142 research outputs found

    Bmi-1 Absence Causes Premature Brain Degeneration

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    Bmi-1, a polycomb transcriptional repressor, is implicated in cell cycle regulation and cell senescence. Its absence results in generalized astrogliosis and epilepsy during the postnatal development, but the underlying mechanisms are poorly understood. Here, we demonstrate the occurrence of oxidative stress in the brain of four-week-old Bmi-1 null mice. The mice showed various hallmarks of neurodegeneration including synaptic loss, axonal demyelination, reactive gliosis and brain mitochondrial damage. Moreover, astroglial glutamate transporters and glutamine synthetase decreased in the Bmi-1 null hippocampus, which might contribute to the sporadic epileptic-like seizures in these mice. These results indicate that Bmi-1 is required for maintaining endogenous antioxidant defenses in the brain, and its absence subsequently causes premature brain degeneration

    Systematic Analysis of Stability Patterns in Plant Primary Metabolism

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    Metabolic networks are characterized by complex interactions and regulatory mechanisms between many individual components. These interactions determine whether a steady state is stable to perturbations. Structural kinetic modeling (SKM) is a framework to analyze the stability of metabolic steady states that allows the study of the system Jacobian without requiring detailed knowledge about individual rate equations. Stability criteria can be derived by generating a large number of structural kinetic models (SK-models) with randomly sampled parameter sets and evaluating the resulting Jacobian matrices. Until now, SKM experiments applied univariate tests to detect the network components with the largest influence on stability. In this work, we present an extended SKM approach relying on supervised machine learning to detect patterns of enzyme-metabolite interactions that act together in an orchestrated manner to ensure stability. We demonstrate its application on a detailed SK-model of the Calvin-Benson cycle and connected pathways. The identified stability patterns are highly complex reflecting that changes in dynamic properties depend on concerted interactions between several network components. In total, we find more patterns that reliably ensure stability than patterns ensuring instability. This shows that the design of this system is strongly targeted towards maintaining stability. We also investigate the effect of allosteric regulators revealing that the tendency to stability is significantly increased by including experimentally determined regulatory mechanisms that have not yet been integrated into existing kinetic models

    Functional Interaction of Nuclear Domain 10 and Its Components with Cytomegalovirus after Infections: Cross-Species Host Cells versus Native Cells

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    Species-specificity is one of the major characteristics of cytomegaloviruses (CMVs) and is the primary reason for the lack of a mouse model for the direct infection of human CMV (HCMV). It has been determined that CMV cross-species infections are blocked at the post-entry level by intrinsic cellular defense mechanisms, but few details are known. It is important to explore how CMVs interact with the subnuclear structure of the cross-species host cell. In our present study, we discovered that nuclear domain 10 (ND10) of human cells was not disrupted by murine CMV (MCMV) and that the ND10 of mouse cells was not disrupted by HCMV, although the ND10-disrupting protein, immediate-early protein 1 (IE1), also colocalized with ND10 in cross-species infections. In addition, we found that the UL131-repaired HCMV strain AD169 (vDW215-BADrUL131) can infect mouse cells to produce immediate-early (IE) and early (E) proteins but that neither DNA replication nor viral particles were detectable in mouse cells. Unrepaired AD169 can express IE1 only in mouse cells. In both HCMV-infected mouse cells and MCMV-infected human cells, the knocking-down of ND10 components (PML, Daxx, and SP100) resulted in significantly increased viral-protein production. Our observations provide evidence to support our hypothesis that ND10 and ND10 components might be important defensive factors against the CMV cross-species infection

    The route to transcription initiation determines the mode of transcriptional bursting in E. coli

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    Transcription is fundamentally noisy, leading to significant heterogeneity across bacterial populations. Noise is often attributed to burstiness, but the underlying mechanisms and their dependence on the mode of promotor regulation remain unclear. Here, we measure E. coli single cell mRNA levels for two stress responses that depend on bacterial sigma factors with different mode of transcription initiation (Οƒ70 and Οƒ54). By fitting a stochastic model to the observed mRNA distributions, we show that the transition from low to high expression of the Οƒ70-controlled stress response is regulated via the burst size, while that of the Οƒ54-controlled stress response is regulated via the burst frequency. Therefore, transcription initiation involving Οƒ54 differs from other bacterial systems, and yields bursting kinetics characteristic of eukaryotic systems

