H2A.Z histone variants facilitate HDACi-dependent removal of H3.3K27M mutant protein in pediatric high-grade glioma cells

Diffuse intrinsic pontine gliomas (DIPGs) are deadly pediatric brain tumors, non-resectable due to brainstem localization and diffusive growth. Over 80% of DIPGs harbor a mutation in histone 3 (H3.3 or H3.1) resulting in a lysine-to-methionine substitution (H3K27M). Patients with DIPG have a dismal prognosis with no effective therapy. We show that histone deacetylase (HDAC) inhibitors lead to a significant reduction in the H3.3K27M protein (up to 80%) in multiple glioma cell lines. We discover that the SB939-mediated H3.3K27M loss is partially blocked by a lysosomal inhibitor, chloroquine. The H3.3K27M loss is facilitated by co-occurrence of H2A.Z, as evidenced by the knockdown of H2A.Z isoforms. Chromatin immunoprecipitation sequencing (ChIP-seq) analysis confirms the occupancy of H3.3K27M and H2A.Z at the same SB939-inducible genes. We discover a mechanism showing that HDAC inhibition in DIPG leads to pharmacological modulation of the oncogenic H3.3K27M protein levels. These findings show the possibility of directly targeting the H3.3K27M oncohistone.

Green chemistry principles for the synthesis of anti fungal active gum acacia-gold nanocomposite - natamycin (GA-AuNC-NT) against food spoilage fungal strain Aspergillus ochraceopealiformis and its marked Congo red dye adsorption efficacy

In this present study, a highly stable gum acacia -gold nanocomposite fabricated with food preservative agent natamycin (GA-AuNC-NT) was prepared via green science principles under in vitro conditions. Various characterisation techniques reveal highly stable structural, functional properties of the synthesised nanocomposite with marked antifungal activity and adsorption efficacy against congo red dye. The antifungal activity was investigated against the fungal strain Aspergillus ochraceopealiformis isolated from spoiled, expired bread. The well diffusion assay, fungal hyphae fragmentation assay and spore germination inhibition assay were used to determine the antifungal activity of the synthesised nanocomposite. Potential antifungal activity of the synthesised nanocomposite was confirmed by recording zone of inhibition, high rate of hyphae fragmentation and marked spore germination inhibition against the tested fungal strain. The molecular mechanism of antifungal activity was studied by measuring oxidative stress marker genes like catalase (CAT), superoxide dismutase (SOD), peroxidase (POD) induction adopting quantitative real-time polymerase chain reaction (q RT-PCR). Among the various treatment, a notable reduction in all the tested marker genes expression was recorded in the nanocomposite treated fungal strain. Release profile studies using different solvents reveals sustained or controlled release of natamycin at the increasing periods. The synthesised nanocomposite's high safety or biocompatibility was evaluated with the Wistar animal model by determining notable changes in behavioural, biochemical, haematological and histopathological parameters. The synthesised nanocomposite did not exhibit any undesirable changes in all the tested parameters confirming the marked biosafety or biocompatibility. The nanocomposite was coated on the bread packaging material. The effect of packaging on the proximate composition, antioxidative enzymes status, and fungal growth of bread samples incubated under the incubation period were studied. Fourier transform infrared spectroscopy (FTIR) and scanning electron microscopy (SEM) studies reveal that the nanocomposite was effectively coated on the packaging material without changing size, shape, and functional groups. No changes in the proximate composition and antioxidative enzymes of the packaged bread samples incubated under different incubation periods reveal the nanocomposite's marked safety. The complete absence of the fungal growth also indicates the uniqueness of the nanocomposite. Further, the sorption studies revealed the utilisation of Langmuir mechanism and pseudo II order model successfully The present finding implies that the synthesised nanocomposite can be used as an effective, safe food preservative agent and adsorbent of toxic chemicals.

