Institute of Physics, Swiss Federal Institute of Technology Lausanne (EPFL), Lausanne, Switzerland.
Institute of Bioengineering, Swiss Federal Institute of Technology Lausanne (EPFL), Lausanne, Switzerland.
Nat Methods. 2022 Oct;19(10):1262-1267. doi: 10.1038/s41592-022-01589-x. Epub 2022 Sep 8.
A common goal of fluorescence microscopy is to collect data on specific biological events. Yet, the event-specific content that can be collected from a sample is limited, especially for rare or stochastic processes. This is due in part to photobleaching and phototoxicity, which constrain imaging speed and duration. We developed an event-driven acquisition framework, in which neural-network-based recognition of specific biological events triggers real-time control in an instant structured illumination microscope. Our setup adapts acquisitions on-the-fly by switching between a slow imaging rate while detecting the onset of events, and a fast imaging rate during their progression. Thus, we capture mitochondrial and bacterial divisions at imaging rates that match their dynamic timescales, while extending overall imaging durations. Because event-driven acquisition allows the microscope to respond specifically to complex biological events, it acquires data enriched in relevant content.
荧光显微镜的一个共同目标是收集特定生物事件的数据。然而,从样本中可以收集到的特定于事件的内容是有限的,特别是对于罕见或随机过程。这在一定程度上是由于光漂白和光毒性,它们限制了成像速度和持续时间。我们开发了一种事件驱动的采集框架,其中基于神经网络的特定生物事件的识别触发即时结构光照显微镜中的实时控制。我们的设置通过在检测到事件发生时切换到慢成像速率,以及在事件进行时切换到快成像速率,在飞行中自适应采集。因此,我们以与它们的动态时间尺度相匹配的成像速率捕获线粒体和细菌分裂,同时延长整体成像持续时间。由于事件驱动的采集允许显微镜专门响应复杂的生物事件,因此它可以获取富含相关内容的数据。