Back

Non-epigenetic mechanisms enable short memories of the environment for cell cycle commitment

Qu, Y.; Jiang, J.; Liu, X.; Yang, X.; Tang, C.

2020-08-14 molecular biology
10.1101/2020.08.14.250704 bioRxiv
Show abstract

Cells continuously survey their environment in order to make fundamental decisions, including whether to divide, migrate, or differentiate. However, a fascinating phenomenon in biology is that cells often possess memory--they temporally integrate both past and present signals to make a reliable decision. Cellular memory manifests across different biological systems over different timescales, and a variety of underlying molecular mechanisms have been proposed. Here we investigate a non-epigenetic molecular mechanism underpinning how a single yeast cell can remember its recent environmental history to decide whether to enter the cell cycle. This "memories" is encoded by the phosphorylation level of the cell cycle inhibitor Whi5. G1 cyclin Cln3 senses environmental nutrient levels and promotes cell-cycle entry by phosphorylating and thus inactivating Whi5. We developed an optogenetic system whereby the nuclear localization of Cln3 can be rapidly and reversibly controlled by light. By monitoring cellular response to different temporal profiles of Cln3, we found that cell cycle entry requires the time duration of nuclear Cln3, supporting the model of "cellular memories". Moreover, instead of the memory could last for the entire G1 phase as previously observed in glucose, we found Whi5 re-activates rapidly, with a similar half-time [~] 12 min, in a variety of nutrient and stress conditions. Our results suggest yeast cell can shortly remember its recent environmental cues to decide whether to enter the cell cycle.

Matching journals

The top 2 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.