Oscillations in MAPK cascade triggered by two distinct designs of coupled positive and negative feedback loops

ABSTRACT: BACKGROUND: Feedback loops, both positive and negative are embedded in the Mitogen Activated Protein Kinase (MAPK) cascade. In the three layer MAPK cascade, both feedback loops originate from the terminal layer and their sites of action are either of the two upstream layers. Recent studies have shown that the cascade uses coupled positive and negative feedback loops in generating oscillations. Two plausible designs of coupled positive and negative feedback loops can be elucidated from the literature; in one design the positive feedback precedes the negative feedback in the direction of signal flow and vice-versa in another. But it remains unexplored how the two designs contribute towards triggering oscillations in MAPK cascade. Thus it is also not known how amplitude, frequency, robustness or nature (analogous/digital) of the oscillations would be shaped by these two designs. RESULTS: We built two models of MAPK cascade that exhibited oscillations as function of two underlying designs of coupled positive and negative feedback loops. Frequency, amplitude and nature (digital/analogous) of oscillations were found to be differentially determined by each design. It was observed that the positive feedback emerging from an oscillating MAPK cascade and functional in an external signal processing module can trigger oscillations in the target module, provided that the target module satisfy certain parametric requirements. The augmentation of the two models was done to incorporate the nuclear-cytoplasmic shuttling of cascade components followed by induction of a nuclear phosphatase. It revealed that the fate of oscillations in the MAPK cascade is governed by the feedback designs. Oscillations were unaffected due to nuclear compartmentalization owing to one design but were completely abolished in the other case. CONCLUSION: The MAPK cascade can utilize two distinct designs of coupled positive and negative feedback loops to trigger oscillations. The amplitude, frequency and robustness of the oscillations in presence or absence of nuclear compartmentalization were differentially determined by two designs of coupled positive and negative feedback loops. A positive feedback from an oscillating MAPK cascade was shown to induce oscillations in an external signal processing module, uncovering a novel regulatory aspect of MAPK signal processing.     

Contributions of the σW, σM and σX regulons to the lantibiotic resistome of Bacillus subtilis

In Bacillus subtilis, the extracytoplasmic function (ECF) σ factors σ^M, σ^W and σ^X all contribute to resistance against lantibiotics. Nisin, a model lantibiotic, has a dual mode of action: it inhibits cell wall synthesis by binding lipid II, and this complex also forms pores in the cytoplasmic membrane. These activities can be separated in a nisin hinge‐region variant (N20P M21P) that binds lipid II, but no longer permeabilizes membranes. The major contribution of σ^M to nisin resistance is expression of ltaSa, encoding a stress‐activated lipoteichoic acid synthase, and σ^X functions primarily by activation of the dlt operon controlling d ‐alanylation of teichoic acids. Together, σ^M and σ^X regulate cell envelope structure to decrease access of nisin to its lipid II target. In contrast, σ^W is principally involved in protection against membrane permeabilization as it provides little protection against the nisin hinge region variant. σ^W contributes to nisin resistance by regulation of a signal peptide peptidase (SppA), phage shock proteins (PspA and YvlC, a PspC homologue) and tellurite resistance related proteins (YceGHI). These defensive mechanisms are also effective against other lantibiotics such as mersacidin, gallidermin and subtilin and comprise an important subset of the intrinsic antibiotic resistome of B. subtilis.     

π–π Stacking mediated drug–drug interactions in human CYP2E1

Because of having many low molecular mass substrates, CYP2E1 is of particular interests to the pharmaceutical industry. Many evidences showed that this enzyme can adopt multiple substrates to significantly reduce the oxidation rate of the substrates. The detailed mechanism for this observation is still unclear. In the current study, we employed GPU‐accelerated molecular dynamics simulations to study the multiple‐binding mode of human CYP2E1, with an aim of offering a mechanistic explanation for the unexplained multiple‐substrate binding. Our results showed that Thr303 and Phe478 were key factors for the substrate recognition and multiple‐substrate binding. The former can form a significant hydrogen bond to recognize and position the substrate in the productive binding orientation in the active site. The latter acted as a mediator for the substrate communications via π–π stacking interactions. In the multiple‐binding mode, the aforementioned π–π stacking interactions formed by the aromatic rings of both substrates and Phe478 drove the first substrate far away from the catalytic center, orienting in an additional binding position and going against the substrate metabolism. All these findings could give atomic insights into the detailed mechanism for the multiple‐substrate binding in human CYP2E1, providing useful information for the drug metabolism mechanism and personalized use of clinical drugs. Proteins 2013; © 2012 Wiley Periodicals, Inc.     

