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Experimental and Mathematical-Modeling Characterization of Trypanosoma cruzi Epimastigote Motility.

Sosa-Hernández E, Ballesteros-Rodea G, Arias-Del-Angel JA, Dévora-Canales D, Manning-Cela RG, Santana-Solano J, Santillán M - PLoS ONE (2015)

Bottom Line: The present work is aimed at characterizing the motility of parasite T. cruzi in its epimastigote form.We further extracted parasite trajectories from the recorded videos, and statistically analysed the following trajectory-step features: step length, angular change of direction, longitudinal and transverse displacements with respect to the previous step, and mean square displacement.The fact that the model predictions closely match most of the experimentally observed parasite-trajectory characteristics, allows us to conclude that the model is an accurate description of T. cruzi motility.

View Article: PubMed Central - PubMed

Affiliation: Unidad Monterrey, Centro de Investigación y de Estudios Avanzados del IPN, Apodaca NL, México.

ABSTRACT
The present work is aimed at characterizing the motility of parasite T. cruzi in its epimastigote form. To that end, we recorded the trajectories of two strains of this parasite (a wild-type strain and a stable transfected strain, which contains an ectopic copy of LYT1 gene and whose motility is known to be affected). We further extracted parasite trajectories from the recorded videos, and statistically analysed the following trajectory-step features: step length, angular change of direction, longitudinal and transverse displacements with respect to the previous step, and mean square displacement. Based on the resulting observations, we developed a mathematical model to simulate parasite trajectories. The fact that the model predictions closely match most of the experimentally observed parasite-trajectory characteristics, allows us to conclude that the model is an accurate description of T. cruzi motility.

No MeSH data available.


Related in: MedlinePlus

Comparison between model predictions (solid lines) and experimentally determined trajectory characteristics (bars or dots) for the genetically-modified strain.a) Probability density function for the angular change of direction between consecutive steps. b) Probability density function for the instantaneous speed. c) Mean squared displacement.
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pone.0142478.g009: Comparison between model predictions (solid lines) and experimentally determined trajectory characteristics (bars or dots) for the genetically-modified strain.a) Probability density function for the angular change of direction between consecutive steps. b) Probability density function for the instantaneous speed. c) Mean squared displacement.

Mentions: By using the previously described algorithm we simulated several long parasite trajectories for each parasite strain. Then, we computed the parasite speed in each step, as well as the angular change of direction between consecutive steps—by means of Eq (3). Finally, we estimated the probability density function for each variable. We repeated the whole procedure for the recorded trajectories, and plotted the results in Figs 8 and 9. Note that there is a very good agreement between the experimental and the simulated results. To our consideration, all this validates the assumptions previously introduced model is based on. To further validate the model we calculated the mean squared displacement—see Eq (6)—for both the recorded and the simulated trajectories and plotted the results in Figs 8 and 9. The agreement between the simulated and the experimental curve is also very good in this case. From the above results, we are confident that our model provides a fair description of the way both parasite strains move.


Experimental and Mathematical-Modeling Characterization of Trypanosoma cruzi Epimastigote Motility.

Sosa-Hernández E, Ballesteros-Rodea G, Arias-Del-Angel JA, Dévora-Canales D, Manning-Cela RG, Santana-Solano J, Santillán M - PLoS ONE (2015)

Comparison between model predictions (solid lines) and experimentally determined trajectory characteristics (bars or dots) for the genetically-modified strain.a) Probability density function for the angular change of direction between consecutive steps. b) Probability density function for the instantaneous speed. c) Mean squared displacement.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4636178&req=5

pone.0142478.g009: Comparison between model predictions (solid lines) and experimentally determined trajectory characteristics (bars or dots) for the genetically-modified strain.a) Probability density function for the angular change of direction between consecutive steps. b) Probability density function for the instantaneous speed. c) Mean squared displacement.
Mentions: By using the previously described algorithm we simulated several long parasite trajectories for each parasite strain. Then, we computed the parasite speed in each step, as well as the angular change of direction between consecutive steps—by means of Eq (3). Finally, we estimated the probability density function for each variable. We repeated the whole procedure for the recorded trajectories, and plotted the results in Figs 8 and 9. Note that there is a very good agreement between the experimental and the simulated results. To our consideration, all this validates the assumptions previously introduced model is based on. To further validate the model we calculated the mean squared displacement—see Eq (6)—for both the recorded and the simulated trajectories and plotted the results in Figs 8 and 9. The agreement between the simulated and the experimental curve is also very good in this case. From the above results, we are confident that our model provides a fair description of the way both parasite strains move.

Bottom Line: The present work is aimed at characterizing the motility of parasite T. cruzi in its epimastigote form.We further extracted parasite trajectories from the recorded videos, and statistically analysed the following trajectory-step features: step length, angular change of direction, longitudinal and transverse displacements with respect to the previous step, and mean square displacement.The fact that the model predictions closely match most of the experimentally observed parasite-trajectory characteristics, allows us to conclude that the model is an accurate description of T. cruzi motility.

View Article: PubMed Central - PubMed

Affiliation: Unidad Monterrey, Centro de Investigación y de Estudios Avanzados del IPN, Apodaca NL, México.

ABSTRACT
The present work is aimed at characterizing the motility of parasite T. cruzi in its epimastigote form. To that end, we recorded the trajectories of two strains of this parasite (a wild-type strain and a stable transfected strain, which contains an ectopic copy of LYT1 gene and whose motility is known to be affected). We further extracted parasite trajectories from the recorded videos, and statistically analysed the following trajectory-step features: step length, angular change of direction, longitudinal and transverse displacements with respect to the previous step, and mean square displacement. Based on the resulting observations, we developed a mathematical model to simulate parasite trajectories. The fact that the model predictions closely match most of the experimentally observed parasite-trajectory characteristics, allows us to conclude that the model is an accurate description of T. cruzi motility.

No MeSH data available.


Related in: MedlinePlus