Elucidating the sources of β-catenin dynamics in human neural progenitor cells

Roles of airway and intestinal epithelia in responding to pathogens and maintaining tissue homeostasis

Epithelial cells form a resilient barrier and orchestrate defensive and reparative mechanisms to maintain tissue stability. This review focuses on gut and airway epithelia, which are positioned where the body interfaces with the outside world. We review the many signaling pathways and mechanisms by which epithelial cells at the interface respond to invading pathogens to mount an innate immune response and initiate adaptive immunity and communicate with other cells, including resident microbiota, to heal damaged tissue and maintain homeostasis. We compare and contrast how airway and gut epithelial cells detect pathogens, release antimicrobial effectors, collaborate with macrophages, Tregs and epithelial stem cells to mount an immune response and orchestrate tissue repair. We also describe advanced research models for studying epithelial communication and behaviors during inflammation, tissue injury and disease.

Receptor/Raft Ratio Is a Determinant for LRP6 Phosphorylation and WNT/β-Catenin Signaling

Microdomains or lipid rafts greatly affect the distribution of proteins and peptides in the membrane and play a vital role in the formation and activation of receptor/protein complexes. A prominent example for the decisive impact of lipid rafts on signaling is LRP6, whose localization to the same lipid rafts domain as the kinase CK1γ is crucial for its successful phosphorylation and the subsequent activation of the signalosome, hence WNT/β-catenin signaling. However, according to various experimental measurements, approximately 25 to 35 % of the cell plasma membrane is covered by nanoscopic raft domains with diameters ranging between 10 to 200 nm. Extrapolating/Translating these values to the membrane of a “normal sized” cell yields a raft abundance, that, by far, outnumbers the membrane-associated pathway components of most individual signaling pathway, such as receptor and kinases. To analyze whether and how the quantitative ratio between receptor and rafts affects LRP6 phosphorylation and WNT/β-catenin pathway activation, we present a computational modeling study, that for the first time employs realistic raft numbers in a compartment-based pathway model. Our simulation experiments indicate, that for receptor/raft ratios smaller than 1, i.e., when the number of raft compartments clearly exceeds the number of pathway specific membrane proteins, we observe significant decrease in LRP6 phosphorylation and downstream pathway activity. Our results suggest that pathway specific targeting and sorting mechanism are required to significantly narrow down the receptor/raft ratio and to enable the formation of the LRP6 signalosome, hence signaling.

Relating simulation studies by provenance-Developing a family of Wnt signaling models

For many biological systems, a variety of simulation models exist. A new simulation model is rarely developed from scratch, but rather revises and extends an existing one. A key challenge, however, is to decide which model might be an appropriate starting point for a particular problem and why. To answer this question, we need to identify entities and activities that contributed to the development of a simulation model. Therefore, we exploit the provenance data model, PROV-DM, of the World Wide Web Consortium and, building on previous work, continue developing a PROV ontology for simulation studies. Based on a case study of 19 Wnt/β-catenin signaling models, we identify crucial entities and activities as well as useful metadata to both capture the provenance information from individual simulation studies and relate these forming a family of models. The approach is implemented in WebProv, a web application for inserting and querying provenance information. Our specialization of PROV-DM contains the entities Research Question, Assumption, Requirement, Qualitative Model, Simulation Model, Simulation Experiment, Simulation Data, and Wet-lab Data as well as activities referring to building, calibrating, validating, and analyzing a simulation model. We show that most Wnt simulation models are connected to other Wnt models by using (parts of) these models. However, the overlap, especially regarding the Wet-lab Data used for calibration or validation of the models is small. Making these aspects of developing a model explicit and queryable is an important step for assessing and reusing simulation models more effectively. Exposing this information helps to integrate a new simulation model within a family of existing ones and may lead to the development of more robust and valid simulation models. We hope that our approach becomes part of a standardization effort and that modelers adopt the benefits of provenance when considering or creating simulation models.

We revise a provenance ontology for simulation studies of cellular biochemical models. Provenance information is useful for understanding the creation of a simulation model because it not only contains information about the entities and activities that have led to a simulation model but also their relations, all of which can be visualized. It provides additional structure by explicitly recording research questions, assumptions, and requirements and relating them along with data, qualitative models, simulation models, and simulation experiments through a small set of predefined but extensible activities.

We have applied our concept to a family of 19 Wnt signaling models and implemented a web-based tool (WebProv) to store the provenance information from these studies. The resulting provenance graph visualizes the story line of simulation studies and demonstrates the creation and calibration of simulation models, the successive attempts of validation and extension, and shows, beyond an individual simulation study, how the Wnt models are related. Thereby, the steps and sources that contributed to a simulation model are made explicit.

Our approach complements other approaches aimed at facilitating the reuse and assessment of simulation products in systems biology such as model repositories as well as annotation and documentation guidelines.

