A Process for Digitizing and Simulating Biologically Realistic Oligocellular Networks Demonstrated for the Neuro-Glio-Vascular Ensemble

One will not understand the brain without an integrated exploration of structure and function, these attributes being two sides of the same coin: together they form the currency of biological computation. Accordingly, biologically realistic models require the re-creation of the architecture of the cellular components in which biochemical reactions are contained. We describe here a process of reconstructing a functional oligocellular assembly that is responsible for energy supply management in the brain and creating a computational model of the associated biochemical and biophysical processes. The reactions that underwrite thought are both constrained by and take advantage of brain morphologies pertaining to neurons, astrocytes and the blood vessels that deliver oxygen, glucose and other nutrients. Each component of this neuro-glio-vasculature ensemble (NGV) carries-out delegated tasks, as the dynamics of this system provide for each cell-type its own energy requirements while including mechanisms that allow cooperative energy transfers. Our process for recreating the ultrastructure of cellular components and modeling the reactions that describe energy flow uses an amalgam of state-of the-art techniques, including digital reconstructions of electron micrographs, advanced data analysis tools, computational simulations and in silico visualization software. While we demonstrate this process with the NGV, it is equally well adapted to any cellular system for integrating multimodal cellular data in a coherent framework.

Statistical Analysis of Chao’s Immune System Simulation

Eric Winnington

Modeling the immune system (IS) means putting together a set of assumptions about its components (cells and organs) and their interactions. Simulations of a model show joint behavior of the components, which for complex realistic models is often impossible to find analytically. Simulations allow us to experiment on how initial concentrations and properties of the immune cells and viruses impact the IS behavior, and gain better quantitative and qualitative insight into how the IS works and why different behavior patterns occur. A simulation, once it has been created, must be reviewed both statistically and analytically as well as validated from the biological point of view. We analyzed Chao’s immune system simulation [1][2] from a statistical and analytical point. We explicited both the Markov chain which was simulated and the underlying process on which Chao’s stage-structured approach was built. Furthermore, we established a test protocol for timestep validation which Chao’s simulator passed. We evaluated Chao’s simulator’s dependence on the random number generator, which was shown to be negligible. Finally, we evaluated the simulator output and our major result is the discovery of a secondary response to a primary infection, an occurrence is not shown in Chao’s dissertation. A tertiary response to the infection is never possible due to the size of the secondary response caused by memory cells.

2005

Photopatterning of Synthetic Hydrogels

Katarzyna Mosiewicz

In recent years sophisticated biomaterials have made a significant impact on our understanding of cellular behavior, particularly in the fields of stem cell research and tissue engineering. Nevertheless, the promising potential of stem cells for regenerative medicine has remained largely unmet. One reason for such limitations could be that there is still incomplete understanding of stem cell behavior due to a lack of advanced in vitro tools suitable to achieve adequate control over cellular processes. By mimicking the dynamic and complex biophysical and biochemical interactions between cells and their natural extracellular matrixes (ECMs), it is possible that we may bridge this gap between current limited in vitro models and complex in vivo organisms. In this thesis, an innovative class of biomaterials is presented that enables the flexible in vitro recapitulation of the dynamic biochemical and biophysical signaling involved in controlling cell fate. Such systems of increasing fidelity to real physiological processes could bring new insights into fundamental cell biology as well as bring us to closer towards cell-based therapeutics applications. In order to achieve a dynamic artificial ECM (aECM), we designed chemical schemes which would allow us to control the biochemical and biophysical properties of the hydrogel in space, time and intensity. The chosen concept is built on a synthetic hydrogel providing static physicochemical support, while spatiotemporal control over a single or multiple signals is achieved by spatiotemporal photoactivation reactions within this hydrogel. Indeed, by modulating the duration, location and intensity of illumination, desired heterogeneities in biochemical and biophysical signal can be introduced in the otherwise homogeneous and static hydrogel network. To implement the designed hydrogel photo-patterning tool, new chemical components were synthesized. Synthetic hydrogels based on poly (ethylene glycol) (PEG) were utilized due to their inert properties, cell biocompatibility and lack of unspecific protein binding. Biochemical signal tethering was rendered spatiotemporally controllable by adding photosensitivity to the existing enzyme-based crosslinking scheme. This was achieved by functionalizing one of enzymatic substrate with a photo-labile “caging” moiety, thereby preventing crosslinking to occur until light illumination. This caged substrate was incorporated into the hydrogel network and served as a light-controllable and specific ligand-binding site. Importantly, it was possible to photo-pattern proteins, which are much complex than peptide-based biomolecules, and their bioactivity was fully preserved with this site-specific immobilization scheme. It was also possible to pattern biophysical cues by making the Michael-type (MT) addition reaction for crosslinking PEG-based hydrogel photosensitive. In this case, the thiol moieties of one of the reactive PEG macromers undergoing crosslinking, were equipped with a caging group which prevented its susceptibility to the counter-reactive functionality, the vinyl sulfone group. Thus, the crosslinking density of the hydrogel backbone could be controlled by light, which was directly translated into differential patterns of hydrogel stiffness. Using this approach, user-defined biochemical and biophysical patterns and even gradients could be obtained in the spatiotemporal manner within the same hydrogel. The crosslinking reaction is the critical parameter in the success of hydrogel photo-patterning, and must rely on a well-controlled and highly selective chemical scheme. Therefore, we also developed a novel enzyme-based cross-linking scheme for synthetic PEG hydrogels. The reaction originates from the naturally occurring post-translational modification of proteins by phosphopantetheine (Ppant) group performed by a family of enzymes known as Ppant transferases (PPTases). By synthesizing biochemical components of this reaction, we implemented a PPTase-catalyzed reaction to form and bio-functionalize PEG hydrogel. The utility of the developed hydrogel platforms was determined in the context of 2D and 3D cell culture. Photo-directed patterns of a cell-adhesive fibronectin fragment triggered adhesion and spreading of muscle progenitor cells, a phenomenon which occurred only within the areas of patterned signaling protein. A photo-patterned elasticity gradient was used to direct mesenchymal stem cell spreading and migration. Finally, the PPTase-based hydrogel was proven to be suitable for 3D culture, as shown by encapsulation of primary human fibroblasts. In this thesis, we demonstrated that a combination of chemical schemes could be assembled to achieve a functional materials toolbox which would begin to reconstruct the complexity of the dynamic in vivo ECM. Such a tool is expected to contribute to the field of cell biology by allowing us to study questions which previously could not be addressed in vitro, and could ultimately contribute to cell-based regenerative medicine.

