Spatially Multiplexed Imaging of Complex Signaling Networks - Neurons and other brain cells employ signal transduction networks to convert cellular inputs into cellular outputs. For example, brain cells receive inputs (e.g., neuromodulators such as dopamine and norepinephrine) which trigger the production, entry, and/or release of a diversity of intracellular messengers (e.g., Ca2+, cAMP), engage proteins that enduringly change cellular state (e.g., kinases such as PKA and MAPK), and drive changes in the cell (e.g., plasticity, changes in gene expression, and synthesis or release of other molecules). Ideally, one could image different parts of a signaling cascade in the same cell, so that the relationship between different signals could be understood, in the brain of an awake behaving animal, without requiring a biology group to purchase expensive new hardware. To enable essentially arbitrary numbers of signals to be imaged at once, with ordinary microscopes, we propose a radically different way to image many signals in the same cell – simply place different reporters at different, randomly located, but stable, places throughout a living cell. Then, while the cell is alive, each punctum of reporter will report the signal measured by that reporter, at that site. Our first paper on such spatially multiplexed imaging, published in Cell (and featured on the cover) in 2020 (Linghu*, Johnson*, et al., Cell, 2020), reported a modular protein design that uses self-assembling peptides, fused to existing genetically encoded indicators of cellular signals, and to reporter-identifying epitopes that could be stained for, later. Such self-assembling peptides cluster the reporters at random, stable points throughout cells, resulting in what we call signaling reporter islands (SiRIs). Live imaging can proceed with a simple microscope, to image many things at once. Then, the specimen is preserved, and epitopes that distinguish the indicators can be stained, to identify the reporter at each punctum. SiRIs are ideally spaced close enough to sample the relevant biology, but far enough to be resolved by a microscope. We now submit this first grant aimed at extending the SiRI toolbox to become powerful, simple toolbox for neuroscientists. Specifically, we will (Aim 1) using generative AI, protein design, and end-to-end screening and validation techniques, create 10 novel SiRIs, validating the resulting sensors in both efficacy and safety, and sensor quality, in cultured mouse hippocampal neurons and mouse hippocampal brain slices; (Aim 2) design, optimize, and validate SiRI for 7-transmembrane protein-based fluorescent reporters of neuromodulators and other cellular inputs (mSiRI); and (Aim 3) optimize, and validate, SiRI/mSiRI for in vivo usage, creating a pipeline for expressing, and imaging, SiRI reporters in the awake mouse cortex, and further validating SiRI reporters on two signaling pathways (the astrocytic lactate shuttle, and GPCR signaling cascades triggered by norepinephrine). Our goal is to deliver to the neuroscience community a powerful, easy to use method systematically imaging signal transduction cascades, to understand how they work. We will share all tools freely as we have in the past, with our previous tools in use by many thousands of scientists around the world.