Exploring the mechanistic and temporal regulation of LRP6 endocytosis in canonical WNT signaling

Endocytosis plays a pivotal regulatory role in canonical WNT signaling. Internalization of the low-density lipoprotein receptor-related protein 6 (LRP6) receptor complex can either promote or attenuate canonical WNT signaling, depending on the employed internalization pathway. Detailed analysis of the mechanism of LRP6 internalization and its temporal regulation is crucial for understanding the different cellular responses to WNT stimulation under varying conditions and in various cell types. Here, we elucidate the mechanisms involved in the internalization of LRP6 and re-evaluate existing, partly contradicting, theories on the regulation of LRP6 receptor internalization. We utilize a computational approach that aims at finding a set of mechanisms that accounts for the temporal dynamics of LRP6 receptor internalization upon WNT stimulation. Starting with a simple simulation model, we successively extend and probe the model's behavior based on quantitative measurements. The final model confirms that LRP6 internalization is clathrin independent in vertebrates, is not restricted to microdomains, and that signalosome formation delays LRP6 internalization within the microdomains. These findings partly revise the current understanding of LRP6 internalization in vertebrates.

Multi-Level Modeling and Simulation of Cellular Systems: An Introduction to ML-Rules

ML-Rules is a rule-based language for multi-level modeling and simulation. ML-Rules supports dynamic nesting of entities and applying arbitrary functions on entity attributes and content, as well as for defining kinetics of reactions. This allows describing and simulating complex cellular dynamics operating at different organizational levels, e.g., to combine intra-, inter-, and cellular dynamics, like the proliferation of cells, or to include compartmental dynamics like merging and splitting of mitochondria or endocytosis. The expressiveness of the language is bought with additional efforts in executing ML-Rules models. Therefore, various simulators have been developed from which the user and automatic procedures can select. The experiment specification language SESSL facilitates design, execution, and reuse of simulation experiments. The chapter illuminates the specific features of ML-Rules as a rule-based modeling language, the implications for an efficient execution, and shows ML-Rules at work.

Spatio-temporal model of endogenous ROS and raft-dependent WNT/beta-catenin signaling driving cell fate commitment in human neural progenitor cells

Canonical WNT/β-catenin signaling is a central pathway in embryonic development, but it is also connected to a number of cancers and developmental disorders. Here we apply a combined in-vitro and in-silico approach to investigate the spatio-temporal regulation of WNT/β-catenin signaling during the early neural differentiation process of human neural progenitors cells (hNPCs), which form a new prospect for replacement therapies in the context of neurodegenerative diseases. Experimental measurements indicate a second signal mechanism, in addition to canonical WNT signaling, being involved in the regulation of nuclear β-catenin levels during the cell fate commitment phase of neural differentiation. We find that the biphasic activation of β-catenin signaling observed experimentally can only be explained through a model that combines Reactive Oxygen Species (ROS) and raft dependent WNT/β-catenin signaling. Accordingly after initiation of differentiation endogenous ROS activates DVL in a redox-dependent manner leading to a transient activation of down-stream β-catenin signaling, followed by continuous auto/paracrine WNT signaling, which crucially depends on lipid rafts. Our simulation studies further illustrate the elaborate spatio-temporal regulation of DVL, which, depending on its concentration and localization, may either act as direct inducer of the transient ROS/β-catenin signal or as amplifier during continuous auto-/parcrine WNT/β-catenin signaling. In addition we provide the first stochastic computational model of WNT/β-catenin signaling that combines membrane-related and intracellular processes, including lipid rafts/receptor dynamics as well as WNT- and ROS-dependent β-catenin activation. The model’s predictive ability is demonstrated under a wide range of varying conditions for in-vitro and in-silico reference data sets. Our in-silico approach is realized in a multi-level rule-based language, that facilitates the extension and modification of the model. Thus, our results provide both new insights and means to further our understanding of canonical WNT/β-catenin signaling and the role of ROS as intracellular signaling mediator.

Human neural progenitor cells offer the promising perspective of using in-vitro grown neural cell populations for replacement therapies in the context of neurodegenerative diseases, such as Parkinson’s or Huntington’s disease. However, to control hNPC differentiation within the scope of stem cell engineering, a thorough understanding of cell fate determination and its endogenous regulation is required. Here we investigate the spatio-temporal regulation of WNT/β-catenin signaling in the process of cell fate commitment in hNPCs, which has been reported to play a crucial role for the differentiation process of hNPCs. Based on a combined in-vitro and in-silico approach we demonstrate an elaborate interplay between endogenous ROS and lipid raft dependent WNT/beta-catenin signaling controlling the nuclear beta-catenin levels throughout the initial phase of neural differentiation. The stochastic multi-level computational model we derive from our experimental measurements adds to the family of existing WNT models, addressing major biochemical and spatial aspects of WNT/beta-catenin signaling that have not been considered in existing models so far. Cross validation studies manifest its predictive capability for other cells and cell lines rendering the model a suitable basis for further studies also in the context of embryonic development, developmental disorders and cancers.