Emerging Advances in Combinatorial Treatments of Epigenetically Altered Pediatric High-Grade H3K27M Gliomas

Somatic mutations in histone encoding genes result in gross alterations in the epigenetic landscape. Diffuse intrinsic pontine glioma (DIPG) is a pediatric high-grade glioma (pHGG) and one of the most challenging cancers to treat, with only 1% surviving for 5 years. Due to the location in the brainstem, DIPGs are difficult to resect and rapidly turn into a fatal disease. Over 80% of DIPGs confer mutations in genes coding for histone 3 variants (H3.3 or H3.1/H3.2), with lysine to methionine substitution at position 27 (H3K27M). This results in a global decrease in H3K27 trimethylation, increased H3K27 acetylation, and widespread oncogenic changes in gene expression. Epigenetic modifying drugs emerge as promising candidates to treat DIPG, with histone deacetylase (HDAC) inhibitors taking the lead in preclinical and clinical studies. However, some data show the evolving resistance of DIPGs to the most studied HDAC inhibitor panobinostat and highlight the need to further investigate its mechanism of action. A new forceful line of research explores the simultaneous use of multiple inhibitors that could target epigenetically induced changes in DIPG chromatin and enhance the anticancer response of single agents. In this review, we summarize the therapeutic approaches against H3K27M-expressing pHGGs focused on targeting epigenetic dysregulation and highlight promising combinatorial drug treatments. We assessed the effectiveness of the epigenetic drugs that are already in clinical trials in pHGGs. The constantly expanding understanding of the epigenetic vulnerabilities of H3K27M-expressing pHGGs provides new tumor-specific targets, opens new possibilities of therapy, and gives hope to find a cure for this deadly disease.

Histone Modifying Enzymes and Chromatin Modifiers in Glioma Pathobiology and Therapy Responses

Signal transduction pathways directly communicate and transform chromatin to change the epigenetic landscape and regulate gene expression. Chromatin acts as a dynamic platform of signal integration and storage. Histone modifications and alteration of chromatin structure play the main role in chromatin-based gene expression regulation. Alterations in genes coding for histone modifying enzymes and chromatin modifiers result in malfunction of proteins that regulate chromatin modification and remodeling. Such dysregulations culminate in profound changes in chromatin structure and distorted patterns of gene expression. Gliomagenesis is a multistep process, involving both genetic and epigenetic alterations. Recent applications of next generation sequencing have revealed that many chromatin regulation-related genes, including ATRX, ARID1A, SMARCA4, SMARCA2, SMARCC2, BAF155 and hSNF5 are mutated in gliomas. In this review we summarize newly identified mechanisms affecting expression or functions of selected histone modifying enzymes and chromatin modifiers in gliomas. We focus on selected examples of pathogenic mechanisms involving ATRX, histone methyltransferase G9a, histone acetylases/deacetylases and chromatin remodeling complexes SMARCA2/4. We discuss the impact of selected epigenetics alterations on glioma pathobiology, signaling and therapeutic responses. We assess the attempts of targeting defective pathways with new inhibitors.

Antibiotics-Induced Obesity: A Mitochondrial Perspective

Antibiotics are the first line of treatment against infections and have contributed immensely to reduce the morbidity and mortality rates. Recently, extensive use of antibiotics has led to alterations of the gut microbiome, predisposition to various diseases and most importantly, increase in the emergence of antibiotic-resistant bacteria, which poses a major threat to global public health. Another major issue faced worldwide due to unregulated use of antibiotics in children as well as in adults is the influence of metabolism and body weight homeostasis, leading to obesity. Apart from the involvement of biosocial causes influencing diet, physical activity, and antibiotic use, pathogenesis of obesity is linked to interconnected functional alterations in cells, tissues and organs due to biochemical, epigenetic and genetic factors. Mitochondrial dysfunction is one such factor, which is becoming the primary focus of various aspects of research on multifactorial complex diseases and is providing new perspectives on etiology, biomarker-based diagnosis, and drug sensitivity. Through this review, we have made an attempt to present the interplay between use of antibiotics, obesity, and associated mitochondrial dysfunction. This may provide insights into the molecular basis, genetic predisposition and environmental triggers, which in turn may have potential clinical applications in the management of antibiotic use.

Hypermethylation of Death-Associated Protein Kinase (DAPK1) and its association with oral carcinogenesis - An experimental and meta-analysis study

OBJECTIVES

The value of abnormal DNA methylation of DAPK1 promoter and its association with various cancers have been suggested in the literature. To establish the significance of DNA methylation of DAPK1 promoter in oral squamous cell carcinoma (OSCC), we a) performed a case-control study, b) evaluated published data for its utility in the diagnosis and prognosis of OSCC and c) identified the association of DAPK1 gene expression with promoter DNA methylation status.