    Optimization of Time-Course Experiments for Kinetic Model Discrimination

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    Systems biology relies heavily on the construction of quantitative models of biochemical networks. These models must have predictive power to help unveiling the underlying molecular mechanisms of cellular physiology, but it is also paramount that they are consistent with the data resulting from key experiments. Often, it is possible to find several models that describe the data equally well, but provide significantly different quantitative predictions regarding particular variables of the network. In those cases, one is faced with a problem of model discrimination, the procedure of rejecting inappropriate models from a set of candidates in order to elect one as the best model to use for prediction

    Adjusting Phenotypes by Noise Control

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    Genetically identical cells can show phenotypic variability. This is often caused by stochastic events that originate from randomness in biochemical processes involving in gene expression and other extrinsic cellular processes. From an engineering perspective, there have been efforts focused on theory and experiments to control noise levels by perturbing and replacing gene network components. However, systematic methods for noise control are lacking mainly due to the intractable mathematical structure of noise propagation through reaction networks. Here, we provide a numerical analysis method by quantifying the parametric sensitivity of noise characteristics at the level of the linear noise approximation. Our analysis is readily applicable to various types of noise control and to different types of system; for example, we can orthogonally control the mean and noise levels and can control system dynamics such as noisy oscillations. As an illustration we applied our method to HIV and yeast gene expression systems and metabolic networks. The oscillatory signal control was applied to p53 oscillations from DNA damage. Furthermore, we showed that the efficiency of orthogonal control can be enhanced by applying extrinsic noise and feedback. Our noise control analysis can be applied to any stochastic model belonging to continuous time Markovian systems such as biological and chemical reaction systems, and even computer and social networks. We anticipate the proposed analysis to be a useful tool for designing and controlling synthetic gene networks

    Several Distinct Polycomb Complexes Regulate and Co-Localize on the INK4a Tumor Suppressor Locus

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    Misexpression of Polycomb repressive complex 1 (PRC1) components in human cells profoundly influences the onset of cellular senescence by modulating transcription of the INK4a tumor suppressor gene. Using tandem affinity purification, we find that CBX7 and CBX8, two Polycomb (Pc) homologs that repress INK4a, both participate in PRC1-like complexes with at least two Posterior sex combs (Psc) proteins, MEL18 and BMI1. Each complex contains a single representative of the Pc and Psc families. In primary human fibroblasts, CBX7, CBX8, MEL18 and BMI1 are present at the INK4a locus and shRNA-mediated knockdown of any one of these components results in de-repression of INK4a and proliferative arrest. Sequential chromatin immunoprecipitation (ChIP) reveals that CBX7 and CBX8 bind simultaneously to the same region of chromatin and knockdown of one of the Pc or Psc proteins results in release of the other, suggesting that the binding of PRC1 complexes is interdependent. Our findings provide the first evidence that a single gene can be regulated by several distinct PRC1 complexes and raise important questions about their configuration and relative functions

    Conservation performance of different conservation governance regimes in the Peruvian Amazon

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    State-controlled protected areas (PAs) have dominated conservation strategies globally, yet their performance relative to other governance regimes is rarely assessed comprehensively. Furthermore, performance indicators of forest PAs are typically restricted to deforestation, although the extent of forest degradation is greater. We address these shortfalls through an empirical impact evaluation of state PAs, Indigenous Territories (ITs), and civil society and private Conservation Concessions (CCs) on deforestation and degradation throughout the Peruvian Amazon. We integrated remote-sensing data with environmental and socio-economic datasets, and used propensity-score matching to assess: (i) how deforestation and degradation varied across governance regimes between 2006–2011; (ii) their proximate drivers; and (iii) whether state PAs, CCs and ITs avoided deforestation and degradation compared with logging and mining concessions, and the unprotected landscape. CCs, state PAs, and ITs all avoided deforestation and degradation compared to analogous areas in the unprotected landscape. CCs and ITs were on average more effective in this respect than state PAs, showing that local governance can be equally or more effective than centralized state regimes. However, there were no consistent differences between conservation governance regimes when matched to logging and mining concessions. Future impact assessments would therefore benefit from further disentangling governance regimes across unprotected land.This work was supported by the Economic and Social Research Council (grant number ES/I019650/1); Cambridge Political Economy Society; Cambridge Philosophical Society; St John’s College; and the Geography Department at the University of Cambridge
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