high molar density. These findings challenge previous assumptions and highlight the importance of nucleosome spacing as a key driver of chromatin organization. These results identified changes in nucleosome spacing as a tentative mechanism for altering the spatial chromatin structure and thus genomic functions.

Cohesin and CTCF complexes mediate contacts in chromatin loops depending on nucleosome positions.

The spatial organization of the eukaryotic genome plays an important role in regulating transcriptional activity. In the nucleus, chromatin forms loops that assemble into fundamental units called topologically associating domains that facilitate or inhibit long-range contacts. These loops are formed and held together by the ring-shaped cohesin protein complex, and this can involve binding of CCCTC-binding factor (CTCF). High-resolution conformation capture experiments provide the frequency at which two DNA fragments physically associate in three-dimensional space. However, technical limitations of this approach, such as low throughput, low resolution, or noise in contact maps, make data interpretation and identification of chromatin intraloop contacts, e.g., between distal regulatory elements and their target genes, challenging. Herein, an existing coarse-grained model of chromatin at single-nucleosome resolution was extended by integrating potentials describing CTCF and cohesin. We performed replica-exchange Monte Carlo simulations with regularly spaced nucleosomes and experimentally determined nucleosome positions in the presence of cohesin-CTCF, as well as depleted systems as controls. In fully extruded loops caused by the presence of cohesin and CTCF, the number of contacts within the formed loops was increased. The number and types of these contacts were impacted by the nucleosome distribution and loop size. Microloops were observed within cohesin-mediated loops due to thermal fluctuations without additional influence of other factors, and the number, size, and shape of microloops were determined by nucleosome distribution and loop size. Nucleosome positions directly affect the spatial structure and contact probability within a loop, with presumed consequences for transcriptional activity.

Differences in nanoscale organization of regulatory active and inactive human chromatin.

Methodological advances in conformation capture techniques have fundamentally changed our understanding of chromatin architecture. However, the nanoscale organization of chromatin and its cell-to-cell variance are less studied. Analyzing genome-wide data from 733 human cell and tissue samples, we identified 2 prototypical regions that exhibit high or absent hypersensitivity to deoxyribonuclease I, respectively. These regulatory active or inactive regions were examined in the lymphoblast cell line K562 by using high-throughput super-resolution microscopy. In both regions, we systematically measured the physical distance of 2 fluorescence in situ hybridization spots spaced by only 5 kb of DNA. Unexpectedly, the resulting distance distributions range from very compact to almost elongated configurations of more than 200-nm length for both the active and inactive regions. Monte Carlo simulations of a coarse-grained model of these chromatin regions based on published data of nucleosome occupancy in K562 cells were performed to understand the underlying mechanisms. There was no parameter set for the simulation model that can explain the microscopically measured distance distributions. Obviously, the chromatin state given by the strength of internucleosomal interaction, nucleosome occupancy, or amount of histone H1 differs from cell to cell, which results in the observed broad distance distributions. This large variability was not expected, especially in inactive regions. The results for the mechanisms for different distance distributions on this scale are important for understanding the contacts that mediate gene regulation. Microscopic measurements show that the inactive region investigated here is expected to be embedded in a more compact chromatin environment. The simulation results of this region require an increase in the strength of internucleosomal interactions. It may be speculated that the higher density of chromatin is caused by the increased internucleosomal interaction strength.

Absence of convection in solid tumors caused by raised interstitial fluid pressure severely limits success of chemotherapy-a numerical study in cancers.