DESIGN

Bisulfite gene sequencing of DAPK1 promoter region was performed on non-malignant and malignant oral samples. Further, using a systematic search, 330 publications were retrieved from PubMed, Scopus, and Google Scholar and 11 relevant articles were identified.

RESULTS

Significant association of DAPK1 promoter methylation with OSCC (p<0.0001) was observed in the case-control study. The studies chosen for meta-analysis showed prognostic and predictive significance of DAPK1 gene promoter, despite defined inconsistencies in few studies. Overall, we obtained a statistically significant (p-value<0.001) association for both sensitivity and specificity of DAPK1 DNA promoter methylation in oral cancer cases, without publication bias.

CONCLUSION

DNA hypermethylation of DAPK1 gene promoter is a promising biomarker for OSCC prediction/prognostics and suggests further validation in large distinct cohorts to facilitate translation to clinics.

Gene promoter-associated CpG island hypermethylation in squamous cell carcinoma of the tongue

The present study was undertaken to explore and validate novel hypermethylated DNA regions in squamous cell carcinoma of the tongue (SCCT). Genome-wide methylation changes were identified by differential methylation hybridization (DMH) microarray and validated by bisulfite genome sequencing (BGS). The results were compared against datasets from The Cancer Genome Atlas head and neck squamous cell carcinoma (TCGA-HNSCC), Gene Expression Omnibus (GSE26549), and ArrayExpress (E-MTAB-1328). DMH identified 116 hypomethylated and 241 hypermethylated regions. Of the latter, 24 were localized to promoter or 5'-UTR regions. By BGS, promoter sequences of DAPK1, LRPPRC, RAB6C, and ZNF471 were significantly hypermethylated in tumors when compared with matched normal tissues (P < 0.0001). A TCGA-HNSCC dataset (516 cases of cancer and 50 normal tissue samples) further confirmed hypermethylation of DAPK1, RAB6C, and ZNF471. Sensitivity and specificity of methylation markers for a diagnosis of cancer were in the range of 70-100% in our study and from TCGA-HNSCC datasets, with an area under curve (AUC) of 0.83 and above. Kaplan-Meier survival analysis of TCGA-HNSCC expression data revealed that patients with low expressions of DAPK1, RAB6C, and ZNF471 showed poorer survival than patients with high expression (P = 0.02). Human papillomavirus (HPV) was found in 55% of cases, HPV16 being the predominant genotype. DAPK1 immunohistochemical staining was lower in SCCT than in normal buccal epithelial cells. This is the first study to report hypermethylation of LRPPRC, RAB6C, and ZNF471 in SCCT and its diagnostic and prognostic potentials in a specific head and neck squamous cell carcinoma.

Host-to-host variation of ecological interactions in polymicrobial infections

Host-to-host variability with respect to interactions between microorganisms and multicellular hosts are commonly observed in infection and in homeostasis. However, the majority of mechanistic models used to analyze host-microorganism relationships, as well as most of the ecological theories proposed to explain coevolution of hosts and microbes, are based on averages across a host population. By assuming that observed variations are random and independent, these models overlook the role of differences between hosts. Here, we analyze mechanisms underlying host-to-host variations of bacterial infection kinetics, using the well characterized experimental infection model of polymicrobial otitis media (OM) in chinchillas, in combination with population dynamic models and a maximum entropy (MaxEnt) based inference scheme. We find that the nature of the interactions between bacterial species critically regulates host-to-host variations in these interactions. Surprisingly, seemingly unrelated phenomena, such as the efficiency of individual bacterial species in utilizing nutrients for growth, and the microbe-specific host immune response, can become interdependent in a host population. The latter finding suggests a potential mechanism that could lead to selection of specific strains of bacterial species during the coevolution of the host immune response and the bacterial species.

