Abstract
BackgroundThe dynamic growing and shortening behaviors of microtubules are central to the fundamental roles played by microtubules in essentially all eukaryotic cells. Traditionally, microtubule behavior is quantified by manually tracking individual microtubules in time-lapse images under various experimental conditions. Manual analysis is laborious, approximate, and often offers limited analytical capability in extracting potentially valuable information from the data.ResultsIn this work, we present computer vision and machine-learning based methods for extracting novel dynamics information from time-lapse images. Using actual microtubule data, we estimate statistical models of microtubule behavior that are highly effective in identifying common and distinct characteristics of microtubule dynamic behavior.ConclusionComputational methods provide powerful analytical capabilities in addition to traditional analysis methods for studying microtubule dynamic behavior. Novel capabilities, such as building and querying microtubule image databases, are introduced to quantify and analyze microtubule dynamic behavior.
Highlights
The dynamic growing and shortening behaviors of microtubules are central to the fundamental roles played by microtubules in essentially all eukaryotic cells
MT dynamics are finely regulated in the cell, [1]
It has been hypothesized that inadequate regulation of neuronal MT dynamics may underlie neuronal cell death in Alzheimer's and related dementias, [2]
Summary
The dynamic growing and shortening behaviors of microtubules are central to the fundamental roles played by microtubules in essentially all eukaryotic cells. Microtubules (MTs) are filamentous cytoskeletal structures composed of tubulin protein subunits. These subunits can associate with, or dissociate from, existing tubulin polymers rapidly, making MTs highly dynamic. Through these dynamic behaviors, MTs are critically involved in many essential cellular functions. Drug induced modulation of MT dynamics underlies the effectiveness of various anticancer drugs, such as Taxol, [3]. For these and a host of basic biology issues, the regulation of MT dynamics is a very active area of research in modern cell biology
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