In comparison with lymphomas and leukemias, chemotherapy of solid neoplasms, i.e., cancer, has much more limited success in curing the patient. This lack of efficacy of chemotherapy has been attributed to increased interstitial fluid pressure within cancers, which obstructs convection and only permits diffusion of oxygen and nutrients about 100 µm from blood vessels. As diffusion is limited to this distance, hypoxic and necrotic fractions within the tumor are observed beyond this region. The comparably small number of cancer cells that can be targeted with drugs inevitably leads to an ineffective treatment response. This study presents an analysis of the influence of interstitial fluid pressure on the chemotherapeutic effect in an HT29 human colon cancer xenograft mouse tumor model. To investigate the limited distribution of drugs into primary tumor and metastases, we developed a mathematical model describing tumor growth dynamics of oxygenated, hypoxic, and necrotic fractions, combined with a pharmacokinetic-pharmacodynamic model describing the behavior and effectivity of the chemotherapeutic agent. According to the numerical simulations, the age of the tumor at treatment was the decisive factor in the reduction in size of the primary tumor. This effect is mediated by the rapid decrease in the percentage of oxygenated cells within the tumor, which reduces the fraction of cells that can be affected by the drug. As in the primary tumor, interstitial fluid pressure builds up in metastases when they reach a specific size, leading to the formation of tumor fractions. This behavior is absent if the metastasis enters a dormant phase before the threshold for the development of interstitial fluid pressure has been reached. The small size of these metastases maximizes therapeutic success since they consist only of oxygenated cells, and the drug therefore affects all the cells.

The initial engraftment of tumor cells is critical for the future growth pattern: a mathematical study based on simulations and animal experiments.

BACKGROUND: Xenograft mouse tumor models are used to study mechanisms of tumor growth and metastasis formation and to investigate the efficacy of different therapeutic interventions. After injection the engrafted cells form a local tumor nodule. Following an initial lag period of several days, the size of the tumor is measured periodically throughout the experiment using calipers. This method of determining tumor size is error prone because the measurement is two-dimensional (calipers do not measure tumor depth). Primary tumor growth can be described mathematically by suitable growth functions, the choice of which is not always obvious. Growth parameters provide information on tumor growth and are determined by applying nonlinear curve fitting. METHODS: We used self-generated synthetic data including random measurement errors to research the accuracy of parameter estimation based on caliper measured tumor data. Fit metrics were investigated to identify the most appropriate growth function for a given synthetic dataset. We studied the effects of measuring tumor size at different frequencies on the accuracy and precision of the estimated parameters. For curve fitting with fixed initial tumor volume, we varied this fixed initial volume during the fitting process to investigate the effect on the resulting estimated parameters. We determined the number of surviving engrafted tumor cells after injection using ex vivo bioluminescence imaging, to demonstrate the effect on experiments of incorrect assumptions about the initial tumor volume. RESULTS: To select a suitable growth function, measurement data from at least 15 animals should be considered. Tumor volume should be measured at least every three days to estimate accurate growth parameters. Daily measurement of the tumor volume is the most accurate way to improve long-term predictability of tumor growth. The initial tumor volume needs to have a fixed value in order to achieve meaningful results. An incorrect value for the initial tumor volume leads to large deviations in the resulting growth parameters. CONCLUSIONS: The actual number of cancer cells engrafting directly after subcutaneous injection is critical for future tumor growth and distinctly influences the parameters for tumor growth determined by curve fitting.

Modeling Growth of Tumors and Their Spreading Behavior Using Mathematical Functions.

Computer simulations of the spread of malignant tumor cells in an entire organism provide important insights into the mechanisms of metastatic progression. Key elements for the usefulness of these models are the adequate selection of appropriate mathematical models describing the tumor growth and its parametrization as well as a proper choice of the fractal dimension of the blood vessels in the primary tumor. In addition, survival in the bloodstream and evasion into the connective spaces of the target organ of the future metastasis have to be modeled. Determination of these from experimental models is complicated by systematic and unsystematic experimental errors which are difficult to assess. In this chapter, we demonstrate how to select the best-suited mathematical function to describe tumor growth for experimental xenograft mouse tumor models and how to parametrize them. Common pitfalls and problems are described as well as methods to avoid them.

Radiotherapy and chemotherapy change vessel tree geometry and metastatic spread in a small cell lung cancer xenograft mouse tumor model.

