On Modeling Signal Transduction Networks

Signal transduction networks are very complex processes employed by the living cell to suitably react to environmental stimuli. Qualitative and quantitative computational models play an increasingly important role in the representation of these networks and in the search of new insights about these phenomena. In this work we analyze some graph-based models used to discover qualitative properties of such networks. In turn, we show that MP systems can naturally extend these graph-based models by adding some qualitative elements. The case study of integrins activation during the lymphocyte recruitment, a crucial phenomenon in inflammatory processes, is described, and a first MP graph for this network is designed. Finally, we discuss some open problems related to the qualitative modeling of signaling networks

Biological networks in metabolic P systems

Abstract The metabolic P algorithm is a procedure which determines, in a biochemically realistic way, the evolution of P systems representing biological phenomena. A new formulation of this algorithm is given and a graphical formalism is introduced which seems to be very natural in expressing biological networks by means of a two level representation: a basic biochemical level and a second one which regulates the dynamical interaction among the reactions of the first level. After some basic examples, the mitotic oscillator in amphibian embryos is considered as an important case study. Three formulations of this biological network are developed. The first two are directly derived by Goldbeter's differential equations representation. The last one, entirely deduced by translating the biological description of the phenomenon in our diagrams, exhibits an analogous pattern, but it is conceptually simpler and avoids many details on the kinetic aspects of the reactions

Size control in mammalian cells involves modulation of both growth rate and cell cycle duration

Despite decades of research, how mammalian cell size is controlled remains unclear because of the difficulty of directly measuring growth at the single-cell level. Here we report direct measurements of single-cell volumes over entire cell cycles on various mammalian cell lines and primary human cells. We find that, in a majority of cell types, the volume added across the cell cycle shows little or no correlation to cell birth size, a homeostatic behavior called “adder”. This behavior involves modulation of G1 or S-G2 duration and modulation of growth rate. The precise combination of these mechanisms depends on the cell type and the growth condition. We have developed a mathematical framework to compare size homeostasis in datasets ranging from bacteria to mammalian cells. This reveals that a near-adder behavior is the most common type of size control and highlights the importance of growth rate modulation to size control in mammalian cells

Detecting separate time scales in genetic expression data.

BACKGROUND: Biological processes occur on a vast range of time scales, and many of them occur concurrently. As a result, system-wide measurements of gene expression have the potential to capture many of these processes simultaneously. The challenge however, is to separate these processes and time scales in the data. In many cases the number of processes and their time scales is unknown. This issue is particularly relevant to developmental biologists, who are interested in processes such as growth, segmentation and differentiation, which can all take place simultaneously, but on different time scales. RESULTS: We introduce a flexible and statistically rigorous method for detecting different time scales in time-series gene expression data, by identifying expression patterns that are temporally shifted between replicate datasets. We apply our approach to a Saccharomyces cerevisiae cell-cycle dataset and an Arabidopsis thaliana root developmental dataset. In both datasets our method successfully detects processes operating on several different time scales. Furthermore we show that many of these time scales can be associated with particular biological functions. CONCLUSIONS: The spatiotemporal modules identified by our method suggest the presence of multiple biological processes, acting at distinct time scales in both the Arabidopsis root and yeast. Using similar large-scale expression datasets, the identification of biological processes acting at multiple time scales in many organisms is now possible.RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are

Mitotic Exit: Thresholds and Targets

Cyclin dependent kinases (CDKs) are at the heart of the cell cycle. Throughout the cycle, these complexes modify many proteins, changing various aspects of their regulation (stability, localization, etc.). As cells exit mitosis, the CDK that has driven many of the cell cycle processes is inhibited and degraded, allowing many of the kinase substrates to return to their unphosphorylated state. This assures that each subsequent cell cycle is begun in the same naïve state, again ready for CDK-dependent regulation. The studies in this thesis focus on two mechanisms by which this restoration is accomplished in the budding yeast, Saccharomyces cerevisiae: (1) a transcriptional program that transcribes many of the genes required for physically dividing the mother and daughter cells and beginning the next round of cell division and (2) a phosphatase that specifically removes the phosphates from sites modified by CDK during exit from mitosis. Two transcription factors, Swi5 and Ace2, transcribe many of the genes required for physically dividing the mother and daughter cells and beginning the next round of cell division. Previously our lab has shown that locking mitotic cyclin levels, by inducing transcription of an undegradable form of the protein, causes dose-dependent delays in different cell cycle events. The first chapter addresses the contribution of the transcriptional program to this phenomenon. Interestingly, in these cells where mitotic cyclin levels were sustained, deletion of the transcription factor Swi5 increases the mitotic cyclin inhibition, specifically as it relates to budding and cytokinesis. Importantly, when phosphorylated by CDK, Swi5 is excluded from the nucleus, so in the second chapter, we investigate its localization when mitotic cyclin levels are locked. Swi5 still enters the nucleus. In fact in some cells, Swi5 enters the nucleus several times before the cell cycle advances. Given previous studies from our lab showing that the release of Cdc14 phosphatase also oscillates under these conditions, the reentry of Swi5 may support a model that a kinase/phosphatase balance allows cell cycle progression in these cells. All this suggests that Swi5 promotes the transcription of genes important for promoting cytokinesis and budding despite high mitotic cyclin levels. In the third chapter, we begin to assess the contribution of specific targets of the mitotic exit transcriptional program to the mitotic cyclin-dependent regulation of specific cell cycle events. Finally, Cdc14, a phosphatase that removes the phosphate groups added by CDKs, is sequestered for most of the cell cycle but released from the nucleolus during the end of mitosis. In the fourth chapter, we examine the physiological relevance of these dephosphorylation events on novel targets of the Cdc14 phosphatase