EPFL2012

Optimal Design of Signaling Modules

Andrijana Radivojevic

One of the basic characteristics of every living system is the ability to respond to extracellular signals. This is carried out through a limited number of protein-based signaling networks, whose function is not based only on simple transmission of the received signals, but incorporates the processing, encoding and integration of both external and internal signals. The results than lead to different changes in gene expression and regulate cell growth, mitogenesis, differentiation, embryo development, and stress responses in mammalian cells, whereas the malfunction is in correlation with diseases such as cancer, asthma and diabetes. In signaling networks, the basic units are covalent modification cycles, which comprise the activation and deactivation of proteins by other proteins. Protein modification in cell signaling – typically a phosphorylation and dephosphorylation – is a general mechanism responsible for the transfer of a wide variety of chemical signals in biological systems. Although the concept does not seem to be complex from a biochemical point of view, these simple systems can nevertheless provide a large diapason of dynamical responses and are therefore ubiquitous building blocks of signaling pathways. These cycles are often linked, forming multiple layers of cycles, the so-called cascades. Commonly observed instance of signal transduction through a series of protein kinase reactions are the kinases of the mitogen-activated protein kinase (MAPK) cascades. These pathways, which are found in almost all eukaryotes, play an important role in controlling different cellular processes, including fundamental functions. The activation of the cellular response by MAPK pathways typically involves at least three phosphorylation steps. In order to better understand the nature of this regulation and to gain greater insight into the mechanisms that determine the function of cells, signaling modules have been intensively studied using mathematical modeling and computational simulations, through the fast growing field of systems biology and its disciplines. The primary aim is to faithfully describe the system and to be able to predict the system behavior. Synergistically with experimental analysis, the reported observations have allowed one to identify properties of these pathways, such as fast signal propagation, large amplification, short signal duration and noise resistance. Since biochemical parameters in signaling pathways are not easily accessible experimentally, it is necessary to use advanced mathematical tools for their correct estimation. Using the paradigm of man-made optimal signal transduction systems, we chose to take the research path for discovering optimal design of cellular signaling modules. To approach the main thesis objective, we first identified the key system parameters through global sensitivity analysis. Comparative analysis of differences and similarities within different system architectures revealed some insights for initial parameter classification and starting point for optimal system design. In order to be able to interpret a broader range of phenotypes, we take into account both steady-state and dynamic properties simultaneously. Furthermore, we investigated the trade-offs between optimal characteristics. As a result, we found the biochemical and biophysical parameters that determine these trade-offs and we analyzed if there exist conditions under which we can simultaneously achieve optimal steady-state and dynamic performance. We first analyze what are the design principles that lead the system to have the minimal signaling times, subject to a certain level of amplification gain. In this setup, we bring out our main research question: are there any trade-offs and interplay between different steady-state and dynamic properties? Furthermore, we include the property of ultrasensitivity and eventually solve multi-objective optimization problems. A particularly insightful finding of this work is that, upon judicious selection of the kinetic parameters, a simple covalent modification cycle is able to meet multiple objectives simultaneously. In particular, this analysis may help explain why signaling cycles are so ubiquitous in cell signaling. The enhancement of ultrasensitivity and faster signal propagation in the multicyclic systems clearly show the advantages of the natural choice of designing signaling pathways in the form of signaling cascades. The thesis concludes with the potential research steps that could be taken along the same path, and that would gather more quantitative knowledge about signaling pathways.

EPFL2012

Optimal Design of Signaling Modules

Andrijana Radivojevic

EPFL2012

Photopatterning of Synthetic Hydrogels

Katarzyna Mosiewicz

EPFL2012