Computational investigations into the orgins of 'short term' biochemical memory in T cell activation

Recent studies have reported that T cells can integrate signals between interrupted encounters with Antigen Presenting Cells (APCs) in such a way that the process of signal integration exhibits a form of memory. Here, we carry out a computational study using a simple mathematical model of T cell activation to investigate the ramifications of interrupted T cell-APC contacts on signal integration. We consider several mechanisms of how signal integration at these time scales may be achieved and conclude that feedback control of immediate early gene products (IEGs) appears to be a highly plausible mechanism that allows for effective signal integration and cytokine production from multiple exposures to APCs. Analysis of these computer simulations provides an experimental roadmap involving several testable predictions.Comment: 11 pages, published July 18th 200

A robust and efficient method for estimating enzyme complex abundance and metabolic flux from expression data

A major theme in constraint-based modeling is unifying experimental data, such as biochemical information about the reactions that can occur in a system or the composition and localization of enzyme complexes, with highthroughput data including expression data, metabolomics, or DNA sequencing. The desired result is to increase predictive capability resulting in improved understanding of metabolism. The approach typically employed when only gene (or protein) intensities are available is the creation of tissue-specific models, which reduces the available reactions in an organism model, and does not provide an objective function for the estimation of fluxes, which is an important limitation in many modeling applications. We develop a method, flux assignment with LAD (least absolute deviation) convex objectives and normalization (FALCON), that employs metabolic network reconstructions along with expression data to estimate fluxes. In order to use such a method, accurate measures of enzyme complex abundance are needed, so we first present a new algorithm that addresses quantification of complex abundance. Our extensions to prior techniques include the capability to work with large models and significantly improved run-time performance even for smaller models, an improved analysis of enzyme complex formation logic, the ability to handle very large enzyme complex rules that may incorporate multiple isoforms, and depending on the model constraints, either maintained or significantly improved correlation with experimentally measured fluxes. FALCON has been implemented in MATLAB and ATS, and can be downloaded from: https://github.com/bbarker/FALCON. ATS is not required to compile the software, as intermediate C source code is available, and binaries are provided for Linux x86-64 systems. FALCON requires use of the COBRA Toolbox, also implemented in MATLAB.Comment: 30 pages, 12 figures, 4 table

Design principles of mammalian signaling networks : emergent properties at modular and global scales

Thesis (Ph. D.)--Massachusetts Institute of Technology, Biological Engineering Division, 2008.Includes bibliographical references (leaves 244-249).This thesis utilizes modeling approaches rooted in statistical physics and physical chemistry to investigate several aspects of cellular signal transduction at both the modular and global levels. Design principles of biological networks and cell signaling processes pertinent to disease progression emerge from these studies. It is my hope that knowledge of these principles may provide new mechanistic insights and conceptual frameworks for thinking about therapeutic intervention into diseases such as cancer and diabetes that arise from aberrant signaling. Areas of interest have emphasized the role of scaffold proteins in protein kinase cascades, modeling relevant biophysical processes related to T cell activation, design principles of signal transduction focusing on multisite phosphorylation, quantifying the notion of signal duration and the time scale dependence of signal detection, and entropy based models of network architecture inferred from proteomics data. These problems are detailed below. The assembly of multiple signaling proteins into a complex by a scaffold protein guides many cellular decisions. Despite recent advances, the overarching principles that govern scaffold function are not well understood. We carried out a computational study using kinetic Monte Carlo simulations to understand how spatial localization of kinases on a scaffold may regulate signaling under different physiological condition. Our studies identify regulatory properties of scaffold proteins that allow them to both amplify and attenuate incoming signals in different biological contexts. In a further, supplementary study, simulations also indicate that a major effect that scaffolds exert on the dynamics of cell signaling is to control how the activation of protein kinases is distributed over time[2].(cont.) Scaffolds can influence the timing of kinase activation by allowing for kinases to become activated over a broad range of times, thus allowing for signaling across a broad spectrum of time scales. T cells orchestrate the adaptive immune response and are central players in maintenance of functioning immune system. Recent studies have reported that T cells can integrate signals between interrupted encounters with Antigen Presenting Cells (APCs) in such a way that the process of signal integration exhibits a form of memory. We carried out a computational study using a simple mathematical model of T cell activation to investigate the ramifications of interrupted T cell-APC contacts on signal integration. We considered several mechanisms of how signal integration at these time scales may be achieved. In another study, we investigated the role of spatially localizing signaling components of the T cell signaling pathway into a structure known as the immunological synapse. We constructed a minimal mathematical model that offers a mechanism for how antigen quality can regulate signaling dynamics in the immunological synapse These studies involving the analysis of signaling dynamics led us to investigate how differences in signal duration might be detected. Signal duration (e.g. the time scales over which an active signaling intermediate persists) is a key regulator of biological decisions in myriad contexts such as cell growth, proliferation, and developmental lineage commitments. Accompanying differences in signal duration are numerous downstream biological processes that require multiple steps of biochemical regulation. We present an analysis that investigates how simple biochemical motifs that involve multiple stages of regulation can be constructed to differentially process signals that persist at different time scales[3].(cont.) Topological features of these networks that allow for different frequency dependent signal processing properties are identified. One role of multisite phosphorylation in cell signaling is also investigated. The utilization of multiple phosphorylation sites in regulating a biological response is ubiquitous in cell signaling. If each site contributes an additional, equivalent binding site, then one consequence of an increase in the number of phosphorylations may be to increase the probability that, upon disassociation, a ligand immediately rebinds to its receptor. How such effects may influence cell signaling systems is not well understood. A self-consistent integral equation formalism for ligand rebinding, in conjunction with Monte Carlo simulations, was employed to further investigate the effects of multiple, equivalent binding sites on shaping biological responses. Finally, this thesis also seeks to investigate cell signaling at a global scale. Advances in Mass Spectrometry based phosphoproteomics have allowed for the real-time quantitative monitoring of entire proteomes as signals propagate through complex networks in response to external signals. The trajectories of as many as 222 phosphorylated tyrosine sites can be simultaneously and reproducibly monitored at multiple time points. We develop and apply a method using the principle of maximum entropy to infer a model of network connectivity of these phosphorylation sites. The model predicts a core structure of signaling nodes, affinity dependent topological features of the network, and connectivity of signaling nodes that were hitherto unassociated with the canonical growth factor signaling network. Our combined results illustrate many complexities in the broad array of control properties that emerge from the physical effects that constrain signal propagation on complex biological networks.(cont.) It is the hope of this work that these studies bring coherence to seemingly paradoxical observations and suggest that cells have evolved design rules that enable biochemical motifs to regulate widely disparate cellular functions.by Jason W. Locasale.Ph.D