BACKGROUND: Tumor vasculature is critical for tumor growth, formation of distant metastases and efficiency of radio- and chemotherapy treatments. However, how the vasculature itself is affected during cancer treatment regarding to the metastatic behavior has not been thoroughly investigated. Therefore, the aim of this study was to analyze the influence of hypofractionated radiotherapy and cisplatin chemotherapy on vessel tree geometry and metastasis formation in a small cell lung cancer xenograft mouse tumor model to investigate the spread of malignant cells during different treatments modalities. METHODS: The biological data gained during these experiments were fed into our previously developed computer model "Cancer and Treatment Simulation Tool" (CaTSiT) to model the growth of the primary tumor, its metastatic deposit and also the influence on different therapies. Furthermore, we performed quantitative histology analyses to verify our predictions in xenograft mouse tumor model. RESULTS: According to the computer simulation the number of cells engrafting must vary considerably to explain the different weights of the primary tumor at the end of the experiment. Once a primary tumor is established, the fractal dimension of its vasculature correlates with the tumor size. Furthermore, the fractal dimension of the tumor vasculature changes during treatment, indicating that the therapy affects the blood vessels' geometry. We corroborated these findings with a quantitative histological analysis showing that the blood vessel density is depleted during radiotherapy and cisplatin chemotherapy. The CaTSiT computer model reveals that chemotherapy influences the tumor's therapeutic susceptibility and its metastatic spreading behavior. CONCLUSION: Using a system biological approach in combination with xenograft models and computer simulations revealed that the usage of chemotherapy and radiation therapy determines the spreading behavior by changing the blood vessel geometry of the primary tumor.

Simulation of metastatic progression using a computer model including chemotherapy and radiation therapy.

INTRODUCTION: Despite considerable research efforts, the process of metastasis formation is still a subject of intense discussion, and even established models differ considerably in basic details and in the conclusions drawn from them. Mathematical and computational models add a new perspective to the research as they can quantitatively investigate the processes of metastasis and the effects of treatment. However, existing models look at only one treatment option at a time. METHODS: We enhanced a previously developed computer model (called CaTSiT) that enables quantitative comparison of different metastasis formation models with clinical and experimental data, to include the effects of chemotherapy, external beam radiation, radioimmunotherapy and radioembolization. CaTSiT is based on a discrete event simulation procedure. The growth of the primary tumor and its metastases is modeled by a piecewise-defined growth function that describes the growth behavior of the primary tumor and metastases during various time intervals. The piecewise-defined growth function is composed of analytical functions describing the growth behavior of the tumor based on characteristics of the tumor, such as dormancy, or the effects of various therapies. The spreading of malignant cells into the blood is modeled by intravasation events, which are generated according to a rate function. Further events in the model describe the behavior of the released malignant cells until the formation of a new metastasis. The model is published under the GNU General Public License version 3. RESULTS: To demonstrate the application of the computer model, a case of a patient with a hepatocellular carcinoma and multiple metastases in the liver was simulated. Besides the untreated case, different treatments were simulated at two time points: one directly after diagnosis of the primary tumor and the other several months later. Except for early applied radioimmunotherapy, no treatment strategy was able to eliminate all metastases. These results emphasize the importance of early diagnosis and of proceeding with treatment even if no clinically detectable metastases are present at the time of diagnosis of the primary tumor. CONCLUSION: CaTSiT could be a valuable tool for quantitative investigation of the process of tumor growth and metastasis formation, including the effects of various treatment options.

Affinity, stoichiometry and cooperativity of heterochromatin protein 1 (HP1) binding to nucleosomal arrays.

