Stem cells have the remarkable ability to self-renew and differentiate during development. In addition, adult self-renewal and differentiation also play an essential role in injury response and overall tissue maintenance. In the past two decades, a considerable effort was made to develop and apply methods of gene expression profiling which are now used to generate atlases of gene expression in different tissues throughout development and in adults. In contrast, considerably less progress has been achieved to develop tools that simultaneously allow multi-gene profiling, manipulation of single cells in situ with minimal perturbation in developing or fully differentiated and aging tissues. Such tools are indispensable to determine how tissues are maintained during the adult life and understand how cells can sometimes enter in an abnormal path that leads to disease. The main challenges posed to capture, interfere and analyze the effects of gene expression in situ in adult and aging tissues with single cell resolution stem from: (1) technical limitations to label and visualize specific cell lineages in inact tissues, (2) the need of non-invasive tools to interfere with specific cell populations and (3) the availability of a reliable system to determine the onset of gene expression in adult and aging tissues. To begin addressing these issues, we have been using a combination of three technologies that allow us to report the temporal birth order of cell lineages by a color-code in intact complex tissues;visualize the expression of several genes with single cell resolution using a combinatorial spectral barcoding in situ hybridization;and finally remove genes within specific cell lineages using RNA interference. In this proposal, we will optimize and expand the range of applications of these technologies to other cell types, which include adult and senescing cells, and make it more accessible to the end-user.
Our studies will provide a way of assessing how multiple genes are activated in adult and senescing cells in complex tissues at single cell level, and provide a powerful toolkit to investigate and engineer tissues in situ. For these reasons, we believe that results from this research are very likely to impact the fields of aging, regenerative medicine, and stroke. The ability to assess adult gene regulation and manipulate transcriptional profiles of selected cell types with single-cell resolution should enhance methods that can be employed in a number of applications, such as multiple probes for detecting early stages of abnormal cellular growth, determining the transcriptional age of tissues, modeling abnormal growth to make prognostic predictions, monitor the appropriate expression of markers, and follow gene expression after damage.
|Atta-Fosu, Thomas; Guo, Weihong; Jeter, Dana et al. (2016) 3D Clumped Cell Segmentation Using Curvature Based Seeded Watershed. J Imaging 2:|