Mixed Poisson distributions in exact solutions of stochastic autoregulation models

In this paper we study the interplay between stochastic gene expression and system design using simple stochastic models of autoactivation and autoinhibition. Using the Poisson representation, a technique whose particular usefulness in the context of nonlinear gene regulation models we elucidate, we find exact results for these feedback models in the steady state. Further, we exploit this representation to analyze the parameter spaces of each model, determine which dimensionless combinations of rates are the shape determinants for each distribution, and thus demarcate where in the parameter space qualitatively different behaviors arise. These behaviors include power-law-tailed distributions, bimodal distributions, and sub-Poisson distributions. We also show how these distribution shapes change when the strength of the feedback is tuned. Using our results, we reexamine how well the autoinhibition and autoactivation models serve their conventionally assumed roles as paradigms for noise suppression and noise exploitation, respectively.

Model of influenza A virus infection: dynamics of viral antagonism and innate immune response

Viral antagonism of host responses is an essential component of virus pathogenicity. The study of the interplay between immune response and viral antagonism is challenging due to the involvement of many processes acting at multiple time scales. Here we develop an ordinary differential equation model to investigate the early, experimentally measured, responses of human monocyte-derived dendritic cells to infection by two H1N1 influenza A viruses of different clinical outcomes: pandemic A/California/4/2009 and seasonal A/New Caledonia/20/1999. Our results reveal how the strength of virus antagonism, and the time scale over which it acts to thwart the innate immune response, differs significantly between the two viruses, as is made clear by their impact on the temporal behavior of a number of measured genes. The model thus sheds light on the mechanisms that underlie the variability of innate immune responses to different H1N1 viruses.

Regulating Brownian fluctuations with tunable microscopic magnetic traps

A major challenge to achieving positional control of fluid borne submicron sized objects is regulating their Brownian fluctuations. We present a magnetic-field-based trap that regulates the thermal fluctuations of superparamagnetic beads in suspension. Local domain-wall fields originating from patterned magnetic wires, whose strength and profile are tuned by weak external fields, enable the bead trajectories within the trap to be managed and easily varied between strong confinements and delocalized spatial excursions that are described remarkably well by simulations.

Stochasticity of gene products from transcriptional pulsing

Transcriptional pulsing has been observed in both prokaryotes and eukaryotes and plays a crucial role in cell-to-cell variability of protein and mRNA numbers. An important issue is how the time constants associated with episodes of transcriptional bursting and mRNA and protein degradation rates lead to different cellular mRNA and protein distributions, starting from the transient regime leading to the steady state. We address this by deriving and then investigating the exact time-dependent solution of the master equation for a transcriptional pulsing model of mRNA distributions. We find a plethora of results. We show that, among others, bimodal and long-tailed (power-law) distributions occur in the steady state as the rate constants are varied over biologically significant time scales. Since steady state may not be reached experimentally we present results for the time evolution of the distributions. Because cellular behavior is determined by proteins, we also investigate the effect of the different mRNA distributions on the corresponding protein distributions using numerical simulations.

Shared kinase fluctuations between two enzymatic reactions

Kinases serve crucial roles in many cellular signaling pathways that process and transfer information. When signaling kinases phosphorylate two targets, these can serve as branch points that distribute information among two pathways. Responses to stimuli transmitted by activated kinases show high levels of cell-to-cell variation that influence cellular function. We ask how fluctuations around a steady state, due to kinase fluctuations and intrinsic noise, are distributed between two reactions with substrates phosphorylated by a shared kinase. We develop the formalism to answer this question and, for a realistic set of biological constants, we illustrate various features of fluctuations and relaxation times to a steady state. We find that the steady-state response determines the size and range in enzyme concentration of phosphorylated substrate fluctuations, and that the choice of an operating point can have a large impact on how shared kinase noise is distributed among two available pathways.

Synchronization rates in classes of relaxation oscillators

Relaxation oscillators arise frequently in physics, electronics, mathematics, and biology. Their mathematical definitions possess a high degree of flexibility in the sense that through appropriate parameter choices relaxation oscillators can be made to exhibit qualitatively different kinds of oscillations. We study numerically four different classes of relaxation oscillators through their synchronization rates in one-dimensional chains with a Heaviside step function interaction and obtain the following results. Relaxation oscillators in the sinusoidal and relaxation regime both exhibit an average time to synchrony, <T(S)> approximately n, where n is the chain length. Relaxation oscillators in the singular limit exhibit <T(S)> approximately n(p), where p is a numerically obtained value less than 0.5. Relaxation oscillators in the singular limit with parameters modified so that they resemble spike oscillations exhibit <T(S)> approximately log(n) in chains and <T(S)> approximately log(L) in two-dimensional square networks of length L. Finally, using a sigmoid interaction results in <T(S)> approximately n(2), for relaxation oscillators in the sinusoidal and relaxation regimes, indicating that the form of the coupling is a controlling factor in the synchronization rate.

