Developmental Engineering: A New Paradigm for the Design and Manufacturing of Cell-Based Products. Part II. From Genes to Networks: Tissue Engineering from the Viewpoint of Systems Biology and Network Science

Department of Biochemistry and Molecular Biology IV, Veterinary Faculty, Complutense University of Madrid , Madrid, Spain .
Tissue Engineering Part B Reviews (Impact Factor: 4.64). 08/2009; 15(4):395-422. DOI: 10.1089/ten.TEB.2009.0461
Source: PubMed


The field of tissue engineering is moving toward a new concept of "in vitro biomimetics of in vivo tissue development." In Part I of this series, we proposed a theoretical framework integrating the concepts of developmental biology with those of process design to provide the rules for the design of biomimetic processes. We named this methodology "developmental engineering" to emphasize that it is not the tissue but the process of in vitro tissue development that has to be engineered. To formulate the process design rules in a rigorous way that will allow a computational design, we should refer to mathematical methods to model the biological process taking place in vitro. Tissue functions cannot be attributed to individual molecules but rather to complex interactions between the numerous components of a cell and interactions between cells in a tissue that form a network. For tissue engineering to advance to the level of a technologically driven discipline amenable to well-established principles of process engineering, a scientifically rigorous formulation is needed of the general design rules so that the behavior of networks of genes, proteins, or cells that govern the unfolding of developmental processes could be related to the design parameters. Now that sufficient experimental data exist to construct plausible mathematical models of many biological control circuits, explicit hypotheses can be evaluated using computational approaches to facilitate process design. Recent progress in systems biology has shown that the empirical concepts of developmental biology that we used in Part I to extract the rules of biomimetic process design can be expressed in rigorous mathematical terms. This allows the accurate characterization of manufacturing processes in tissue engineering as well as the properties of the artificial tissues themselves. In addition, network science has recently shown that the behavior of biological networks strongly depends on their topology and has developed the necessary concepts and methods to describe it, allowing therefore a deeper understanding of the behavior of networks during biomimetic processes. These advances thus open the door to a transition for tissue engineering from a substantially empirical endeavor to a technology-based discipline comparable to other branches of engineering.

1 Follower
26 Reads
  • Source
    • "As is widely accepted, this bone repair in adults recapitulates the normal development of the skeleton during embryogenesis [24]. Moreover, the current paradigm of bone tissue engineering also relies on biomimetics to reproduce bone formation from development biology [25] [26]. Prenatal bone formation starts with mesenchymal cell condensation and subsequent differentiation to chondrocytes (through endochondral ossification) or, in precise cases, straight forward to osteoblasts (through intramembranous ossification) [27]. "
    [Show abstract] [Hide abstract]
    ABSTRACT: Bone fracture healing impairment related to mechanical problems has been largely corrected by advances in fracture management. Better protocols, more strict controls of time and function, hardware and surgical technique evolution have contributed to better prognosis, even in complex fractures. However, atrophic nonunion persists in clinical cases where, for different reasons, the osteogenic capability is impaired. When this is the case, a better understanding of basic mechanisms under bone repair and augmentation techniques may put in perspective the current possibilities and future opportunities. Among those, cell therapy particularly aims to correct this insufficient osteogenesis. However, the launching of safe and efficacious cell therapies still requires substantial amount of research, especially clinical trials. This review will envisage the current clinical trials on bone healing augmentation based on cell therapy, with the experience provided by the REBORNE Project, and the insight from investigator-driven clinical trials on advanced therapies towards the future.
    Bone 08/2014; 70. DOI:10.1016/j.bone.2014.07.033 · 3.97 Impact Factor
  • Source
    • "Proteins are normally expressed at different concentrations in different individuals of the same species, and yet the overall behavior of their biological networks does not differ significantly. This phenomenon has led to the notion that biological networks are inherently robust [1] [20]. In modeling terms, this means that, if a model is a close representation of a biological network, most of the parameters of that model can vary inside a certain interval without influencing the qualitative behavior of the whole network. "
    [Show abstract] [Hide abstract]
    ABSTRACT: ANIMO (Analysis of Networks with Interactive MOdeling) is a software for modeling biological networks, such as e.g. signaling, metabolic or gene networks. An ANIMO model is essentially the sum of a network topology and a number of interaction parameters. The topology describes the interactions between biological entities in form of a graph, while the parameters determine the speed of occurrence of such interactions. When a mismatch is observed between the behavior of an ANIMO model and experimental data, we want to update the model so that it explains the new data. In general, the topology of a model can be expanded with new (known or hypothetical) nodes, and enables it to match experimental data. However, the unrestrained addition of new parts to a model causes two problems: models can become too complex too fast, to the point of being intractable, and too many parts marked as "hypothetical" or "not known" make a model unrealistic. Even if changing the topology is normally the easier task, these problems push us to try a better parameter fit as a first step, and resort to modifying the model topology only as a last resource. In this paper we show the support added in ANIMO to ease the task of expanding the knowledge on biological networks, concentrating in particular on the parameter settings.
    04/2014; 145. DOI:10.4204/EPTCS.145.5
  • Source
    • "In the past years it has become increasingly clear that a thorough understanding of cells, tissues and disease pathologies is a prerequisite for the development of effective therapies and drugs (Lenas et al, 2009a, b). This insight is causing a gradual shift towards systems biology, that aims to unravel the molecular mechanisms of biological systems as a whole, rather than focusing on the individual components. "
    [Show abstract] [Hide abstract]
    ABSTRACT: Computational modeling of biological networks permits comprehensive analysis of cells and tissues to define molecular phenotypes and novel hypotheses. Although a large number of software tools have been developed, the versatility of these tools is limited by mathematical complexities that prevent their broad adoption and effective use by molecular biologists. This study clarifies the basic aspects of molecular modeling, how to convert data into useful input, as well as the number of time points and molecular parameters that should be considered for molecular regulatory models with both explanatory and predictive potential. We illustrate the necessary experimental preconditions for converting data into a computational model of network dynamics. This model requires neither a thorough background in mathematics nor precise data on intracellular concentrations, binding affinities or reaction kinetics. Finally, we show how an interactive model of crosstalk between signal transduction pathways in primary human articular chondrocytes allows insight into processes that regulate gene expression.
    Gene 10/2013; DOI:10.1016/j.gene.2013.10.010 · 2.14 Impact Factor
Show more


26 Reads
Available from