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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.


CMPI estimates are independent of positioning errors.(a)CCD and coupled NCD// of 50 single live NIH cells (red dot) and fixed NIH cells (blue dots) in the CCD vs. NCD// plot. (b)Left: Original barcode of an individual NIH cell tracked at 1-min lag time for 60 min. Right: Error-filtered barcode of the same tracking data. (c) Linear relationship of diffusion coefficient and error-filtered CMPI.
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f5: CMPI estimates are independent of positioning errors.(a)CCD and coupled NCD// of 50 single live NIH cells (red dot) and fixed NIH cells (blue dots) in the CCD vs. NCD// plot. (b)Left: Original barcode of an individual NIH cell tracked at 1-min lag time for 60 min. Right: Error-filtered barcode of the same tracking data. (c) Linear relationship of diffusion coefficient and error-filtered CMPI.

Mentions: When acquired from shorter time intervals, the magnitudes of the CCDs and NCDs inevitably become smaller. Hence, the imaging acquisition errors will have more significant impacts to the data. To evaluate this impact, a fixed-cell was subjected to the CN correlation analysis to obtain the positioning error profile in the CCD-NCD// coordinate system. Since the probed cell was fixed, the non-zero distribution of its CN correlation data in the CCD vs. NCD// plot was merely contributed from the acquisition errors, which formed a special region in the CCD-NCD// coordinate system that could be treated as a separate distribution, called Region V: Stationary Mode. The results confirmed that the positioning error cannot be ignored (Fig. 5a). However, it cannot be an implication that every CN correlation datum located within the zone is in stationary mode since the positioning error could also make a non-zero CN correlation datum shift and look “stationary”.


Displacement correlations between a single mesenchymal-like cell and its nucleus effectively link subcellular activities and motility in cell migration analysis
CMPI estimates are independent of positioning errors.(a)CCD and coupled NCD// of 50 single live NIH cells (red dot) and fixed NIH cells (blue dots) in the CCD vs. NCD// plot. (b)Left: Original barcode of an individual NIH cell tracked at 1-min lag time for 60 min. Right: Error-filtered barcode of the same tracking data. (c) Linear relationship of diffusion coefficient and error-filtered CMPI.
© Copyright Policy - open-access
Related In: Results  -  Collection

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

f5: CMPI estimates are independent of positioning errors.(a)CCD and coupled NCD// of 50 single live NIH cells (red dot) and fixed NIH cells (blue dots) in the CCD vs. NCD// plot. (b)Left: Original barcode of an individual NIH cell tracked at 1-min lag time for 60 min. Right: Error-filtered barcode of the same tracking data. (c) Linear relationship of diffusion coefficient and error-filtered CMPI.
Mentions: When acquired from shorter time intervals, the magnitudes of the CCDs and NCDs inevitably become smaller. Hence, the imaging acquisition errors will have more significant impacts to the data. To evaluate this impact, a fixed-cell was subjected to the CN correlation analysis to obtain the positioning error profile in the CCD-NCD// coordinate system. Since the probed cell was fixed, the non-zero distribution of its CN correlation data in the CCD vs. NCD// plot was merely contributed from the acquisition errors, which formed a special region in the CCD-NCD// coordinate system that could be treated as a separate distribution, called Region V: Stationary Mode. The results confirmed that the positioning error cannot be ignored (Fig. 5a). However, it cannot be an implication that every CN correlation datum located within the zone is in stationary mode since the positioning error could also make a non-zero CN correlation datum shift and look “stationary”.

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.