Self-organization and productivity in semi-arid ecosystems: implications of seasonality in rainfall

Spatial self-organization including striking vegetation patterns observed in arid ecosystems has been studied in models with uniform rainfall. In this paper, we present a fully seasonal rainfall model that produces vegetation patterns found in nature by including the natural adaptation of plants to scarcity of water and the consequent seasonal variation in their growth and metabolic rate. We present results for the mean-field and spatially extended versions of the model. We find that the patterns depend on the duration of the wet season even with fixed total annual precipitation (PPT) showing how seasonality affects spatial self-organization. We observe that the productivity can vary for fixed PPT as a function of the duration thereby providing another source of observed variations. We compute the maximum vegetation cover as function of PPT and find that the behavior is consistent with observations. We comment on the implications for regime shifts due to increased interannual fluctuations caused by climatic changes. Our specific model calculations provide more general conclusions for ecosystems with competition for scarce resources due to seasonal variations in the resource, especially for self-organization and productivity.

NF-kappaB oscillations and cell-to-cell variability

Oscillations in the transcriptional activator NF-kappaB localized in the nucleus have been observed when a cell is stimulated by an external agent. A negative feedback based on the protein IkappaB whose expression is controlled by NF-kappaB is known to be responsible for these oscillations. We study NF-kappaB oscillations, which have been observed both for cell populations by Hoffmann et al. [2002. The IkappaB-NF-kappaB signaling module: temporal control and selective gene activation. Science 298, 1241-1245] and for single cells by Nelson et al. [2004. Oscillations in NF-kappaB signaling control the dynamics of gene expression. Science 306, 704-708]. In order to study cell-to-cell variability we use Gillespie's algorithm, applied to a simplified version of the model proposed by Hoffmann et al. (2002). We consider the amounts of cellular NF-kappaB and activated IKK as external parameters. When these are fixed, we show that intrinsic fluctuations are small in a model with strong transcription, as is the case of the Hoffmann et al. (2002) model, whether transcription is quadratic or linear in the number of NF-kappaB molecules. Intrinsic fluctuations can however be large when transcription is weak, as we illustrate in a model variant. The effect of extrinsic fluctuations can be significant: cell-to-cell fluctuations of the initial amount of cellular NF-kappaB affect mainly the amplitude of nuclear NF-kappaB oscillations, at least when transcription is linear in the number of NF-kappaB molecules, while fluctuations in the amount of activated IKK affect both their amplitude and period, whatever the mode of transcription. In this case model results are in qualitative agreement with the considerable cell-to-cell variability of NF-kappaB oscillations observed by Nelson et al. (2004).

The linear noise approximation for molecular fluctuations within cells

We study the applicability of Van Kampen's linear noise approximation to the calculation of fluctuations in cells due to small number of molecules for simple genetic systems not previously considered. These systems include dimer formation and feedback. We explain why the linear noise approximation can be surprisingly effective, but also illustrate how it fails in a simple example when a protein probability distribution is not purely Gaussian.

A feedforward loop motif in transcriptional regulation: induction and repression

We study the dynamical behavior of a unit of three positive transcriptional regulators which occurs frequently in biological networks of yeast and bacteria as a feedforward loop. We investigate numerically a set of reactions incorporating the basic features of transcription and translation. We determine (i) how the feedforward loop motif functions as a computational element such as an AND gate in the presence of stochastic fluctuations, and (ii) the robustness of the motif when transcription at the primary level is suddenly repressed. We highlight the effective time-scales which underlie both of these aspects of the feedforward loop motif. We show how threshold behavior of the motif output arises as a function of the number of external inducers as well as the time over which the inducer acts. We discuss how individual cell behavior can deviate significantly from average behavior, due to intrinsic fluctuations in the small number of molecules present in a cell.

