dFRAME: A Video Recording-Based Analytical Method for Studying Feeding Rhythm in Drosophila.

dFRAME: A Video Recording-Based Analytical Method for Studying Feeding Rhythm in Drosophila.
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DOI:
10.3389/fgene.2021.763200
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发表时间:
2021
影响因子:
3.7
通讯作者:
Li Y
Li Y
中科院分区:
生物学3区
文献类型:
--
作者:
Niu M;Zhang X;Li W;Wang J;Li Y

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动物,从昆虫到人类,表现出明显的摄食行为的昼夜节律。果蝇作为一种遗传动物模型,已经被报道具有摄食节律,但由于缺乏合适和实用的方法,相关研究有限。在这里,我们提出了一种基于视频记录的分析方法,即果蝇摄食节律分析方法(DFRAME)。使用我们新开发的计算机程序FlyFeding,我们提取了单个苍蝇的运动轨迹,并描述了它们接近食物的行为。为了区分摄食和不摄食事件,我们利用高倍率视频记录来优化我们的方法,通过设置截止阈值来消除不摄食事件的干扰。此外,我们还验证了这种方法对雌雄果蝇以及一天中的所有时段都适用。利用该方法,我们分析了野生型和周期突变果蝇的长期饲养状况。研究结果重新捕捉了之前报道的摄食节律,并揭示了这些果蝇在光/暗周期或持续黑暗环境下的摄食模式的详细轮廓。总之,我们的dFRAME方法能够对果蝇的摄食行为进行长期、稳定、可靠和精细的分析。对这一强大的遗传动物模型的高通量研究将获得对摄食节律的分子和神经机制的深刻见解。
Animals, from insects to humans, exhibit obvious diurnal rhythmicity of feeding behavior. Serving as a genetic animal model, Drosophila has been reported to display feeding rhythms; however, related investigations are limited due to the lack of suitable and practical methods. Here, we present a video recording-based analytical method, namely, Drosophila Feeding Rhythm Analysis Method (dFRAME). Using our newly developed computer program, FlyFeeding, we extracted the movement track of individual flies and characterized their food-approaching behavior. To distinguish feeding and no-feeding events, we utilized high-magnification video recording to optimize our method by setting cut-off thresholds to eliminate the interference of no-feeding events. Furthermore, we verified that this method is applicable to both female and male flies and for all periods of the day. Using this method, we analyzed long-term feeding status of wild-type and period mutant flies. The results recaptured previously reported feeding rhythms and revealed detailed profiles of feeding patterns in these flies under either light/dark cycles or constant dark environments. Together, our dFRAME method enables a long-term, stable, reliable, and subtle analysis of feeding behavior in Drosophila. High-throughput studies in this powerful genetic animal model will gain great insights into the molecular and neural mechanisms of feeding rhythms.
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