Quantifying Single and Dual Channel Live Imaging Data: Kymograph Analysis of Organelle Motility in Neurons

Abstract

Live imaging is commonly used to study dynamic processes in cells. Many labs carrying out live imaging in neurons use kymographs as a tool. Kymographs display time-dependent microscope data (time-lapsed images) in two-dimensional representations showing position vs. time. Extraction of quantitative data from kymographs, often done manually, is time-consuming and not standardized across labs. We describe here our recent methodology for quantitatively analyzing single color kymographs. We discuss the challenges and solutions of reliably extracting quantifiable data from single-channel kymographs. When acquiring in two fluorescent channels, the challenge becomes analyzing two objects that may co-traffic together. One must carefully examine the kymographs from both channels and decide which tracks are the same or try to identify the coincident tracks from an overlay of the two channels. This process is laborious and time consuming. The difficulty in finding an available tool for such analysis has led us to create a program to do so, called KymoMerge. KymoMerge semi-automates the process of identifying co-located tracks in multi-channel kymographs and produces a co-localized output kymograph that can be analyzed further. We describe our analysis, caveats, and challenges of two-color imaging using KymoMerge.