Fluctuations and slow variables in genetic networks

Computer simulations of large genetic networks are often extremely time consuming because, in addition to the biologically interesting translation and transcription reactions, many less interesting reactions like DNA binding and dimerizations have to be simulated. It is desirable to use the fact that the latter occur on much faster timescales than the former to eliminate the fast and uninteresting reactions and to obtain effective models of the slow reactions only. We use three examples of self-regulatory networks to show that the usual reduction methods where one obtains a system of equations of the Hill type fail to capture the fluctuations that these networks exhibit due to the small number of molecules; moreover, they may even miss describing the behavior of the average number of proteins. We identify the inclusion of fast-varying variables in the effective description as the cause for the failure of the traditional schemes. We suggest a different effective description, which entails the introduction of an additional species, not present in the original networks, that is slowly varying. We show that this description allows for a very efficient simulation of the reduced system while retaining the correct fluctuations and behavior of the full system. This approach ought to be applicable to a wide range of genetic networks.

The role of dimerization in noise reduction of simple genetic networks

Fluctuations are an intrinsic property of genetic networks due to the small number of interacting molecules. We study the role of dimerization reactions in controlling these fluctuations in a simple genetic circuit with negative feedback. We compare two different pathways. In the dimeric pathway the proteins to be regulated form dimers in solution that afterward bind to an operator site and inhibit transcription. In the monomeric pathway monomers bind to the operator site and then recruit another monomer to form a dimer directly on the DNA. We find that while both pathways implement the same negative feedback mechanism, the protein number fluctuations in the dimeric pathway are drastically reduced compared to the monomeric pathway. This difference in the ability to reduce fluctuations may be of importance in the design of genetic networks.

Scale-invariant behavior in a spatial game of prisoners' dilemma

A spatially extended version of the game of prisoner's dilemma, originally proposed by Nowak and May, is modified to include stochastic updating and found to exhibit scale-invariant behavior. Two critical regimes with different scaling behaviors are found; the corresponding exponents have been determined numerically. Spatially, the critical states are characterized by the existence of delicately balanced networks of defectors separating domains of cooperators; temporally, the evolution of the critical states following local perturbations is characterized by avalanches of various magnitudes, which cause restructuring of the networks of defectors on all scales.

Synchronization in Relaxation Oscillator Networks with Conduction Delays

We study locally coupled networks of relaxation oscillators with excitatory connections and conduction delays and propose a mechanism for achieving zero phase-lag synchrony. Our mechanism is based on the observation that different rates of motion along different nullclines of the system can lead to synchrony in the presence of conduction delays. We analyze the system of two coupled oscillators and derive phase compression rates. This analysis indicates how to choose nullclines for individual relaxation oscillators in order to induce rapid synchrony. The numerical simulations demonstrate that our analytical results extend to locally coupled networks with conduction delays and that these networks can attain rapid synchrony with appropriately chosen nullclines and initial conditions. The robustness of the proposed mechanism is verified with respect to different nullclines, variations in parameter values, and initial conditions.

Synchrony and desynchrony in integrate-and-fire oscillators

Due to many experimental reports of synchronous neural activity in the brain, there is much interest in understanding synchronization in networks of neural oscillators and its potential for computing perceptual organization. Contrary to Hopfield and Herz (1995), we find that networks of locally coupled integrate-and-fire oscillators can quickly synchronize. Furthermore, we examine the time needed to synchronize such networks. We observe that these networks synchronize at times proportional to the logarithm of their size, and we give the parameters used to control the rate of synchronization. Inspired by locally excitatory globally inhibitory oscillator network (LEGION) dynamics with relaxation oscillators (Terman & Wang, 1995), we find that global inhibition can play a similar role of desynchronization in a network of integrate-and-fire oscillators. We illustrate that a LEGION architecture with integrate-and-fire oscillators can be similarly used to address image analysis.

Singular Lyapunov spectra and conservation laws

We give analytic arguments and numerical evidence to show that the presence of conservation laws can produce a singularity in the spectrum of Lyapunov exponents for extended dynamical systems of low spatial dimensionality. This phenomenon can be used, e.g., for finding hidden conservation laws. (c) 1995 American Institute of Physics.