Heterochromatin protein 1 (HP1) participates in establishing and maintaining heterochromatin via its histone-modification-dependent chromatin interactions. In recent papers HP1 binding to nucleosomal arrays was measured in vitro and interpreted in terms of nearest-neighbour cooperative binding. This mode of chromatin interaction could lead to the spreading of HP1 along the nucleosome chain. Here, we reanalysed previous data by representing the nucleosome chain as a 1D binding lattice and showed how the experimental HP1 binding isotherms can be explained by a simpler model without cooperative interactions between neighboring HP1 dimers. Based on these calculations and spatial models of dinucleosomes and nucleosome chains, we propose that binding stoichiometry depends on the nucleosome repeat length (NRL) rather than protein interactions between HP1 dimers. According to our calculations, more open nucleosome arrays with long DNA linkers are characterized by a larger number of binding sites in comparison to chains with a short NRL. Furthermore, we demonstrate by Monte Carlo simulations that the NRL dependent folding of the nucleosome chain can induce allosteric changes of HP1 binding sites. Thus, HP1 chromatin interactions can be modulated by the change of binding stoichiometry and the type of binding to condensed (methylated) and non-condensed (unmethylated) nucleosome arrays in the absence of direct interactions between HP1 dimers.

Perforin-dependent direct cytotoxicity in natural killer cells induces considerable knockdown of spontaneous lung metastases and computer modelling-proven tumor cell dormancy in a HT29 human colon cancer xenograft mouse model.

BACKGROUND: For long, natural killer (NK) cells have been suspected to play a critical role in suppressing the development of spontaneous metastases in cancer patients. Despite a wide range of studies it remains unclear so far to what extent primary tumor growth together with formation of distant metastases and NK cell activity influence each other. METHODS: To precisely investigate the role of NK cells with a perforin-deficiency in cancer growth and metastasis formation, human HT29 colon cancer cells were subcutaneously grafted into pore forming protein and recombination activating gene 2 double knock out (pfp/rag2) mice and in recombination activating gene 2 only knock out (rag2) mice both with black six background. Both mice lack B and T cell functions due to the absence of rag2. RESULTS: Primary tumors developed in 16/16 in pfp/rag2 and 20/20 rag2 mice. At sacrifice primary tumor weight did not differ significantly. However, tumors grew faster in pfp/rag2 mice (50 days) than in pfp/rag2 mice (70 days). Circulating tumor cells (CTC) in murine blood were nearly three times higher in pfp/rag2 (68 cells/ml) than in rag2 mice (24 cells/ml). Lung metastases occurred frequently in pfp/rag2 mice (13/16) and infrequently in rag2 mice (5/20). The mean number of metastases was 789 in pfp/rag2 mice compared to 210 in rag2 mice. Lung metastases in pfp/rag2 mice consisted of 10-100 tumor cells while those in rag2 mice were generally disseminated tumor cells (DTCs).Computer modelling showed that perforin-dependent killing of NK cells decelerates the growth of the primary tumour and kills 80% of CTCs. Furthermore, perforin-mediated cytotoxicity hampers the proliferation of the malignant cells in host tissue forcing them to stay dormant for at least 30 days. CONCLUSION: The results exactly quantified the effect of perforin-dependent direct cytotoxicity of NK cells on HT29 on primary tumor growth, number of CTCs in the blood and the number of metastases. The largest effects were seen in the number of mice developing spontaneous lung metastases and the mean number of lung metastases. Hence, perforin-mediated cytotoxicity used for direct killing by NK cells is more important than indirect killing by secretion of death-inducing ligands by NK cells.

Changing chromatin fiber conformation by nucleosome repositioning.