The circadian clock and the cell cycle

The circadian clock is an endogenous time-keeping mechanism that allows an organism to coordinate its biology with the 24 hour variations in its external environment. Epidemiological studies have linked clock disruption to an increase incidence of cancer, in particular breast malignancy. On a molecular level, clock components have been shown to regulate cell cycle gene expression and its progression in a number of models. This thesis set out to further dissect the link between these two important systems. Within the zebrafish cell-line, PAC2, mitosis was demonstrated to be under circadian control via clock regulation of the cell cycle mediator, Cyclin B1. Techniques used were then translated into a human cell-line model to study species specific clock function, with particular reference to breast epithelial tissue. Glucocorticoids, putative clock synchronisation agents in vivo, were observed to induce cellular clock synchronisation in HEK 293 cells and the benign breast epithelial cell-line MCF10A. Clock disruption inhibited cell growth. Study of the breast epithelial cell cycle mutant, MDA-MB-231, demonstrated a functional clock, revealing no reciprocal regulation. In contrast, decreased expression levels of clock gene and putative tumour suppressor, Per1, were observed within the malignant breast epithelial cell-line, MCF7, leading to greatly disrupted clock function and circadian independent cell growth. Unlike the zebrafish model, no intracellular clock regulation of cell cycle genes expression or function was observed, expression being preferentially modified by homeral circadian regulators such as glucocorticoids and melatonin. This also contradicts mammalian in vivo studies, leading to the hypothesis that the clock and cell cycle maybe uncoupled in immortalised cell cultures. In conclusion this study has demonstrated that clock regulation of the cell cycle in mammalian system is a multifactorial process and that disruption of this system leads to changes in the character of the cell cycle within the host tissue. Further work must explore this relationship in an in vivo setting

Studying the cell cycle using systems biology and high content characterization of the Ubiquitin Proteasome System

The cell cycle is the process through which our cells grow and divide in a carefully orchestrated and controlled manner. An uncontrolled cell cycle is a basic hallmark of cancer, in which excessive cell growth leads to adverse effects on the tissue- and organ-level. The Ubiquitin Proteasome System (UPS) is responsible for the destruction of unwanted proteins in the cell, but has additionally been identified to inhabit regulatory roles in a myriad of cellular processes. This thesis aimed to study the cell cycle and the ubiquitin proteasome system using high-throughput and high-content approaches. The first approach aimed at observing the endogenous fluctuations of mRNA, proteins, phosphorylations, and intra-cellular compartmentalization over the cell cycle, and how these systems are regulated and coordinated throughout the cell cycle, described in Study I and II. Aside from characterizing cell cycle oscillation patterns of transcripts, proteins, phosphorylation events and subcellular localization changes, the dynamics between transcriptional and proteomic regulation was further investigated by comparing oscillation patterns of corresponding mRNA and protein pairs. The second approach aimed to investigate how one of the largest enzyme families in the human proteome, the UPS, affects the cell cycle and responses to external and intrinsic DNA damage. This was done through a phenotypical characterization after silencing the genes comprising the family in a high- content imaging study, Study III. The results revealed many novel UPS genes as essential for proper progression through the cell cycle and maintenance of DNA integrity. By combining multiple reporter systems in one high-content study, correlations between cell cycle, viability and DNA Damage Response phenotypes could be performed. This revealed an increased tendency for G1/S-phase cell cycle arrests after signs of spontaneous DNA damage, and an enrichment for G2 cell cycle arrests after failure of 53bp1 recruitment to double-strand breaks. Aside from providing data resources and system biology results regarding the interaction between different cellular process, the studies also identified specific genes and proteins in novel roles regarding these basic cellular processes. In Study II, the methyl-transferase protein MAT2A was discovered to change subcellular localization in synchronization with the cell cycle, possible to provide the higher source of methyl groups needed during S-phase and G2-phase. In Study IV, the E3 ubiquitin ligases ARIH1 and ARIH2 were investigated for effects on proliferation and growth of glioblastoma multiforme. The high-content Study III identified many novel UPS genes with a myriad of cell cycle and DNA damage phenotypes, among them the E3 ubiquitin adapter BTBD1. Silencing of BTBD1 incurred dramatic phenotypes on the cell cycle and DNA damage responses, and BTBD1 was further characterized and identified to be essential for proper function of the DNA topoisomerase TOP1. Throughout these projects, in order to validate novel findings, methods to control specific gene expression levels was developed, utilizing shRNA and CRISPR/Cas9-mediated silencing as well as a flexible method of overexpression. These systems are described in Study IV. The presented studies combine high-content and high-throughput approaches with novel visualization and analysis methods to distill information from complex data, both to summarize interactions between mRNA, proteins, and function, but also to identify novel regulators of basal cellular processes

