Stochastic branching models for the telomeres dynamics in a model including telomerase activity

Area of Science:

• Genetics and Molecular Biology
• Computational Biology
• Biophysics

Background:

• Telomeres, protective DNA caps on chromosomes, shorten with each cell division due to the end replication problem.
• Telomere shortening is linked to cellular senescence, aging, and age-related diseases.
• Telomerase, an enzyme, can lengthen telomeres, potentially delaying aging but increasing cancer risk.

Purpose of the Study:

• To develop a stochastic mathematical model for telomere dynamics.
• To incorporate factors like multiple chromosomes, telomerase activity, and cell type variations.
• To analyze the theoretical properties and long-term behavior of the telomere length distribution.

Main Methods:

• Stochastic modeling of telomere shortening and lengthening.
• Theoretical analysis of model properties, including long-term behavior.
• Numerical simulations to assess parameter impacts on biological quantities.

Main Results:

• The model captures the dependence of telomere length distribution on dynamic processes.
• Analysis of theoretical properties provides insights into telomere maintenance mechanisms.
• Numerical investigations reveal how model parameters influence the Hayflick limit and cellular population growth.

Conclusions:

• The stochastic model offers a framework for understanding telomere dynamics and their relation to aging.
• Telomerase activity and cell type are critical factors influencing telomere length and cellular lifespan.
• The model aids in studying the trade-off between aging prevention and cancer risk associated with telomere maintenance.