Chromatin conformation is dynamic and heterogeneous with respect to nucleosome positions, which can be changed by chromatin remodeling complexes in the cell. These molecular machines hydrolyze ATP to translocate or evict nucleosomes, and establish loci with regularly and more irregularly spaced nucleosomes as well as nucleosome-depleted regions. The impact of nucleosome repositioning on the three-dimensional chromatin structure is only poorly understood. Here, we address this issue by using a coarse-grained computer model of arrays of 101 nucleosomes considering several chromatin fiber models with and without linker histones, respectively. We investigated the folding of the chain in dependence of the position of the central nucleosome by changing the length of the adjacent linker DNA in basepair steps. We found in our simulations that these translocations had a strong effect on the shape and properties of chromatin fibers: i), Fiber curvature and flexibility at the center were largely increased and long-range contacts between distant nucleosomes on the chain were promoted. ii), The highest destabilization of the fiber conformation occurred for a nucleosome shifted by two basepairs from regular spacing, whereas effects of linker DNA changes of ?10 bp in phase with the helical twist of DNA were minimal. iii), A fiber conformation can stabilize a regular spacing of nucleosomes inasmuch as favorable stacking interactions between nucleosomes are facilitated. This can oppose nucleosome translocations and increase the energetic costs for chromatin remodeling. Our computational modeling framework makes it possible to describe the conformational heterogeneity of chromatin in terms of nucleosome positions, and thus advances theoretical models toward a better understanding of how genome compaction and access are regulated within the cell.

Computer simulation of the metastatic progression.

A novel computer model based on a discrete event simulation procedure describes quantitatively the processes underlying the metastatic cascade. Analytical functions describe the size of the primary tumor and the metastases, while a rate function models the intravasation events of the primary tumor and metastases. Events describe the behavior of the malignant cells until the formation of new metastases. The results of the computer simulations are in quantitative agreement with clinical data determined from a patient with hepatocellular carcinoma in the liver. The model provides a more detailed view on the process than a conventional mathematical model. In particular, the implications of interventions on metastasis formation can be calculated.

TNFα signalling primes chromatin for NF-κB binding and induces rapid and widespread nucleosome repositioning.

BACKGROUND: The rearrangement of nucleosomes along the DNA fiber profoundly affects gene expression, but little is known about how signalling reshapes the chromatin landscape, in three-dimensional space and over time, to allow establishment of new transcriptional programs. RESULTS: Using micrococcal nuclease treatment and high-throughput sequencing, we map genome-wide changes in nucleosome positioning in primary human endothelial cells stimulated with tumour necrosis factor alpha (TNFα) - a proinflammatory cytokine that signals through nuclear factor kappa-B (NF-κB). Within 10 min, nucleosomes reposition at regions both proximal and distal to NF-κB binding sites, before the transcription factor quantitatively binds thereon. Similarly, in long TNFα-responsive genes, repositioning precedes transcription by pioneering elongating polymerases and appears to nucleate from intragenic enhancer clusters resembling super-enhancers. By 30 min, widespread repositioning throughout megabase pair-long chromosomal segments, with consequential effects on three-dimensional structure (detected using chromosome conformation capture), is seen. CONCLUSIONS: Whilst nucleosome repositioning is viewed as a local phenomenon, our results point to effects occurring over multiple scales. Here, we present data in support of a TNFα-induced priming mechanism, mostly independent of NF-κB binding and/or elongating RNA polymerases, leading to a plastic network of interactions that affects DNA accessibility over large domains.

Modeling nucleosome position distributions from experimental nucleosome positioning maps.

MOTIVATION: Recent experimental advancements allow determining positions of nucleosomes for complete genomes. However, the resulting nucleosome occupancy maps are averages of heterogeneous cell populations. Accordingly, they represent a snapshot of a dynamic ensemble at a single time point with an overlay of many configurations from different cells. To study the organization of nucleosomes along the genome and to understand the mechanisms of nucleosome translocation, it is necessary to retrieve features of specific conformations from the population average. RESULTS: Here, we present a method for identifying non-overlapping nucleosome configurations that combines binary-variable analysis and a Monte Carlo approach with a simulated annealing scheme. In this manner, we obtain specific nucleosome configurations and optimized solutions for the complex positioning patterns from experimental data. We apply the method to compare nucleosome positioning at transcription factor binding sites in different mouse cell types. Our method can model nucleosome translocations at regulatory genomic elements and generate configurations for simulations of the spatial folding of the nucleosome chain. AVAILABILITY: Source code, precompiled binaries, test data and a web-based test installation are freely available at http://bioinformatics.fh-stralsund.de/nucpos/

Probing the elasticity of DNA on short length scales by modeling supercoiling under tension.

