Irene Georgakoudi, PhD, MSc

Institution: Tufts University
Research: Label-free, high resolution, non-destructive imaging of metabolism in living specimens
Categories: Tufts

The Georgakoudi laboratory focuses on the development of label-free, microscopic imaging methods to assess metabolic function in living specimens. We rely on multi-photon imaging approaches that rely for contrast on endogenous fluorescence from molecules such as NAD(P)H, FAD, retinol, and lipofuscin to assess changes in the activity of key metabolic pathways and oxidative stress. We have also shown that NAD(P)H-based two- photon images can be analyzed to quantitatively characterize changes in mitochondrial organization in vivo and without the need for an exogenous label. The goal is to use such techniques to monitor functional metabolic changes in three-dimensional tissues dynamically to improve understanding of their role during development, the function of different adipose tissue types, and in the context of several diseases, including cancer and neurodegeneration/traumatic brain injury. Relevant ongoing projects include the following:

1) Label-free, metabolic function imaging-based detection of cervical pre-cancers in humans. We have shown that a combination of metrics of metabolic function as a function of depth within human cervical epithelial tissue models and freshly excised biopsies can be used to discriminate cervical pre-cancerous tissues from healthy epithelia. Enhanced levels of glycolysis and decreased levels of metabolic function variations within different epithelial tissue layers are main biomarkers of cervical pre-cancers. Metabolic heterogeneity variations are also important discriminators. Our goal is to develop and test a system that enables us to acquire such measurements in humans to assess diagnostic and potentially prognostic performance and ultimately enable accurate detection of pre-cancerous lesion without a biopsy at the time of imaging.
2) Dynamic monitoring of metabolic interactions in engineered brain tissue models during development and following traumatic brain injury. We have shown that label-free, two photon imaging can be used to monitor metabolic function of differentiating stem cells and different brain cell populations. We have also shown that our imaging approaches can identify subpopulations of cells with distinct metabolic function and responses to treatment in three-dimensional engineered tissue models of glioblastoma. Our current studies focus on exploiting such tools to monitor metabolic interactions between neurons, astrocytes, and microglia in engineered brain tissue models of traumatic brain injury to improve our understanding of their role in disease development and responses to potential treatments.