Recent advances in imaging technology and fluorescent probes have made it possible to gain information about the dynamics of subcellular processes at unprecedented spatiotemporal scales. Unfortunately, a lack of automated tools to efficiently process the resulting imaging data encoding the fine details of the biological processes remains a major bottleneck in utilizing the full potential of these powerful experimental techniques. Here we present a computational tool, called PunctaSpecks, that can characterize fluorescence signals arising from a wide range of biological molecules under normal and pathological conditions. Among other things, the program can calculate the number, areas, life-times, and amplitudes of fluorescence signals arising from multiple sources, track diffusing fluorescence sources like moving mitochondria, and determine the overlap probability of two processes or organelles imaged using indicator dyes of different colors. We have tested PunctaSpecks on synthetic time-lapse movies containing mobile fluorescence objects of various sizes, mimicking the activity of biomolecules. The robustness of the software is tested by varying the level of noise along with random but known pattern of appearing, disappearing, and movement of these objects. Next, we use PunctaSpecks to characterize protein-protein interaction involved in store-operated Ca²⁺ entry through the formation and activation of plasma membrane-bound ORAI1 channel and endoplasmic reticulum membrane-bound stromal interaction molecule (STIM), the evolution of inositol 1,4,5-trisphosphate (IP₃)-induced Ca²⁺ signals from sub-micrometer size local events into global waves in human cortical neurons, and the activity of Alzheimer’s disease-associated β amyloid pores in the plasma membrane. The tool can also be used to study other dynamical processes imaged through fluorescence molecules. The open source algorithm allows for extending the program to analyze more than two types of biomolecules visualized using markers of different colors.

成像技术和荧光探针的最新进展使得在前所未有的时空尺度上获得有关亚细胞过程动力学的信息成为可能。不幸的是，缺乏自动化工具来有效地处理编码生物过程的精细细节的所得成像数据仍然是利用这些强大实验技术的全部潜力的主要瓶颈。在这里，我们提出了一种称为 PunctaSpecks 的计算工具，它可以表征在正常和病理条件下由各种生物分子产生的荧光信号。除其他外，该程序可以计算来自多个来源的荧光信号的数量、面积、寿命和幅度，跟踪扩散的荧光源，如移动的线粒体，并确定使用不同颜色的指示剂染料成像的两个过程或细胞器的重叠概率。我们已经在包含各种尺寸的移动荧光物体的合成延时电影上测试了 PunctaSpecks，模拟了生物分子的活动。通过改变噪声水平以及这些对象出现、消失和移动的随机但已知模式来测试软件的稳健性。接下来，我们使用 PunctaSpecks 来表征存储操作的 Ca 中涉及的蛋白质 - 蛋白质相互作用 通过改变噪声水平以及这些对象出现、消失和移动的随机但已知模式来测试软件的稳健性。接下来，我们使用 PunctaSpecks 来表征存储操作的 Ca 中涉及的蛋白质 - 蛋白质相互作用 通过改变噪声水平以及这些对象出现、消失和移动的随机但已知模式来测试软件的稳健性。接下来，我们使用 PunctaSpecks 来表征存储操作的 Ca 中涉及的蛋白质 - 蛋白质相互作用²⁺通过质膜结合 ORAI1 通道和内质网膜结合基质相互作用分子 (STIM) 的形成和激活进入，肌醇 1,4,5-三磷酸 (IP ₃ ) 诱导的 Ca ²⁺信号的演变来自将亚微米大小的局部事件转化为人类皮层神经元中的全局波，以及质膜中与阿尔茨海默病相关的 β 淀粉样蛋白孔的活动。该工具还可用于研究通过荧光分子成像的其他动态过程。开源算法允许扩展程序以分析使用不同颜色标记可视化的两种以上类型的生物分子。