Global analysis of phase locking in gene expression during cell cycle: the potential in network modeling

<p>Abstract</p> <p>Background</p> <p>In nonlinear dynamic systems, synchrony through oscillation and frequency modulation is a general control strategy to coordinate multiple modules in response to external signals. Conversely, the synchrony information can be utilized to infer interaction. Increasing evidence suggests that frequency modulation is also common in transcription regulation.</p> <p>Results</p> <p>In this study, we investigate the potential of phase locking analysis, a technique to study the synchrony patterns, in the transcription network modeling of time course gene expression data. Using the yeast cell cycle data, we show that significant phase locking exists between transcription factors and their targets, between gene pairs with prior evidence of physical or genetic interactions, and among cell cycle genes. When compared with simple correlation we found that the phase locking metric can identify gene pairs that interact with each other more efficiently. In addition, it can automatically address issues of arbitrary time lags or different dynamic time scales in different genes, without the need for alignment. Interestingly, many of the phase locked gene pairs exhibit higher order than 1:1 locking, and significant phase lags with respect to each other. Based on these findings we propose a new phase locking metric for network reconstruction using time course gene expression data. We show that it is efficient at identifying network modules of focused biological themes that are important to cell cycle regulation.</p> <p>Conclusions</p> <p>Our result demonstrates the potential of phase locking analysis in transcription network modeling. It also suggests the importance of understanding the dynamics underlying the gene expression patterns.</p

Suprachiasmatic nuclei development: A characterization of transcription factors and the influence of retinal innervation and VIP signaling

The suprachiasmatic nuclei: SCN) are highly specialized neural structures with an essential behavioral function; creating the rhythm of the mammalian central clock and entraining that internal clock to the external world. The nuclei each consist of approximately 10,000 neurons, each capable of creating near 24 h rhythms, organized into a highly structured network. While the molecular clockwork underlying the rhythm within neurons and network properties have been well studied, how the nuclei are initially specified and how the network develops is poorly understood. Herein, we seek to elucidate the genes and mechanisms involved in the specification and development of SCN neurons, the SCN network, and circadian function. We first identified genes expressed relatively discretely with the SCN. Using these genes we provided a detailed analysis of transcription factor: TF) and developmental-gene expression within the SCN from neurogenesis through to adulthood in mice (Mus musculus). Through this analysis we identified a genetically distinct neuroepithelium from which SCN neurons are derived and described a gene cascade through which SCN neurons progress as they become postmitotic. In addition, we observed changes in patterns of TF expression through development indicating maturation of nuclei both prenatally and postnatally. We investigated the contribution of critical circadian components in shaping SCN development by monitoring the localization of TF expression in mouse models that lacked either Atoh7, necessary for retinal ganglion cell development, or functional VIP peptide or VIP receptor 2: VPAC2, Vipr2). We found that maturation of TF expression patterns within the SCN occurred independent of retinal innervation and VIP signaling, suggesting that localizations may reflect intrinsic differences in subsets of neurons within the nuclei rather than induced changes. Finally, we began to define specific TFs necessary for SCN development using a Cre/loxP system to temporally localize TF deletion. We found that the well-conserved TF, Six3, is necessary for the initial formation and specification of SCN neurons, but not involved postmitotically in onset or localization of TF or peptide expression. This work begins to reveal aspects of the development of circadian function, by providing a characterization of SCN anatomical development and the first descriptions of TFs necessary for specification

Daughter-Specific Transcription Factors Regulate Cell Size Control in Budding Yeast

The asymmetric localization of cell fate determinants results in asymmetric cell cycle control in budding yeast