Publications

Nuclear positioning is a crucial cell function, but how a migrating cell positions its nucleus is not understood. Using traction-force microscopy, we found that the position of the nucleus in migrating fibroblasts closely coincided with the center point of the traction-force balance, called the point of maximum tension (PMT). Positioning of the nucleus close to the PMT required nucleus-cytoskeleton connections through linker of nucleoskeleton-to-cytoskeleton (LINC) complexes. Although the nucleus briefly lagged behind the PMT following spontaneous detachment of the uropod during migration, the nucleus quickly repositioned to the PMT within a few minutes. Moreover, traction-generating spontaneous protrusions deformed the nearby nucleus surface to pull the nuclear centroid toward the new PMT, and subsequent retraction of these protrusions relaxed the nuclear deformation and restored the nucleus to its original position. We propose that the protruding or retracting cell boundary transmits a force to the surface of the nucleus through the intervening cytoskeletal network connected by the LINC complexes, and that these forces help to position the nucleus centrally and allow the nucleus to efficiently propagate traction forces across the length of the cell during migration.

The Biopharmaceutics Drug Disposition Classification System (BDDCS) can be utilized to predict drug disposition, including interactions with other drugs and transporter or metabolizing enzyme effects based on the extent of metabolism and solubility of a drug. However, defining the extent of metabolism relies upon clinical data. Drugs exhibiting high passive intestinal permeability rates are extensively metabolized. Therefore, we aimed to determine if in vitro measures of permeability rate or in silico permeability rate predictions could predict the extent of metabolism, to determine a reference compound representing the permeability rate above which compounds would be expected to be extensively metabolized, and to predict the major route of elimination of compounds in a two-tier approach utilizing permeability rate and a previously published model predicting the major route of elimination of parent drug. Twenty-two in vitro permeability rate measurement data sets in Caco-2 and MDCK cell lines and PAMPA were collected from the literature, while in silico permeability rate predictions were calculated using ADMET Predictor or VolSurf+. The potential for permeability rate to differentiate between extensively and poorly metabolized compounds was analyzed with receiver operating characteristic curves. Compounds that yielded the highest sensitivity-specificity average were selected as permeability rate reference standards. The major route of elimination of poorly permeable drugs was predicted by our previously published model, and the accuracies and predictive values were calculated. The areas under the receiver operating curves were >0.90 for in vitro measures of permeability rate and >0.80 for the VolSurf+ model of permeability rate, indicating they were able to predict the extent of metabolism of compounds. Labetalol and zidovudine predicted greater than 80% of extensively metabolized drugs correctly and greater than 80% of poorly metabolized drugs correctly in Caco-2 and MDCK, respectively, while theophylline predicted greater than 80% of extensively and poorly metabolized drugs correctly in PAMPA. A two-tier approach predicting elimination route predicts 72 ± 9%, 49 ± 10%, and 66 ± 7% of extensively metabolized, biliarily eliminated, and renally eliminated parent drugs correctly when the permeability rate is predicted in silico and 74 ± 7%, 85 ± 2%, and 73 ± 8% of extensively metabolized, biliarily eliminated, and renally eliminated parent drugs correctly when the permeability rate is determined in vitro.