RNA interference-mediated knockdown of CD49e (α5 integrin chain) in human thymic epithelial cells modulates the expression of multiple genes and decreases thymocyte adhesion

Abstract Background The thymus is a central lymphoid organ, in which bone marrow-derived T cell precursors undergo a complex process of maturation. Developing thymocytes interact with thymic microenvironment in a defined spatial order. A component of thymic microenvironment, the thymic epithelial cells, is crucial for the maturation of T-lymphocytes through cell-cell contact, cell matrix interactions and secretory of cytokines/chemokines. There is evidence that extracellular matrix molecules play a fundamental role in guiding differentiating thymocytes in both cortical and medullary regions of the thymic lobules. The interaction between the integrin α5β1 (CD49e/CD29; VLA-5) and fibronectin is relevant for thymocyte adhesion and migration within the thymic tissue. Our previous results have shown that adhesion of thymocytes to cultured TEC line is enhanced in the presence of fibronectin, and can be blocked with anti-VLA-5 antibody. Results Herein, we studied the role of CD49e expressed by the human thymic epithelium. For this purpose we knocked down the CD49e by means of RNA interference. This procedure resulted in the modulation of more than 100 genes, some of them coding for other proteins also involved in adhesion of thymocytes; others related to signaling pathways triggered after integrin activation, or even involved in the control of F-actin stress fiber formation. Functionally, we demonstrated that disruption of VLA-5 in human TEC by CD49e-siRNA-induced gene knockdown decreased the ability of TEC to promote thymocyte adhesion. Such a decrease comprised all CD4/CD8-defined thymocyte subsets. Conclusion Conceptually, our findings unravel the complexity of gene regulation, as regards key genes involved in the heterocellular cell adhesion between developing thymocytes and the major component of the thymic microenvironment, an interaction that is a mandatory event for proper intrathymic T cell differentiation.

Computational framework to support integration of biomolecular and clinical data within a translational approach

Background The use of the knowledge produced by sciences to promote human health is the main goal of translational medicine. To make it feasible we need computational methods to handle the large amount of information that arises from bench to bedside and to deal with its heterogeneity. A computational challenge that must be faced is to promote the integration of clinical, socio-demographic and biological data. In this effort, ontologies play an essential role as a powerful artifact for knowledge representation. Chado is a modular ontology-oriented database model that gained popularity due to its robustness and flexibility as a generic platform to store biological data; however it lacks supporting representation of clinical and socio-demographic information. Results We have implemented an extension of Chado – the Clinical Module - to allow the representation of this kind of information. Our approach consists of a framework for data integration through the use of a common reference ontology. The design of this framework has four levels: data level, to store the data; semantic level, to integrate and standardize the data by the use of ontologies; application level, to manage clinical databases, ontologies and data integration process; and web interface level, to allow interaction between the user and the system. The clinical module was built based on the Entity-Attribute-Value (EAV) model. We also proposed a methodology to migrate data from legacy clinical databases to the integrative framework. A Chado instance was initialized using a relational database management system. The Clinical Module was implemented and the framework was loaded using data from a factual clinical research database. Clinical and demographic data as well as biomaterial data were obtained from patients with tumors of head and neck. We implemented the IPTrans tool that is a complete environment for data migration, which comprises: the construction of a model to describe the legacy clinical data, based on an ontology; the Extraction, Transformation and Load (ETL) process to extract the data from the source clinical database and load it in the Clinical Module of Chado; the development of a web tool and a Bridge Layer to adapt the web tool to Chado, as well as other applications. Conclusions Open-source computational solutions currently available for translational science does not have a model to represent biomolecular information and also are not integrated with the existing bioinformatics tools. On the other hand, existing genomic data models do not represent clinical patient data. A framework was developed to support translational research by integrating biomolecular information coming from different “omics” technologies with patient’s clinical and socio-demographic data. This framework should present some features: flexibility, compression and robustness. The experiments accomplished from a use case demonstrated that the proposed system meets requirements of flexibility and robustness, leading to the desired integration. The Clinical Module can be accessed in http://dcm.ffclrp.usp.br/caib/pg=iptrans webcite.