Effect of positive feedback loops on the robustness of oscillations in the network of cyclin-dependent kinases driving the mammalian cell cycle

The transitions between the G(1) , S, G(2) and M phases of the mammalian cell cycle are driven by a network of cyclin-dependent kinases (Cdks), whose sequential activation is regulated by intertwined negative and positive feedback loops. We previously proposed a detailed computational model for the Cdk network, and showed that this network is capable of temporal self-organization in the form of sustained oscillations, which govern ordered progression through the successive phases of the cell cycle [Gérard and Goldbeter (2009) Proc Natl Acad Sci USA106, 21643-21648]. We subsequently proposed a skeleton model for the cell cycle that retains the core regulatory mechanisms of the detailed model [Gérard and Goldbeter (2011) Interface Focus1, 24-35]. Here we extend this skeleton model by incorporating Cdk regulation through phosphorylation/dephosphorylation and by including the positive feedback loops that underlie the dynamics of the G(1) /S and G(2) /M transitions via phosphatase Cdc25 and via phosphatase Cdc25 and kinase Wee1, respectively. We determine the effects of these positive feedback loops and ultrasensitivity in phosphorylation/dephosphorylation on the dynamics of the Cdk network. The multiplicity of positive feedback loops as well as the existence of ultrasensitivity promote the occurrence of bistability and increase the amplitude of the oscillations in the various cyclin/Cdk complexes. By resorting to stochastic simulations, we further show that the presence of multiple, redundant positive feedback loops in the G(2) /M transition of the cell cycle markedly enhances the robustness of the Cdk oscillations with respect to molecular noise.     

Progesterone blockade of the positive feedback effects of 17β oestradiol in the ewe

Ovariectomized ewes (n = 24) were treated with implants that resulted in circulating concentrations of progesterone and 17β-oestradiol similar to those seen in intact ewes in the luteal phase of an oestrous cycle. Progesterone implants were left in for 10 days, and 17β-oestradiol implants for 14 days. Twelve of these ewes received daily injections of 17β-oestradiol in oil (i.m.) at doses sufficient to cause a surge release of luteinizing hormone (LH) in the absence of progesterone. The other 12 ewes were treated daily with vehicle (oil). Following progesterone withdrawal on Day 10, each group of 12 ewes was divided into three subgroups. Ewes in each subgroup of the groups treated daily with 17β-oestradiol or vehicle, received an injection of either 17β-oestradiol (oil i.m.), gonadotrophin-releasing hormone (GnRH) (saline, i.v.) or vehicle, 24 h after progesterone withdrawal. Following progesterone withdrawal, no LH surge was detected in ewes treated with vehicle. Surge secretion of LH was detected in ewes of all other groups. The data suggested that in progesterone-treated ewes, daily exposure to stimulatory doses of 17β-oestradiol did not desensitize the hypothalamic pituitary axis to the positive feedback effects of 17β-oestradiol. Daily exposure to 17β-oestradiol did not suppress pituitary responsiveness to GnRH. It was concluded that circulating concentrations of progesterone, similar to those seen during the luteal phase of an oestrous cycle in intact ewes, may prevent all necessary components of the LH surge secretory mechanism from responding to 17β-oestradiol.     

The downward spiral: eco‐evolutionary feedback loops lead to the emergence of ‘elastic’ ranges

In times of severe environmental changes and resulting shifts in the geographical distribution of animal and plant species it is crucial to unravel the mechanisms responsible for the dynamics of species’ ranges. Without such a mechanistic understanding, reliable projections of future species distributions are difficult to derive. Species’ ranges may be highly dynamic. One particularly interesting phenomenon is range contraction following a period of expansion, referred to as ‘elastic’ behaviour. It has been proposed that this phenomenon occurs in habitat gradients, which are characterized by a negative cline in selection for dispersal from the range core towards the margin, as one may find, for example, with increasing patch isolation. Using individual‐based simulations and numerical analyses we show that Allee effects are an important determinant of range border elasticity. If only intra‐specific processes are considered, Allee effects are even a necessary condition for ranges to exhibit elastic behavior. The eco‐evolutionary interplay between dispersal evolution, Allee effects and habitat isolation leads to lower colonization probability and higher local extinction risk after range expansions, which result in an increasing amount of marginal sink patches and consequently, range contraction. We also demonstrate that the nature of the gradient is crucial for range elasticity. Gradients which do not select for lower dispersal at the margin than in the core (especially gradients in patch size, demographic stochasticity and extinction rate) do not lead to elastic range behavior. Thus, we predict that range contractions are likely to occur after periods of expansion for species living in gradients of increasing patch isolation, which suffer from Allee effects.     