The wormlike-chain (WLC) model is widely used to describe the energetics of DNA bending. Motivated by recent experiments, alternative, so-called subelastic chain models were proposed that predict a lower elastic energy of highly bent DNA conformations. Until now, no unambiguous verification of these models has been obtained because probing the elasticity of DNA on short length scales remains challenging. Here we investigate the limits of the WLC model using coarse-grained Monte Carlo simulations to model the supercoiling of linear DNA molecules under tension. At a critical supercoiling density, the DNA extension decreases abruptly due to the sudden formation of a plectonemic structure. This buckling transition is caused by the large energy required to form the tightly bent end-loop of the plectoneme and should therefore provide a sensitive benchmark for model evaluation. Although simulations based on the WLC energetics could quantitatively reproduce the buckling measured in magnetic tweezers experiments, the buckling almost disappears for the tested linear subelastic chain model. Thus, our data support the validity of a harmonic bending potential even for small bending radii down to 3.5 nm.

Are metastases from metastases clinical relevant? Computer modelling of cancer spread in a case of hepatocellular carcinoma.

BACKGROUND: Metastasis formation remains an enigmatic process and one of the main questions recently asked is whether metastases are able to generate further metastases. Different models have been proposed to answer this question; however, their clinical significance remains unclear. Therefore a computer model was developed that permits comparison of the different models quantitatively with clinical data and that additionally predicts the outcome of treatment interventions. METHODS: The computer model is based on discrete events simulation approach. On the basis of a case from an untreated patient with hepatocellular carcinoma and its multiple metastases in the liver, it was evaluated whether metastases are able to metastasise and in particular if late disseminated tumour cells are still capable to form metastases. Additionally, the resection of the primary tumour was simulated. The simulation results were compared with clinical data. RESULTS: The simulation results reveal that the number of metastases varies significantly between scenarios where metastases metastasise and scenarios where they do not. In contrast, the total tumour mass is nearly unaffected by the two different modes of metastasis formation. Furthermore, the results provide evidence that metastasis formation is an early event and that late disseminated tumour cells are still capable of forming metastases. Simulations also allow estimating how the resection of the primary tumour delays the patient's death. CONCLUSION: The simulation results indicate that for this particular case of a hepatocellular carcinoma late metastases, i.e., metastases from metastases, are irrelevant in terms of total tumour mass. Hence metastases seeded from metastases are clinically irrelevant in our model system. Only the first metastases seeded from the primary tumour contribute significantly to the tumour burden and thus cause the patient's death.

Dissecting DNA-histone interactions in the nucleosome by molecular dynamics simulations of DNA unwrapping.

The nucleosome complex of DNA wrapped around a histone protein octamer organizes the genome of eukaryotes and regulates the access of protein factors to the DNA. We performed molecular dynamics simulations of the nucleosome in explicit water to study the dynamics of its histone-DNA interactions. A high-resolution histone-DNA interaction map was derived that revealed a five-nucleotide periodicity, in which the two DNA strands of the double helix made alternating contacts. On the 100-ns timescale, the histone tails mostly maintained their initial positions relative to the DNA, and the spontaneous unwrapping of DNA was limited to 1-2 basepairs. In steered molecular dynamics simulations, external forces were applied to the linker DNA to investigate the unwrapping pathway of the nucleosomal DNA. In comparison with a nucleosome without the unstructured N-terminal histone tails, the following findings were obtained: 1), Two main barriers during unwrapping were identified at DNA position ±70 and ±45 basepairs relative to the central DNA basepair at the dyad axis. 2), DNA interactions of the histone H3 N-terminus and the histone H2A C-terminus opposed the initiation of unwrapping. 3), The N-terminal tails of H2A, H2B, and H4 counteracted the unwrapping process at later stages and were essential determinants of nucleosome dynamics. Our detailed analysis of DNA-histone interactions revealed molecular mechanisms for modulating access to nucleosomal DNA via conformational rearrangements of its structure.

