Department of Mechanical Engineering, York University, Toronto, ON, Canada.
Department of Biology, York University, Toronto, ON, Canada.
Comput Biol Med. 2021 May;132:104314. doi: 10.1016/j.compbiomed.2021.104314. Epub 2021 Mar 7.
In this paper, the heartbeat parameters of small model organisms, i.e. Drosophila melanogaster (fruit fly) and Danio rerio (zebrafish), were quantified in-vivo in intact larvae using microfluidics and a novel MATLAB-based software. Among different developmental stages of flies and zebrafish, the larval stage is privileged due to biological maturity, optical accessibility, and the myogenic nature of the heart. Conventional methods for parametric quantification of heart activities are complex and mostly done on dissected, irreversibly immobilized, or anesthetized larvae. Microfluidics has helped with reversible immobilization without the need for anesthesia, but heart monitoring is still done manually due to challenges associated with the movement of floating organs and cardiac interruptions. In our MATLAB software applied to videos recorded in microfluidic-based whole-organism assays, we have used image segmentation to automatically detect the heart and extract the heartbeat signal based on pixel intensity variations of the most contractile region of the heart tube. The smoothness priors approach (SPA) was applied to remove the undesired low-frequency noises caused by environmental light changes or heart movement. Heart rate and arrhythmicity were automatically measured from the detrended heartbeat signal while other parameters including end-diastolic and end-systolic diameters, shortening distance, shortening time, fractional shortening, and shortening velocity were quantified for the first time in intact larvae, using M-mode images under bright field microscopy. The software was able to detect more than 94% of the heartbeats and the cardiac arrests in intact Drosophila larvae. Our user-friendly software enables in-vivo quantification of D. melanogaster and D. rerio larval heart functions in microfluidic devices, with the potential to be applied to other biological models and used for automatic screening of drugs and alleles that affect their heart.
本文使用微流控技术和一种新的基于 MATLAB 的软件，对小模式生物（即黑腹果蝇和斑马鱼）的心跳参数进行了体内量化。在蝇和鱼的不同发育阶段中，幼虫阶段由于其具有生物学成熟度、光学可及性和心肌的性质而具有优势。对心脏活动进行参数量化的传统方法较为复杂，且大多应用于解剖、不可逆固定或麻醉的幼虫。微流控技术有助于实现可逆固定，而无需使用麻醉剂，但由于浮动器官运动和心脏中断相关的挑战，心脏监测仍需手动进行。在我们应用于基于微流控全器官检测的视频的 MATLAB 软件中，我们使用图像分割自动检测心脏，并根据心脏管最收缩区域的像素强度变化提取心跳信号。平滑先验方法（SPA）被应用于去除由环境光变化或心脏运动引起的不需要的低频噪声。从去趋势的心跳信号中自动测量心率和心律失常，同时首次在完整幼虫中使用明场显微镜下的 M 模式图像量化其他参数，包括舒张末期和收缩末期直径、缩短距离、缩短时间、分数缩短和缩短速度。该软件能够检测到超过 94%的完整黑腹果蝇幼虫的心跳和心脏骤停。我们的用户友好型软件能够在微流控设备中对 D. melanogaster 和 D. rerio 幼虫的心脏功能进行体内量化，具有应用于其他生物模型并用于自动筛选影响其心脏的药物和等位基因的潜力。