Soluble CXCL16 promotes TNF‐α‐induced apoptosis in DLBCL via the AMAD10‐NF‐κB regulatory feedback loop

We had previously identified that the co‐expression of transmembrane CXCL16 (TM‐CXCL16) and its receptor CXCR6 is an independent risk factor for poor survival in patients with diffuse large B‐cell lymphoma (DLBCL). However, the impact of the soluble form of CXCL16 (sCXCL16) on the pathogenesis of DLBCL remains unknown. In the present study, the synergistic effect of sCXCL16 and tumor necrosis factor α (TNF‐α) on apoptosis in DLBCL cell lines (OCI‐LY8 and OCI‐LY10) was investigated in vitro. sCXCL16 reinforced TNF‐α‐mediated inhibition of DLBCL cell proliferation, as determined by the cell counting kit‐8 assay. The results of annexin V staining showed that sCXCL16 enhanced TNF‐α‐induced apoptosis in OCI‐LY8 and OCI‐LY10 cells through a death receptor‐caspase signaling pathway. The results of gene microarray suggested a significant upregulation of differentially expressed genes in the TNF signaling pathway. sCXCL16 increased the concentration of extracellular TNF‐α by binding to CXCR6 to activate the nuclear factor‐κB (NF‐κB) signaling pathway. TNF‐α also induced the secretion of sCXCL16 by increasing the expression of ADAM10, which is known to cleave TM‐CXCL16 to yield sCXCL16. Moreover, bioinformatics analysis revealed that elevated TNF‐α and ADAM10 expression levels in tumor tissues predicted better survival in patients with DLBCL. Thus, our study suggests that sCXCL16 enhances TNF‐α‐induced apoptosis of DLBCL cells, which may involve a positive feedback loop consisting of TNF‐α, ADAM10, sCXCL16, and members of the NF‐κB pathway. sCXCL16 and TNF‐α may be used as prognostic markers in the clinic, and their combinational use is a promising approach in the context of DLBCL therapy.     

Magnetic field exposure enhances mRNA expression of σ32 in E. coli

The mechanism of interaction between weak electromagnetic fields and cells is not understood. As a result, the health effect(s) induced by exposure to these fields remains unclear. In addition to questions relating to the site of initial magnetic field (MF) interactions, the nature of the cell's response to these perturbations is also unclear. We examined the hypothesis that the cells respond to MFs in a manner similar to other environmental stressors such as heat. Using the bacterium Escherichia coli, we examined the mRNA levels of σ³², a protein that interacts with RNA polymerase to help it recognize a variety of stress promoters in the cell. Our data show that the intracellular level of σ³² mRNA is enhanced following a 15-min exposure to a 60 Hz, 1.1 mT magnetic field. J. Cell. Biochem. 68:1–7, 1998. © 1998 Wiley-Liss, Inc.     

Beyond basins: φ,ψ preferences of a residue depend heavily on the φ,ψ values of its neighbors

The Ramachandran plot distributions of nonglycine residues from experimentally determined structures are routinely described as grouping into one of six major basins: β, P_II, α, α_L, ξ and γ'. Recent work describing the most common conformations adopted by pairs of residues in folded proteins [i.e., (φ,ψ)₂‐motifs] showed that commonly described major basins are not true single thermodynamic basins, but are composed of distinct subregions that are associated with various conformations of either the preceding or following neighbor residue. Here, as documentation of the extent to which the conformational preferences of a central residue are influenced by the conformations of its two neighbors, we present a set of φ,ψ‐plots that are delimited simultaneously by the φ,ψ‐angles of its neighboring residues on both sides. The level of influence seen here is typically greater than the influence associated with considering the identities of neighboring residues, implying that the use of this heretofore untapped information can improve the accuracy of structure prediction algorithms and low resolution protein structure refinement.