Data Management for a Police Command/Control Simulation Study

The primary purpose of this thesis is to aid the Orlando Police Department locate areas of improvement with the effect of reducing the total response time of the Command/Control Center through the application of basic industrial engineering techniques. This work is presented in three major chapters. The first is concerned with the definition of the present operation of the Center, the total scope of each separate function within the Center and the interactions with the general public and other public safety departments. The second chapter develops the studies which provide the input values for the simulation model and the analysis of these parameters through statistical testing procedures. The final chapter states the interpretations of the statistical values and indicates the areas where industrial engineering techniques could best be applied to reduce the total response time of the Command/Control Center. This work was supported bya grant from the Governor\u27s Council on Criminal Justice to the Orlando Police Department

Child Temperamental Regulation and Classroom Quality in Head Start: Considering the Role of Cumulative Economic Risk

There is growing recognition that cumulative economic risk places children at higher risk for depressed academic competencies (Crosnoe & Cooper, 2010; NCCP, 2008; Sameroff, 2000). Yet, children’s temperamental regulation and the quality of the early childhood classroom environment have been associated with better academic skills. This study is an examination of prekindergarten classroom quality (instructional support, emotional support, organization) as a moderator between temperamental regulation and early math and literacy skills for children at varying levels of cumulative economic risk. The sample includes children enrolled in Head Start programs drawn from the FACES 2009 study. Three main findings emerged. First, for lower and highest risk children, more instructional support was associated with better math performance when children had high levels of temperamental regulation but poorer performance when children had low temperamental regulation. Second, among highest risk children, low instructional support was protective for math performance for children with low temperamental regulation and detrimental for those with high temperamental regulation. Third, for highest risk children, high classroom organization predicted better literacy scores for those with high temperamental regulation. Children with low temperamental regulation were expected to perform about the same, regardless of the level of classroom organization. Implications are discussed

Observed Quality and Consistency of Fifth Graders’ Teacher–Student Interactions: Associations With Feelings, Engagement, and Performance in School

This study examined how overall quality and within-day consistency in fifth graders’ teacher-student interactions related to feelings about, engagement, and academic performance in school. Participants were 956 children in a national study. Students who experienced higher quality interactions reported more positive feelings about school, were more engaged, performed better in math and reading, and had more closeness and less conflict with teachers. Independent of overall interaction quality, students who experienced less consistency in their interactions with teachers, whether it was with the same teacher or across teachers, were less engaged and had more teacher-reported conflict. Findings emphasize the separate contributions of both high quality and consistency of teacher–student interactions to students’ success

Profiles of learning opportunities of multilingual and monolingual children in kindergarten

Early childhood education serves an increasing number of multilingual children, and teachers are challenged to create high-quality learning opportunities in the classroom for all children. The child’s engagement and interactions with the teacher are important in this respect. The present study therefore examined how multilingualism relates to engagement and teacher-child interactions, taking a person-oriented approach. During one school year, 76 kindergarteners (43 multilingual) from 19 classrooms were observed for behavioral engagement and individual teacher-child interactions. Five engagement profiles were identified that reflect different levels of engagement across classroom settings. Multilingual children were overrepresented in profiles that showed lower engagement in one or more settings. Also, five interaction profiles were identified that showed strong diversity in the interactions of teachers with children in their classroom. Monolingual and multilingual children were equally represented across these profiles. Children in the more beneficial interaction profiles were also often in the moderate-to-high engagement profiles