Welzel Oliver, Boening Daniel, Stroebel Armin, Reulbach Udo, Klingauf Jurgen, Kornhuber Johannes, Groemer Teja Wolfgang
Department of Psychiatry and Psychotherapy, University of Erlangen-Nuremberg, Schwabachanlage 6, 91054, Erlangen, Germany.
Eur Biophys J. 2009 Sep;38(7):883-9. doi: 10.1007/s00249-009-0458-5. Epub 2009 Apr 30.
On their way to the synapse and back, neuronal proteins are carried in cargo vesicles along axons and dendrites. Here, we demonstrate that the key parameters of axonal transport, i.e., particle velocities and pausing times can be read out from CCD-camera images automatically. In the present study, this is achieved via cross- and autocorrelation of kymograph columns. The applicability of the method was measured on simulated kymographs and data from axonal transport timeseries of mRFP-labeled synaptophysin. In comparing outcomes of velocity determinations via a performance parameter that is analogous to the signal-to-noise ratio (SNR) definition, we find that outcomes are dependent on sampling, particle numbers and signal to noise of the kymograph. Autocorrelation of individual columns allows exact determination of pausing time populations. In contrast to manual tracking, correlation does not require experience, a priori assumptions or disentangling of individual particle trajectories and can operate at low SNR.
在往返突触的过程中，神经元蛋白通过货物囊泡沿着轴突和树突运输。在此，我们证明轴突运输的关键参数，即颗粒速度和暂停时间，可以从电荷耦合器件（CCD）相机图像中自动读出。在本研究中，这是通过对记录速度图的列进行互相关和自相关来实现的。该方法的适用性在模拟记录速度图以及来自mRFP标记的突触素轴突运输时间序列的数据上进行了测量。通过类似于信噪比（SNR）定义的性能参数比较速度测定的结果时，我们发现结果取决于采样、颗粒数量和记录速度图的信噪比。单个列的自相关允许精确确定暂停时间群体。与手动跟踪相比，相关性不需要经验、先验假设或解开单个颗粒轨迹，并且可以在低信噪比下运行。
