Clinically Available Medicines Demonstrating Anti-Toxoplasma Activity.

Toxoplasma gondii is an apicomplexan parasite of humans and other mammals, including livestock and companion animals. While chemotherapeutic regimens, including pyrimethamine and sulfadiazine regimens, ameliorate acute or recrudescent disease such as toxoplasmic encephalitis or ocular toxoplasmosis, these drugs are often toxic to the host. Moreover, no approved options are available to treat infected women who are pregnant. Lastly, no drug regimen has shown the ability to eradicate the chronic stage of infection, which is characterized by chemoresistant intracellular cysts that persist for the life of the host. In an effort to promote additional chemotherapeutic options, we now evaluate clinically available drugs that have shown efficacy in disease models but which lack clinical case reports. Ideally, less-toxic treatments for the acute disease can be identified and developed, with an additional goal of cyst clearance from human and animal hosts.

Integrating interactive computational modeling in biology curricula.

While the use of computer tools to simulate complex processes such as computer circuits is normal practice in fields like engineering, the majority of life sciences/biological sciences courses continue to rely on the traditional textbook and memorization approach. To address this issue, we explored the use of the Cell Collective platform as a novel, interactive, and evolving pedagogical tool to foster student engagement, creativity, and higher-level thinking. Cell Collective is a Web-based platform used to create and simulate dynamical models of various biological processes. Students can create models of cells, diseases, or pathways themselves or explore existing models. This technology was implemented in both undergraduate and graduate courses as a pilot study to determine the feasibility of such software at the university level. First, a new (In Silico Biology) class was developed to enable students to learn biology by "building and breaking it" via computer models and their simulations. This class and technology also provide a non-intimidating way to incorporate mathematical and computational concepts into a class with students who have a limited mathematical background. Second, we used the technology to mediate the use of simulations and modeling modules as a learning tool for traditional biological concepts, such as T cell differentiation or cell cycle regulation, in existing biology courses. Results of this pilot application suggest that there is promise in the use of computational modeling and software tools such as Cell Collective to provide new teaching methods in biology and contribute to the implementation of the "Vision and Change" call to action in undergraduate biology education by providing a hands-on approach to biology.

Design, Assessment, and in vivo Evaluation of a Computational Model Illustrating the Role of CAV1 in CD4(+) T-lymphocytes.

Caveolin-1 (CAV1) is a vital scaffold protein heterogeneously expressed in both healthy and malignant tissue. We focus on the role of CAV1 when overexpressed in T-cell leukemia. Previously, we have shown that CAV1 is involved in cell-to-cell communication, cellular proliferation, and immune synapse formation; however, the molecular mechanisms have not been elucidated. We hypothesize that the role of CAV1 in immune synapse formation contributes to immune regulation during leukemic progression, thereby warranting studies of the role of CAV1 in CD4(+) T-cells in relation to antigen-presenting cells. To address this need, we developed a computational model of a CD4(+) immune effector T-cell to mimic cellular dynamics and molecular signaling under healthy and immunocompromised conditions (i.e., leukemic conditions). Using the Cell Collective computational modeling software, the CD4(+) T-cell model was constructed and simulated under CAV1 (+/+), CAV1 (+/-), and CAV1 (-/-) conditions to produce a hypothetical immune response. This model allowed us to predict and examine the heterogeneous effects and mechanisms of CAV1 in silico. Experimental results indicate a signature of molecules involved in cellular proliferation, cell survival, and cytoskeletal rearrangement that were highly affected by CAV1 knock out. With this comprehensive model of a CD4(+) T-cell, we then validated in vivo protein expression levels. Based on this study, we modeled a CD4(+) T-cell, manipulated gene expression in immunocompromised versus competent settings, validated these manipulations in an in vivo murine model, and corroborated acute T-cell leukemia gene expression profiles in human beings. Moreover, we can model an immunocompetent versus an immunocompromised microenvironment to better understand how signaling is regulated in patients with leukemia.

A novel method for simulating insulin mediated GLUT4 translocation.

Glucose transport in humans is a vital process which is tightly regulated by the endocrine system. Specifically, the insulin hormone triggers a cascade of intracellular signals in target cells mediating the uptake of glucose. Insulin signaling triggers cellular relocalization of the glucose transporter protein GLUT4 to the cell surface, which is primarily responsible for regulated glucose import. Pathology associated with the disruption of this pathway can lead to metabolic disorders, such as type II diabetes mellitus, characterized by the failure of cells to appropriately uptake glucose from the blood. We describe a novel simulation tool of the insulin intracellular response, incorporating the latest findings regarding As160 and GEF interactions. The simulation tool differs from previous computational approaches which employ algebraic or differential equations; instead, the tool incorporates statistical variations of kinetic constants and initial molecular concentrations which more accurately mimic the intracellular environment. Using this approach, we successfully recapitulate observed in vitro insulin responses, plus the effects of Wortmannin-like inhibition of the pathway. The developed tool provides insight into transient changes in molecule concentrations throughout the insulin signaling pathway, and may be employed to identify or evaluate potentially critical components of this pathway, including those associated with insulin resistance. In the future, this highly tractable platform may be useful for simulating other complex cell signaling pathways. Biotechnol. Bioeng. 2014;111: 2454-2465. © 2014 Wiley Periodicals, Inc.