Application of microarrays to identify and characterize genes involved in attachment dependence in HeLa cells
The ability to modify cellular properties such as adhesion is of interest in the design and performance of biotechnology-related processes. The current study was undertaken in order to evaluate the effectiveness of modulating cellular adhesion in HeLa cells from a genomics perspective. Using DNA microarrays, differences in gene expression between two phenotypically distinct, anchorage-dependent and anchorage-independent, HeLa cell lines were identified. With the aid of several statistical methods and an extensive literature search, two genes were selected as potential targets for further study: siat7e and lama4.Subsequently, experiments were carried out to investigate the effects of siat7e and lama4 separately, on adhesion in HeLa cells by altering their expression in vivo. Decreasing the expression of siat7e, a type II membrane glycosylating sialyltransferase, in anchorage-independent HeLa cells using short interfering RNA (siRNA) resulted in greater aggregation (i.e. clumping) and morphological changes as compared to untreated anchorage-independent HeLa cells. Similar effects were seen in anchorage-independent HeLa cells when the expression of lama4 which encodes laminin α4, a member of the laminin family of glycoproteins, was enhanced as compared to untreated anchorage-independent HeLa cells. Using a shear flow chamber, an attachment assay was developed; illustrating either increased expression of siat7e or decreased expression of lama4 in anchorage-dependent HeLa cells reduced cellular adhesion.Collectively, the results of this study are consistent with the roles siat7e and lama4 play in adhesion processes in vivo and indicate modifying the expression of either gene can influence adhesion in HeLa cells. The strategy of applying bioinformatics techniques to characterize and manipulate phenotypic behaviors is a powerful tool for altering the properties of various cell lines for desired biotechnology objectives.
Journal: Metabolic Engineering - Volume 9, Issue 3, May 2007, Pages 241–251