Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.666748
Title: A systems biology approach to musculoskeletal tissue engineering : transcriptomic and proteomic analysis of cartilage and tendon cells
Author: Mueller, Alan
ISNI:       0000 0004 5357 0760
Awarding Body: University of Liverpool
Current Institution: University of Liverpool
Date of Award: 2015
Availability of Full Text:
Access from EThOS:
Access from Institution:
Abstract:
Disorders of cartilage and tendon account for a high incidence of disability and are highly prevalent co-morbidities within the ageing population; therefore, musculoskeletal disorders represent a major public health policy issue. Despite considerable efforts to characterise biochemical and biomechanical cues that promote a stable differentiated cartilage or tendon phenotype in vitro the benchmarks by which progress is measured are limited. Common regenerative interventions, such as autologous cartilage implantation, have a required period of monolayer expansion that induces a loss of the functional phenotype, termed dedifferentiation. Dedifferentiation has no definitive mechanism yet is widely described in both regenerative and degenerative contexts; in addition to stem cell transplantation and cell-seeding in three-dimensional scaffolds, dedifferentiation represents the third approach to the development of regenerative mechanisms for mammalian tissue repair. Cartilage and tendon show a number of common features in structure, develop, disease, and repair. The extracellular matrix is a dynamic and complex structure that confers the functional mechanical properties of cartilage and tendon. Dysregulation of production and degradation are critical to the pathophysiology of musculoskeletal disorders, therefore, reparative interventions require a stable, functional phenotype from the outset. Cartilage and tendon demonstrate a commonality in terms of function defining structure both being sparsely cellular with a preponderance of collagenous matrix. Parity of functionality with the pre- injury state after healing is rarely achieved for cartilage and tendon. Cartilage and  tendon also share common embryological origins. Common mesenchymal progenitor cells differentiate into many musculoskeletal tissues with diverse functions. Specialist sub-populations of tendon and cartilage progenitors enable formation of transitional zones between these developing tissues. The development of musculoskeletal structures does not occur in isolation, however, cartilage and tendon have not previously been considered together in a systems context. An integrated understanding of the differentiation of these tissues should inform regenerative therapies and tissue engineering strategies. Systems biology is paradigm shift in scientific thinking where traditional reductionist strategies to complex biological problems have been superseded by a holistic philosophy seeking to understand the emergent behavior of a system by the integrative and predictive modeling of all elements of that system. Whole transcriptome and proteome profiling studies are used to collect quantitative data about a system, which may then be exploited by systems biology methodologies including the analysis of gene and protein networks. Gene-gene co-expression relationships, which are core regulatory mechanisms in biology, are often not part of a comprehensive gene expression analysis. Many biological networks are sparse and have a scale-free topology, which generally indicates that the majority of genes have very few connections, whilst certain key regulators, or ‘hubs’, are highly interconnected. Co-expression networks may be used to define regulatory sub- networks and ‘hubs’ that have phenotypic associations. This approach allows all quantitative data to be used and makes no a priori assumptions about relationships in the system and, therefore, can facilitate the exploration of emergent behavior in the system and the generation of novel hypotheses. The ultimate goal of tissue engineering is the replacement of lost or damaged cells, and in vitro, to develop biomimetic (organotypic) structures to serve as experimental models. Tissues, and the strategies to functionally replicate them ex vivo, are complex and require an integrated, multi-disciplinary approach. Systems biology approaches, using data arising from multiple-levels of the biological hierarchy, can facilitate the development of predictive models for bioengineered tissue. The iterative refinement, quantification, and perturbation of these models may expedite the translation of well-validated organotypic systems, through legal regulatory frameworks, into regenerative strategies for musculoskeletal disorders in humans. In this thesis the systems under consideration are the major cell populations of cartilage and tendon (chondrocytes and tenocytes, respectively). They are described in three environmental conditions: native tissue, monolayer (two- dimensional), or three-dimensional models. There has been no systematic investigate of the global gene and protein profiles of cartilage and tendon in their native state relative to monolayer or three-dimensional cultures. There is no clear mechanistic description of the impact of in vitro environmental perturbations on the system or indeed the adequacy of these models as proxies for cartilage and tendon. A discovery approach using transcriptomic and proteomic profiling is undertaken to define a robust and consistent gene and protein profile for each condition. Differentially expressed elements are functionally annotated and pathway topology approaches employed to predict major signalling pathways associated with the observed phenotype. This study defines dedifferentiated chondrocytes and tenocytes in monolayer culture as expressing markers of musculoskeletal development, including scleraxis (Scx) and Mohawk (Mkx). Furthermore, there is reproducible synthetic profile convergence in monolayer culture between cartilage and tendon cells. Standard three-dimensional culture systems for chondrocyte and tenocytes fail to replicate the gene expression profile of cartilage and tendon. The PI-3K/Akt signaling pathway is predicted to be the predominant canonical pathway associated with de- and re-differentiation in vitro. Using novel, and publically available, transcriptomic data sets a meta-analysis of microarray gene expression profiles is performed using weighted gene co- expression network analysis. This is employed for transcriptome network decomposition to isolate highly correlated and interconnected gene-sets (modules) from gene expression profiles of cartilage and tendon cells in different environmental conditions. Sub-networks strongly associated with de- and re- differentiation phenotypes are defined. Comparison of global transcriptome network architecture was performed to define the conservation of network modules between a model species (rat) and human data. In addition to the annotation of an osteoarthritis-associated module in the rat a class-prediction analysis defined a minimal gene signature for the prediction of three-dimensional cultures from standard monolayer culture. Finally, proteomic and transcriptomic data sets are integrated by defining common upstream regulators (TGFB and PDGF BB) and unified mechanistic networks are generated for de- and re- differentiation. The studies collected in this thesis contribute to a wider understanding of cartilage and tendon tissue engineering and organotypic culture development. A clear mechanistic understanding of the regulatory networks controlling differentiation of cartilage and tendon progenitor cells is required in order to develop improved in vitro models and bio-engineered tissue that are physiologically relevant. The findings presented here provide practical outputs and testable hypotheses to drive future evidence-based research in organotypic culture development for musculoskeletal tissues.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.666748  DOI: Not available
Keywords: Q Science (General)
Share: