RESUMO
Optical recording of intricate molecular dynamics is becoming an indispensable technique for biological studies, accelerated by the development of new or improved biosensors and microscopy technology. This creates major computational challenges to extract and quantify biologically meaningful spatiotemporal patterns embedded within complex and rich data sources, many of which cannot be captured with existing methods. Here, we introduce Activity Quantification and Analysis (AQuA2), a fast, accurate, and versatile data analysis platform built upon advanced machine learning techniques. It decomposes complex live imaging-based datasets into elementary signaling events, allowing accurate and unbiased quantification of molecular activities and identification of consensus functional units. We demonstrate applications across a wide range of biosensors, cell types, organs, animal models, and imaging modalities. As exemplar findings, we show how AQuA2 identified drug-dependent interactions between neurons and astroglia, and distinct sensorimotor signal propagation patterns in the mouse spinal cord.
RESUMO
In non-mammalian vertebrates, some neurons can regenerate after spinal cord injury. One of these, the giant Mauthner (M-) neuron shows a uniquely direct link to a robust survival-critical escape behavior but appears to regenerate poorly. Here we use two-photon microscopy in parallel with behavioral assays in zebrafish to show that the M-axon can regenerate very rapidly and that the recovery of functionality lags by just days. However, we also find that the site of the injury is critical: While regeneration is poor both close and far from the soma, rapid regeneration and recovery of function occurs for injuries between 10% and 50% of total axon length. Our findings show that rapid regeneration and the recovery of function can be studied at remarkable temporal resolution after targeted injury of one single M-axon and that the decision between poor and rapid regeneration can be studied in this one axon.
