Critical role of PI3-K/Akt/GSK-3(5 signaling pathway in recovery from anthrax lethal toxin-induced cell cycle arrest and MEK cleavage in macrophages

Lethal toxin (LeTx) is a critical virulence factor of B. anthracis causing immune suppression and toxic shock of the infected host. It inhibits cytokine production and cell proliferation/differentiation in various immune cells. In the present study, I demonstrated that a brief exposure to LeTx caused a continual MEK1 cleavage and prevented TNF-ce production in non-proliferating cells such as human peripheral blood mononuclear cells or mouse primary peritoneal macrophages. In human monocytic cell lines U-937 and THP-1, LeTx induced cell cycle arrest in Go-Gi phase by rapid down-regulation of cyclin D1/D2 and checkpoint kinase 1 through MEK1 inhibition. However, THP-1 cells adaptively adjusted to LeTx and overrode cell cycle arrest by activating the PI3K/Akt signaling pathway. Activated Akt inhibited GSK3 and prevented proteasome-mediated cyclin D1 degradation in LeTx-intoxicated THP-1 cells. Recovery from cell cycle arrest was required before recovering from on-going MEK1 cleavage and suppression of TNF-a production. This study demonstrated that modulation of PI3K/Akt/GSK3 signaling cascades can be beneficial for protecting or facilitating recovery from cellular LeTx intoxication in cells that depend on basal MEK1 activity for proliferation

Critical role of PI3-K∕Akt∕GSK-3β signaling pathway in recovery from anthrax lethal toxin-induced cell cycle arrest and MEK cleavage in macrophages

Lethal toxin (LeTx) is a critical virulence factor of B. anthracis causing immune suppression and toxic shock of the infected host. It inhibits cytokine production and cell proliferation/differentiation in various immune cells. In the present study, I demonstrated that a brief exposure to LeTx caused a continual MEKl cleavage and prevented TNF-α production in non-proliferating cells such as human peripheral blood mononuclear cells or mouse primary peritoneal macrophages. In human monocytic cell lines U-937 and THP-1, LeTx induced cell cycle arrest in G0-Gι phase by rapid down-regulation of cyclin D1∕D2 and checkpoint kinase 1 through MEKl inhibition. However, THP-1 cells adaptively adjusted to LeTx and overrode cell cycle arrest by activating the PI3K∕Akt signaling pathway. Activated Akt inhibited GSK3 and prevented proteasome-mediated cyclin D1 degradation in LeTx-intoxicated THP-1 cells. Recovery from cell cycle arrest was required before recovering from on-going MEKl cleavage and suppression of TNF-α production. This study demonstrated that modulation of PI3K∕Akt∕GSK3 signaling cascades can be beneficial for protecting or facilitating recovery from cellular LeTx intoxication in cells that depend on basal MEKl activity for proliferation

The role of model dynamics in ensemble Kalman filter performance for chaotic systems

The ensemble Kalman filter (EnKF) is susceptible to losing track of observations, or ‘diverging’, when applied to large chaotic systems such as atmospheric and ocean models. Past studies have demonstrated the adverse impact of sampling error during the filter’s update step. We examine how system dynamics affect EnKF performance, and whether the absence of certain dynamic features in the ensemble may lead to divergence. The EnKF is applied to a simple chaotic model, and ensembles are checked against singular vectors of the tangent linear model, corresponding to short-term growth and Lyapunov vectors, corresponding to long-term growth. Results show that the ensemble strongly aligns itself with the subspace spanned by unstable Lyapunov vectors. Furthermore, the filter avoids divergence only if the full linearized long-term unstable subspace is spanned. However, short-term dynamics also become important as nonlinearity in the system increases. Non-linear movement prevents errors in the long-term stable subspace from decaying indefinitely. If these errors then undergo linear intermittent growth, a small ensemble may fail to properly represent all important modes, causing filter divergence. A combination of long and short-term growth dynamics are thus critical to EnKF performance. These findings can help in developing practical robust filters based on model dynamics.National Science Foundation (U.S.) (CMF Program Grant 0530851)National Science Foundation (U.S.) (DDAS Program Grant 0540259)National Science Foundation (U.S.) (ITR/AP Program Grant 0121182