The synergy of damage repair and retention promotes rejuvenation and prolongs healthy lifespans in cell lineages
Artikel i vetenskaplig tidskrift, 2020

Damaged proteins are inherited asymmetrically during cell division in the yeast Saccharomyces cerevisiae, such that most damage is retained within the mother cell. The consequence is an ageing mother and a rejuvenated daughter cell with full replicative potential. Daughters of old and damaged mothers are however born with increasing levels of damage resulting in lowered replicative lifespans. Remarkably, these prematurely old daughters can give rise to rejuvenated cells with low damage levels and recovered lifespans, called second-degree rejuvenation. We aimed to investigate how damage repair and retention together can promote rejuvenation and at the same time ensure low damage levels in mother cells, reflected in longer health spans. We developed a dynamic model for damage accumulation over successive divisions in individual cells as part of a dynamically growing cell lineage. With detailed knowledge about single-cell dynamics and relationships between all cells in the lineage, we can infer how individual damage repair and retention strategies affect the propagation of damage in the population. We show that damage retention lowers damage levels in the population by reducing the variability across the lineage, and results in larger population sizes. Repairing damage efficiently in early life, as opposed to investing in repair when damage has already accumulated, counteracts accelerated ageing caused by damage retention. It prolongs the health span of individual cells which are moreover less prone to stress. In combination, damage retention and early investment in repair are beneficial for healthy ageing in yeast cell populations.


Barbara Maria Schnitzer

Chalmers, Matematiska vetenskaper, Tillämpad matematik och statistik

Johannes Borgqvist

Chalmers, Matematiska vetenskaper, Tillämpad matematik och statistik

Marija Cvijovic

Chalmers, Matematiska vetenskaper, Tillämpad matematik och statistik

PLoS Computational Biology

1553-734X (ISSN) 1553-7358 (eISSN)

Vol. 16 10 e1008314


Annan biologi

Biomedicinsk laboratorievetenskap/teknologi

Klinisk vetenskap





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