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Displacement correlations between a single mesenchymal-like cell and its nucleus effectively link subcellular activities and motility in cell migration analysis

View Article: PubMed Central - PubMed

ABSTRACT

Cell migration is an essential process in organism development and physiological maintenance. Although current methods permit accurate comparisons of the effects of molecular manipulations and drug applications on cell motility, effects of alterations in subcellular activities on motility cannot be fully elucidated from those methods. Here, we develop a strategy termed cell-nuclear (CN) correlation to parameterize represented dynamic subcellular activities and to quantify their contributions in mesenchymal-like migration. Based on the biophysical meaning of the CN correlation, we propose a cell migration potential index (CMPI) to measure cell motility. When the effectiveness of CMPI was evaluated with respect to one of the most popular cell migration analysis methods, Persistent Random Walk, we found that the cell motility estimates among six cell lines used in this study were highly consistent between these two approaches. Further evaluations indicated that CMPI can be determined using a shorter time period and smaller cell sample size, and it possesses excellent reliability and applicability, even in the presence of a wide range of noise, as might be generated from individual imaging acquisition systems. The novel approach outlined here introduces a robust strategy through an analysis of subcellular locomotion activities for single cell migration assessment.

No MeSH data available.


Correlations between cell and nucleus displacements can describe subcellular activities of cell migration.(a) The CN correlation data point (red dot) locates the correlation between a CCD and a coupled NCD// (projection of nucleus centroid displacement in the CCD direction) in a CCD vs. NCD// plot. (b) Four separate regions (separated by dash lines at 45°, 75°, and 105°) in the CCD-NCD// coordinate system correspond to distinct subcellular migratory activities. A cluster of red dots shown are the CN correlation data acquired from 50 NIH 3T3 fibroblasts tracked at 1-min. time intervals for 1 hour. (c) The barcode enables visualization of the sequential occurrence of CN correlations in the four regions. Regions are distinguished by red, yellow, blue, and green, respectively. Each bar represents a CN correlation data point acquired at a 1-min time interval.
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f1: Correlations between cell and nucleus displacements can describe subcellular activities of cell migration.(a) The CN correlation data point (red dot) locates the correlation between a CCD and a coupled NCD// (projection of nucleus centroid displacement in the CCD direction) in a CCD vs. NCD// plot. (b) Four separate regions (separated by dash lines at 45°, 75°, and 105°) in the CCD-NCD// coordinate system correspond to distinct subcellular migratory activities. A cluster of red dots shown are the CN correlation data acquired from 50 NIH 3T3 fibroblasts tracked at 1-min. time intervals for 1 hour. (c) The barcode enables visualization of the sequential occurrence of CN correlations in the four regions. Regions are distinguished by red, yellow, blue, and green, respectively. Each bar represents a CN correlation data point acquired at a 1-min time interval.

Mentions: When a correlation exists between a CCD and coupled NCD, this correlation should share a common driving force. Hence, when the correlation is analyzed, the transient direction of every CCD could be set as the reference direction to correlate to the coupled NCD projected in the same direction (denoted as NCD//) (Fig. 1a). Based on the mesenchymal migratory mechanism, a trailing edge detachment event should yield a significant NCD// due to the coherent movements between the cell body and the nucleus. In contrast, in a leading edge protrusion event, the NCD// should be negligible because during the event the nucleus remains relatively stationary. We term the correlation between a CCD and the concomitant NCD// a CN correlation and describe the migration status of a cell through a collection of CN correlations.


Displacement correlations between a single mesenchymal-like cell and its nucleus effectively link subcellular activities and motility in cell migration analysis
Correlations between cell and nucleus displacements can describe subcellular activities of cell migration.(a) The CN correlation data point (red dot) locates the correlation between a CCD and a coupled NCD// (projection of nucleus centroid displacement in the CCD direction) in a CCD vs. NCD// plot. (b) Four separate regions (separated by dash lines at 45°, 75°, and 105°) in the CCD-NCD// coordinate system correspond to distinct subcellular migratory activities. A cluster of red dots shown are the CN correlation data acquired from 50 NIH 3T3 fibroblasts tracked at 1-min. time intervals for 1 hour. (c) The barcode enables visualization of the sequential occurrence of CN correlations in the four regions. Regions are distinguished by red, yellow, blue, and green, respectively. Each bar represents a CN correlation data point acquired at a 1-min time interval.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC5037420&req=5

f1: Correlations between cell and nucleus displacements can describe subcellular activities of cell migration.(a) The CN correlation data point (red dot) locates the correlation between a CCD and a coupled NCD// (projection of nucleus centroid displacement in the CCD direction) in a CCD vs. NCD// plot. (b) Four separate regions (separated by dash lines at 45°, 75°, and 105°) in the CCD-NCD// coordinate system correspond to distinct subcellular migratory activities. A cluster of red dots shown are the CN correlation data acquired from 50 NIH 3T3 fibroblasts tracked at 1-min. time intervals for 1 hour. (c) The barcode enables visualization of the sequential occurrence of CN correlations in the four regions. Regions are distinguished by red, yellow, blue, and green, respectively. Each bar represents a CN correlation data point acquired at a 1-min time interval.
Mentions: When a correlation exists between a CCD and coupled NCD, this correlation should share a common driving force. Hence, when the correlation is analyzed, the transient direction of every CCD could be set as the reference direction to correlate to the coupled NCD projected in the same direction (denoted as NCD//) (Fig. 1a). Based on the mesenchymal migratory mechanism, a trailing edge detachment event should yield a significant NCD// due to the coherent movements between the cell body and the nucleus. In contrast, in a leading edge protrusion event, the NCD// should be negligible because during the event the nucleus remains relatively stationary. We term the correlation between a CCD and the concomitant NCD// a CN correlation and describe the migration status of a cell through a collection of CN correlations.

View Article: PubMed Central - PubMed

ABSTRACT

Cell migration is an essential process in organism development and physiological maintenance. Although current methods permit accurate comparisons of the effects of molecular manipulations and drug applications on cell motility, effects of alterations in subcellular activities on motility cannot be fully elucidated from those methods. Here, we develop a strategy termed cell-nuclear (CN) correlation to parameterize represented dynamic subcellular activities and to quantify their contributions in mesenchymal-like migration. Based on the biophysical meaning of the CN correlation, we propose a cell migration potential index (CMPI) to measure cell motility. When the effectiveness of CMPI was evaluated with respect to one of the most popular cell migration analysis methods, Persistent Random Walk, we found that the cell motility estimates among six cell lines used in this study were highly consistent between these two approaches. Further evaluations indicated that CMPI can be determined using a shorter time period and smaller cell sample size, and it possesses excellent reliability and applicability, even in the presence of a wide range of noise, as might be generated from individual imaging acquisition systems. The novel approach outlined here introduces a robust strategy through an analysis of subcellular locomotion activities for single cell migration assessment.

No MeSH data available.