Microtubule tip tracking and tip structures at the nanometer scale using digital fluorescence microscopy

Alexei O. Demchouk, Melissa K. Gardner, David J. Odde

Research output: Contribution to journalArticlepeer-review

44 Scopus citations

Abstract

Microtubules (MTs) are central to fundamental cellular processes including mitosis, polarization, and axon extension. A key issue is to understand how MT-associated proteins and therapeutic drugs, such as the anticancer drug paclitaxel, control MT self-assembly. To facilitate this research, it would be helpful to have automated methods that track the tip of dynamically assembling MTs as observed via fluorescence microscopy. Through a combination of digital fluorescence imaging with MT modeling, modelconvolution, and automated image analysis of live and fixed MTs, we developed a method for MT tip tracking that includes estimation of the measurement error. We found that the typical single-frame tip tracking accuracy of GFP-tubulin labeled MTs in living LLC-PK1α cells imaged with a standard widefield epifluorescence digital microscope system is ∼36 nm, the equivalent of ∼4.5 tubulin dimer layers. However, if the MT tips are blunt, the tip tracking accuracy can be as accurate as ∼15 nm (∼2 dimer layers). By fitting a Gaussian survival function to the MT tip intensity profiles, we also established that MTs within living cells are not all blunt, but instead exhibit highly variable tapered tip structures with a protofilament length standard deviation of ∼180 nm. More generally, the tip tracking method can be extended to track the tips of any individual fluorescently labeled filament, and can estimate filament tip structures both in vivo and in vitro with single-frame accuracy on the nanoscale.

Original languageEnglish (US)
Pages (from-to)192-204
Number of pages13
JournalCellular and Molecular Bioengineering
Volume4
Issue number2
DOIs
StatePublished - Jun 2011

Bibliographical note

Funding Information:
We thank Dominique Seetapun for technical assistance. The research was conducted with support from NIH (GM071522 and GM076177), and NSF (MCB-0615568).

Keywords

  • Algorithm
  • Automation
  • LLC-PK1
  • MATLAB
  • Microtubules
  • Tips
  • Tracking

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