A spatiotemporal characterization method for the dynamic cytoskeleton

Ghada Alhussein, Aya Shanti, Ilyas A.H. Farhat, Sara B.H. Timraz, Noaf S.A. Alwahab, Yanthe E. Pearson, Matthew N. Martin, Nicolas Christoforou, Jeremy C.M. Teo

Research output: Contribution to journalArticlepeer-review


The significant gap between quantitative and qualitative understanding of cytoskeletal function is a pressing problem; microscopy and labeling techniques have improved qualitative investigations of localized cytoskeleton behavior, whereas quantitative analyses of whole cell cytoskeleton networks remain challenging. Here we present a method that accurately quantifies cytoskeleton dynamics. Our approach digitally subdivides cytoskeleton images using interrogation windows, within which box-counting is used to infer a fractal dimension (Df) to characterize spatial arrangement, and gray value intensity (GVI) to determine actin density. A partitioning algorithm further obtains cytoskeleton characteristics from the perinuclear, cytosolic, and periphery cellular regions. We validated our measurement approach on Cytochalasin-treated cells using transgenically modified dermal fibroblast cells expressing fluorescent actin cytoskeletons. This method differentiates between normal and chemically disrupted actin networks, and quantifies rates of cytoskeletal degradation. Furthermore, GVI distributions were found to be inversely proportional to Df, having several biophysical implications for cytoskeleton formation/degradation. We additionally demonstrated detection sensitivity of differences in Df and GVI for cells seeded on substrates with varying degrees of stiffness, and coated with different attachment proteins. This general approach can be further implemented to gain insights on dynamic growth, disruption, and structure of the cytoskeleton (and other complex biological morphology) due to biological, chemical, or physical stimuli.

Original languageEnglish (US)
Pages (from-to)221-232
Number of pages12
Issue number5
StatePublished - May 1 2016


  • Cytoskeleton rearrangement
  • High-throughput analysis
  • Live-imaging
  • Mechanobiology
  • Temporal analysis

ASJC Scopus subject areas

  • Structural Biology
  • Cell Biology


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