Unfair competition governs the interaction of pCPI-17 with myosin phosphatase (PP1-MYPT1).

The small phosphoprotein pCPI-17 inhibits myosin light-chain phosphatase (MLCP). Current models postulate that during muscle relaxation, phosphatases other than MLCP dephosphorylate and inactivate pCPI-17 to restore MLCP activity. We show here that such hypotheses are insufficient to account for the observed rapidity of pCPI-17 inactivation in mammalian smooth muscles. Instead, MLCP itself is the critical enzyme for pCPI-17 dephosphorylation. We call the mutual sequestration mechanism through which pCPI-17 and MLCP interact inhibition by unfair competition: MLCP protects pCPI-17 from other phosphatases, while pCPI-17 blocks other substrates from MLCP\u27s active site. MLCP dephosphorylates pCPI-17 at a slow rate that is, nonetheless, both sufficient and necessary to explain the speed of pCPI-17 dephosphorylation and the consequent MLCP activation during muscle relaxation

Efficient computation of the first passage time distribution of the generalized master equation by steady-state relaxation

The generalized master equation or the equivalent continuous time random walk equations can be used to compute the macroscopic first passage time distribution (FPTD) of a complex stochastic system from short-term microscopic simulation data. The computation of the mean first passage time and additional low-order FPTD moments can be simplified by directly relating the FPTD moment generating function to the moments of the local FPTD matrix. This relationship can be physically interpreted in terms of steady-state relaxation, an extension of steady-state flow. Moreover, it is amenable to a statistical error analysis that can be used to significantly increase computational efficiency. The efficiency improvement can be extended to the FPTD itself by modelling it using a Gamma distribution or rational function approximation to its Laplace transform

Sam68 exerts separable effects on cell cycle progression and apoptosis

BACKGROUND: The RNA-binding protein Sam68 has been implicated in a number of cellular processes, including transcription, RNA splicing and export, translation, signal transduction, cell cycle progression and replication of the human immunodeficiency virus and poliovirus. However, the precise impact it has on essential cellular functions remains largely obscure. RESULTS: In this report we show that conditional overexpression of Sam68 in fibroblasts results in both cell cycle arrest and apoptosis. Arrest in G1 phase of the cell cycle is associated with decreased levels of cyclins D1 and E RNA and protein, resulting in dramatically reduced Rb phosphorylation. Interestingly, cell cycle arrest does not require the specific RNA binding ability of Sam68. In marked contrast, induction of apoptosis by Sam68 absolutely requires a fully-functional RNA binding domain. Moreover, the anti-cancer agent trichostatin A potentiates Sam68-driven apoptosis. CONCLUSIONS: For the first time we have shown that Sam68, an RNA binding protein with multiple apparent functions, exerts functionally separable effects on cell proliferation and survival, dependent on its ability to bind specifically to RNA. These findings shed new light on the ability of signal transducing RNA binding proteins to influence essential cell function. Moreover, the ability of a class of anti-cancer therapeutics to modulate its ability to promote apoptosis suggests that Sam68 status may impact some cancer treatments

Macrostate Data Clustering

We develop an effective nonhierarchical data clustering method using an analogy to the dynamic coarse graining of a stochastic system. Analyzing the eigensystem of an interitem transition matrix identifies fuzzy clusters corresponding to the metastable macroscopic states (macrostates) of a diffusive system. A "minimum uncertainty criterion" determines the linear transformation from eigenvectors to cluster-defining window functions. Eigenspectrum gap and cluster certainty conditions identify the proper number of clusters. The physically motivated fuzzy representation and associated uncertainty analysis distinguishes macrostate clustering from spectral partitioning methods. Macrostate data clustering solves a variety of test cases that challenge other methods.Comment: keywords: cluster analysis, clustering, pattern recognition, spectral graph theory, dynamic eigenvectors, machine learning, macrostates, classificatio

Acetonitrile cluster solvation in a cryogenic ethane-methane-propane liquid: Implications for Titan lake chemistry

The atmosphere of Titan, Saturn’s largest moon, exhibits interesting UV- and radiation-driven chemistry between nitrogen and methane, resulting in dipolar, nitrile-containing molecules. The assembly and subsequent solvation of such molecules in the alkane lakes and seas found on the moon’s surface are of particular interest for investigating the possibility of prebiotic chemistry in Titan’s hydrophobic seas. Here we characterize the solvation of acetonitrile, a product of Titan’s atmospheric radiation chemistry tentatively detected on Titan’s surface [H. B. Niemann et al., Nature 438, 779–784 (2005)], in an alkane mixture estimated to match a postulated composition of the smaller lakes during cycles of active drying and rewetting. Molecular dynamics simulations are employed to determine the potential of mean force of acetonitrile (CH_3CN) clusters moving from the alkane vapor into the bulk liquid. We find that the clusters prefer the alkane liquid to the vapor and do not dissociate in the bulk liquid. This opens up the possibility that acetonitrile-based microscopic polar chemistry may be possible in the otherwise nonpolar Titan lakes

