Quantification of cell shape, intracellular flows and transport based on DIC object detection and tracking.

Computational image analysis combined with label-free imaging has helped maintain its relevance for cell biology, despite the rapid technical improvements in fluorescence microscopy with the molecular specificity of tags. Here, we discuss some computational tools developed in our lab and their application to quantify cell shape, intracellular organelle movement and bead transport in vitro, using differential interference contrast (DIC) microscopy data as inputs. The focus of these methods is image filtering to enhance image gradients, and combining them with segmentation and single particle tracking (SPT). We demonstrate the application of these methods to Escherichia coli cell length estimation and tracking of densely packed lipid granules in Caenorhabditis elegans one-celled embryos, diffusing beads in solutions of different viscosities and kinesin-driven transport on microtubules. These approaches demonstrate how improvements to low-level image analysis methods can help obtain insights through quantitative cellular and subcellular microscopy.

Polymerization kinetics of tubulin from mung seedlings modeled as a competition between nucleation and GTP-hydrolysis rates.

Microtubules (MTs) form physiologically important cytoskeletal structures that are assembled by tubulin polymerization in nucleation- and guanosine triphosphate (GTP)-dependent manner. GTP hydrolysis competes with the addition of monomers, to determine the GTP-cap size, and the onset of shrinkage, which alternates with growth. Multiple theoretical models of MT polymerization dynamics have been reconciled to the kinetics of animal brain tubulins, but more recently, rapid kinetics seen in Arabidopsis tubulin polymerization suggest the need to sample a wider diversity in tubulin polymerization kinetics and reconcile it to theory. Here, we isolated tubulin from seedlings of Vigna sp. (mung bean), compared polymerization kinetics to animal brain tubulin, and used a computational model to understand the differences. We find that activity-isolated mung tubulin polymerizes in a nucleation-dependent manner, based on turbidimetry, qualitatively similar to brain tubulin, but with a 10-fold smaller critical concentration. GTP-dependent polymerization kinetics also appear to be transient, indicative of high rates of GTP hydrolysis. Computational modeling of tubulin nucleation and vectorial GTP hydrolysis to examine the effects of high nucleation and GTP-hydrolysis rates predicts a dominance of the latter in determining MT lengths and numbers. Microscopy of mung tubulin filaments stabilized by GMPCPP or taxol results in few and short MTs, compared to the many long MTs arising from goat tubulin, qualitatively matching the model predictions. We find GTP-hydrolysis outcompetes nucleation rates in determining MT lengths and numbers.