Integrative molecular biology requires understanding interactions of large numbers of pathways. Similarly, molecular medicine increasingly relies on complex macromolecular diagnostics to guide therapeutic choices. A fundamental argument for laser capture microdissection (LCM) of tissues is that without separation of specific cell populations from complex tissues, we will miss critical control functions of thousands of regulated transcription factors, cell regulators, and receptors that are expressed at low copy number. Without detecting changes in many of these critical effectors, the integrative understanding of tissue function and pathology will not proceed effectively. In complex tissues - particularly among pathological variations - it is exceptionally difficult to measure the majority of molecules that are at low copy number per cell without first isolating specific cell populations. For example, in a recent collaboration with the NEI, we adapted LCM method to isolate localized (3D) cells at the site of retinal topoglogical closure and performed microarray analysis of gene expression at 8 time points of embryonic development. This enabled us to identify low copy number transcriptions factors that when blocked lead to loss of closure in animal models. These transcription factors and approximately 200 other temporally and spatially covarying genes appear likely to play a role in coloboma, an inborn developmental defect of the retina occurring in humans. We are developing novel mathematical approaches capable of more comprehensively identifying within such datasets the specific networks of genes that drive such local tissue development. The LCM techniques that we started developing fourteen years ago are now widely used in molecular analysis of genetics and gene expression changes within target cells within complex tissues. However, in global proteomic and lipid studies without molecular amplification methods, the quantity of isolated cells sufficient to perform accurate characterization of less abundant species is problematic as the microscopic visualization, targeting, and isolation in laser microdissection has a maximal rate of about 1 to 20 cells per second depending on their microscopic distribution within the tissues. Recently, in collaboration with NCI and CIT, we invented and are now refining an automatic target-directed microtransfer technique based on macromolecule-specific staining of cells not requiring user visualization or microscopic targeting and capable of much higher throughput rates. This technique (patent pending) is built on our physical understanding of thermoplastic microtransfer and uses a much simpler device and transfer films than commercial laser microdissection instruments. This rapid, automated microtransfer method has improved spatial resolution (1 micron) and is consequently particularly well-suited to isolate highly dispersed, specific cell populations (e.g., specific neurons in the brain) or specific organelles (e.g., neuronal nuclei in the brain). The spatial relationships (morphology) among the specific cells in the tissue are preserved on the transfer film. In collaboration with Drs Markey, Lippincott-Schwartz, and Morgan under an NIH Directors Challenge Award, we are applying our technology to proteomics studies of subcellular organelles. As this technology becomes more robust, we will seek to integrate the microtransfer with molecular profiling of specific organelles or isolated cells within tissues, including routine proteomic and lipidomic analyses, particularly greater sensitivity to molecular species less abundant in grosser tissue samples. If microdissection and molecular analysis can be made clinically practical, the expression levels of sets of approximately 20 to 100 critical, stage-specific disease markers within a selected cell population might provide reliable diagnosis and intermediate endpoints of response to molecular therapies in individual patients. Our analysis of large gene expression and protein databases suggests that a significant fraction of all genes is expressed in any specific cell type and that the levels of gene products universally exhibit a highly skewed power-law distribution similar to those characterizing many other complex systems. We have developed mathematical models for the evolution of such distributions that predict the observed distributions of genes, protein domains, and gene expression observed in species of increasing biological complexity. In normal human physiology, homeostasis arises from a highly robust interacting network of large number of gene products in specific cell phenotypes that interact directly through direct and hormonal interactions with many other cellular phenotypes. We foresee an evolution of molecular diagnosis from one based on the qualitative or quantitative analysis of a few key biomarker macromolecules to one in which special clustering algorithms analyze complex multivariate databases. Such analyses should permit a more complete identification of highly correlated clinical cases and allow us to characterize their response to molecular therapies specifically designed to prevent progression. We are attempting to develop new approaches for better integration of our thermoplastic microtransfer methods of microdissection with downstream macromolecular analysis to permit more routine and simpler multiplex molecular diagnostics. A key feature is using the polymer matrix in which target cells are embedded for affinity purification and then for direct optical detection within the transparent polymer. Using a variety of microscopy techniques in our lab, we seek to quantitatively characterize protocols for incorporating affinity nanoparticles in the tissue and polymer matrix. In the longer term, we foresee using in situ optical labels to quantify the spatial distributions of specific molecules captured within the microtransfer and retained following simpler purification steps. Coupling the robust and simple automatic microdissection with rapid purification and detection of species might provide unique abilities to follow macromolecular changes in normal tissue development and in human pathologies. We are working on integrating the statistics of expression levels spatially and temporally correlated within specific cell populations with pathway and transcription factor databases to provide a more integrated approach to molecular physiology. With future integration of microdissection and macromolecular analysis, we believe the critical role for many less abundantly expressed genes in determining normal function and pathological changes will be more easily studied and integrated into molecular diagnostics and selection of clinical therapies.
