In many forms of retinal degeneration, photoreceptors die but inner retinal circuits remain intact. In the rd1 mouse, an established model for blinding retinal diseases, spontaneous activity in the coupled network of AII amacrine and ON cone bipolar cells leads to rhythmic bursting of ganglion cells. Since such activity could impair retinal and/or cortical responses to restored photoreceptor function, understanding its nature is important for developing treatments of retinal pathologies. Here we analyzed a compartmental model of the wild-type mouse AII amacrine cell to predict that the cell's intrinsic membrane properties, specifically, interacting fast Na and slow, M-type K conductances, would allow its membrane potential to oscillate when light-evoked excitatory synaptic inputs were withdrawn following photoreceptor degeneration. We tested and confirmed this hypothesis experimentally by recording from AIIs in a slice preparation of rd1 retina. Additionally, recordings from ganglion cells in a whole mount preparation of rd1 retina demonstrated that activity in AIIs was propagated unchanged to elicit bursts of action potentials in ganglion cells. We conclude that oscillations are not an emergent property of a degenerated retinal network. Rather, they arise largely from the intrinsic properties of a single retinal interneuron, the AII amacrine cell.
The mechanoreceptive sensory hair cells in the inner ear are selectively vulnerable to numerous genetic and environmental insults. In mammals, hair cells lack regenerative capacity, and their death leads to permanent hearing loss and vestibular dysfunction. Their paucity and inaccessibility has limited the search for otoprotective and regenerative strategies. Growing hair cells in vitro would provide a route to overcome this experimental bottleneck. We report a combination of four transcription factors (Six1, Atoh1, Pou4f3, and Gfi1) that can convert mouse embryonic fibroblasts, adult tail-tip fibroblasts and postnatal supporting cells into induced hair cell-like cells (iHCs). iHCs exhibit hair cell-like morphology, transcriptomic and epigenetic profiles, electrophysiological properties, mechanosensory channel expression, and vulnerability to ototoxin in a high-content phenotypic screening system. Thus, direct reprogramming provides a platform to identify causes and treatments for hair cell loss, and may help identify future gene therapy approaches for restoring hearing.
Ribbon-type presynaptic active zones are a hallmark of excitatory retinal synapses, and the ribbon organelle is thought to serve as the organizing point of the presynaptic active zone. Imaging of exocytosis from isolated retinal neurons, however, has revealed ectopic release (i.e., release away from ribbons) in significant quantities. Here, we demonstrate in an in vitro mouse retinal slice preparation that ribbon-independent release from rod bipolar cells activates postsynaptic AMPARs on AII amacrine cells. This form of release appears to draw on a unique, ribbon-independent, vesicle pool. Experimental, anatomical, and computational analyses indicate that it is elicited by a significant, global elevation of intraterminal [Ca 2ϩ ] arising following local buffer saturation. Our observations support the conclusion that ribbon-independent release provides a read-out of the average behavior of all of the active zones in a rod bipolar cell's terminal.
High throughput drug screening is an established approach to investigate tumor biology and identify therapeutic leads. Traditional platforms use two-dimensional cultures which do not accurately reflect the biology of human tumors. More clinically relevant model systems such as three-dimensional tumor organoids can be difficult to scale and screen. Manually seeded organoids coupled to destructive endpoint assays allow for the characterization of treatment response, but do not capture transitory changes and intra-sample heterogeneity underlying clinically observed resistance to therapy. We present a pipeline to generate bioprinted tumor organoids linked to label-free, time-resolved imaging via high-speed live cell interferometry (HSLCI) and machine learning-based quantitation of individual organoids. Bioprinting cells gives rise to 3D structures with unaltered tumor histology and gene expression profiles. HSLCI imaging in tandem with machine learning-based segmentation and classification tools enables accurate, label-free parallel mass measurements for thousands of organoids. We demonstrate that this strategy identifies organoids transiently or persistently sensitive or resistant to specific therapies, information that could be used to guide rapid therapy selection.
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