Density-dependent cooperative non-specific binding in solid-phase SELEX affinity selection

The non-specific binding of undesired ligands to a target is the primary factor limiting the enrichment of tight-binding ligands in affinity selection. Solution-phase non-specific affinity is determined by the free-energy of ligand binding to a single target. However, the solid-phase affinity might be higher if a ligand bound concurrently to multiple adjacent immobilized targets in a cooperative manner. Cooperativity could emerge in this case as a simple consequence of the relationship between the free energy of binding, localization entropy and the spatial distribution of the immobilized targets. We tested this hypothesis using a SELEX experimental design and found that non-specific RNA aptamer ligands can concurrently bind up to four bead-immobilized peptide targets, and that this can increase their effective binding affinity by two orders-of-magnitude. Binding curves were quantitatively explained by a new statistical mechanical model of density-dependent cooperative binding, which relates cooperative binding to both the target concentration and the target surface density on the immobilizing substrate. Target immobilization plays a key role in SELEX and other ligand enrichment methods, particularly in new multiplexed microfluidic purification devices, and these results have strong implications for optimizing their performance

Defining NELF-E RNA binding in HIV-1 and promoter-proximal pause regions

The four-subunit Negative Elongation Factor (NELF) is a major regulator of RNA Polymerase II (Pol II) pausing. The subunit NELF-E contains a conserved RNA Recognition Motif (RRM) and is proposed to facilitate Poll II pausing through its association with nascent transcribed RNA. However, conflicting ideas have emerged for the function of its RNA binding activity. Here, we use in vitro selection strategies and quantitative biochemistry to identify and characterize the consensus NELF-E binding element (NBE) that is required for sequence specific RNA recognition (NBE: CUGAGGA(U) for Drosophila). An NBE-like element is present within the loop region of the transactivation-response element (TAR) of HIV-1 RNA, a known regulatory target of human NELF-E. The NBE is required for high affinity binding, as opposed to the lower stem of TAR, as previously claimed. We also identify a non-conserved region within the RRM that contributes to the RNA recognition of Drosophila NELF-E. To understand the broader functional relevance of NBEs, we analyzed promoter-proximal regions genome-wide in Drosophila and show that the NBE is enriched +20 to +30 nucleotides downstream of the transcription start site. Consistent with the role of NELF in pausing, we observe a significant increase in NBEs among paused genes compared to non-paused genes. In addition to these observations, SELEX with nuclear run-on RNA enrich for NBE-like sequences. Together, these results describe the RNA binding behavior of NELF-E and supports a biological role for NELF-E in promoter-proximal pausing of both HIV-1 and cellular genes

Cell cycle-dependent activation of Ras

AbstractBackground Ras proteins play an essential role in the transduction of signals from a wide range of cell-surface receptors to the nucleus. These signals may promote cellular proliferation or differentiation, depending on the cell background. It is well established that Ras plays an important role in the transduction of mitogenic signals from activated growth-factor receptors, leading to cell-cycle entry. However, important questions remain as to whether Ras controls signalling events during cell-cycle progression and, if so, at which point in the cell-cycle it is activated.Results To address these questions we have developed a novel, functional assay for the detection of cellular activated Ras. Using this assay, we found that Ras was activated in HeLa cells, following release from mitosis, and in NIH 3T3 fibroblasts, following serum-stimulated cell-cycle entry. In each case, peak Ras activation occurred in mid-G1 phase. Ras activation in HeLa cells at mid-G1 phase was dependent on RNA and protein synthesis and was not associated with tyrosine phosphorylation of Shc proteins and their binding to Grb2. Significantly, activation of Ras and the extracellular-signal regulated (ERK) subgroup of mitogen-activated protein kinases were not temporally correlated during G1-phase progression.Conclusions Activation of Ras during mid-G1 phase appears to differ in many respects from its rapid activation by growth factors, suggesting a novel mechanism of regulation that may be intrinsic to cell-cycle progression. Furthermore, the temporal dissociation between Ras and ERK activation suggests that Ras targets alternate effector pathways during G1-phase progression