ABSTRACT The goal of this Bioengineering Research Grant (BRG) proposal is to develop fluorescent labels for single-cell classification through imaging of intact three-dimensional tissue. We are focusing on semiconductor quantum dots (QDs), nanocrystals that exhibit bright fluorescence and unique optical and electronic properties. We designed new classes of QDs which we propose will allow quantitative, multispectral analysis of 30 or more distinct molecules so that hyperspectral light sheet microscopy can be used to proteomically profile and comprehensively map 20 or more distinct cell types throughout an intact tissue after a single staining step. This technology addresses an outstanding bottleneck in optical microscopy of three-dimensional tissue, for which only 3 distinct molecular markers can be easily distinguished, limiting the capacity to precisely classify cell types and to co-localize different cell types. This proposal comes at a time when new light sheet microscopes have recently become widely available for full-thickness imaging of optically cleared tissues at sub-cellular resolution such that rapid advances in multiplexing could yield rapid impacts. As an example, the investigators of this project developed workflows to optically clear, immunolabel, and image intact adipose tissues from lean and obese rodent models, in addition to software to comprehensively identify cells based on fluorescent immunostains, and deep learning algorithms to automate microenvironment segmentation. With these advances, we were able to discover new classes of immune microenvironments in adipose tissue that are believed to promote comorbidities of obesity, such as type 2 diabetes and heart disease. However key hypotheses regarding the nature of these microenvironments cannot be readily addressed until we can discretely categorize cells based on their molecular expression patterns within their contextual microenvironments. In this proposal, our technological goal is to develop fluorophores for high-content multiplexing in intact tissues. Our biological goal is to use these tools to understand immune cell microenvironments that regulate adipose tissue in the state of obesity. Our Specific Aims are to (1) engineer the photophysics of new classes of QD-based labels, (2) conjugate these labels to antibody fragments and validate their target specificity as molecular probes, (3) quantitatively evaluate cell labeling and classification accuracy in three-dimensional adipose tissue, and (4) apply probe panels to quantify adipose immune microenvironments at the cellular level in the lean and obese states. This is a collaborative proposal between engineers and scientists with expertise in quantum dots and molecular probes (Andrew Smith), advanced optical microscopy (Paul Selvin), biomedical image computing (Mark Anastasio), cellular immunology (Erik Nelson), and animal models of obesity (Kelly Swanson).

NARRATIVE Classification of cells within human tissues is essential for understanding states of health and disease. In this proposal, we will develop a new class of fluorescent label that increases the number of molecular classification markers for cells by an order of magnitude. These labels function within intact, three-dimensional tissue, an attribute that we will use to map the local environments of adipose tissue immune cells that are thought to determine comorbid outcomes of obesity.