RESULTS: As a contribution, we have developed automated Ca2+ spiking analysis (CaSA) software that performs i) automated peak detection, ii) statistical analyses based on the detected peaks, iii) autocorrelation analysis of peak-to-peak intervals to highlight major traits in the spiking pattern.We have evaluated CaSA in two experimental studies. In the first, CaSA highlighted unpredicted differences in the spiking patterns induced in Medicago truncatula root epidermal cells by exudates of the AM fungus Gigaspora margarita as a function of the phosphate concentration in the growth medium of both host and fungus. In the second study we compared the spiking patterns triggered by either AM fungal or rhizobial symbiotic signals. CaSA revealed the existence of different patterns in signal periodicity, which are thought to contribute to the so-called Ca2+ signature.
CONCLUSIONS: We therefore propose CaSA as a useful tool for characterizing oscillatory biological phenomena such as Ca2+ spiking.
结果:作为贡献,我们开发了自动Ca2+尖峰分析(CaSA)软件,该软件执行i)自动峰值检测,ii)基于检测到的峰值的统计分析,iii)峰间间隔的自相关分析,以突出加标模式中的主要性状。我们在两项实验研究中评估了CaSA。在第一,CaSA强调了AM真菌Gigasporamargarita的渗出物在紫花苜蓿根表皮细胞中诱导的加标模式与宿主和真菌生长培养基中磷酸盐浓度的关系。在第二项研究中,我们比较了由AM真菌或根瘤菌共生信号触发的尖峰模式。CaSA揭示了信号周期性存在不同模式,它们被认为有助于所谓的Ca2+签名。
结论:因此,我们提出CaSA作为表征振荡生物学现象如Ca2+尖峰的有用工具。