Force spectroscopy of chromatin fibers: extracting energetics and structural information from Monte Carlo simulations.

The folding of the nucleosome chain into a chromatin fiber is a central factor for controlling the DNA access of protein factors involved in transcription, DNA replication and repair. Force spectroscopy experiments with chromatin fibers are ideally suited to dissect the interactions that drive this process, and to probe the underlying fiber conformation. However, the interpretation of the experimental data is fraught with difficulties due to the complex interplay of the nucleosome geometry and the different energy terms involved. Here, we apply a Monte Carlo simulation approach to derive virtual chromatin fiber force spectroscopy curves. In the simulations, the effect of the nucleosome geometry, repeat length, nucleosome-nucleosome interaction potential, and the unwrapping of the DNA from the histone protein core on the shape of the force-extension curves was investigated. These simulations provide a framework for the evaluation of experimental data sets. We demonstrate how the relative contributions of DNA bending and twisting, nucleosome unstacking and unwrapping the nucleosomal DNA from the histone octamer can be dissected for a given fiber geometry.

Parallel high-performance grid computing: capabilities and opportunities of a novel demanding service and business class allowing highest resource efficiency.

Especially in the life-science and the health-care sectors the huge IT requirements are imminent due to the large and complex systems to be analysed and simulated. Grid infrastructures play here a rapidly increasing role for research, diagnostics, and treatment, since they provide the necessary large-scale resources efficiently. Whereas grids were first used for huge number crunching of trivially parallelizable problems, increasingly parallel high-performance computing is required. Here, we show for the prime example of molecular dynamic simulations how the presence of large grid clusters including very fast network interconnects within grid infrastructures allows now parallel high-performance grid computing efficiently and thus combines the benefits of dedicated super-computing centres and grid infrastructures. The demands for this service class are the highest since the user group has very heterogeneous requirements: i) two to many thousands of CPUs, ii) different memory architectures, iii) huge storage capabilities, and iv) fast communication via network interconnects, are all needed in different combinations and must be considered in a highly dedicated manner to reach highest performance efficiency. Beyond, advanced and dedicated i) interaction with users, ii) the management of jobs, iii) accounting, and iv) billing, not only combines classic with parallel high-performance grid usage, but more importantly is also able to increase the efficiency of IT resource providers. Consequently, the mere "yes-we-can" becomes a huge opportunity like e.g. the life-science and health-care sectors as well as grid infrastructures by reaching higher level of resource efficiency.

Exploring the conformational space of chromatin fibers and their stability by numerical dynamic phase diagrams.

The three-dimensional structure of chromatin affects DNA accessibility and is therefore a key regulator of gene expression. However, the path of the DNA between consecutive nucleosomes, and the resulting chromatin fiber organization remain controversial. The conformational space available for the folding of the nucleosome chain has been analytically described by phase diagrams with a two-angle model, which describes the chain trajectory by a DNA entry-exit angle at the nucleosome and a torsion angle between consecutive nucleosomes. Here, a novel type of numerical phase diagrams is introduced that relates the geometric phase space to the energy associated with a given chromatin conformation. The resulting phase diagrams revealed differences in the energy landscape that reflect the probability of a given conformation to form in thermal equilibrium. Furthermore, we investigated the effects of entropy and additional degrees of freedom in the dynamic phase diagrams by performing Monte Carlo simulations of the initial chain trajectories. Using our approach, we were able to demonstrate that conformations that initially were geometrically impossible could evolve into energetically favorable states in thermal equilibrium due to DNA bending and torsion. In addition, dynamic phase diagrams were applied to identify chromatin fibers that reflect certain experimentally determined features.