How does a cell balance "risk" and "speed" when it divides to give birth to a new single-celled entity? Scientists from the Federal Polytechnic University of Lausanne (notably Ahmad Sadeghi, Roxane Dervey, Vojislav Gligorovski and Marco Labagnara and Sahand Jamal Rahi) have developed and experimentally tested the first mathematical theory describing the cell's best strategy for duplicating itself safely and efficiently.
Cells go through a life cycle that includes growing to the right size, developing 'equipment' to perform their functions, and finally dividing into two new cells.
The cell cycle is crucial because it ensures the perpetuation of the cell population and, by extension, the larger structure of which it is a part, such as a tissue of the body, and ultimately the survival of an entire animal (or plant) species ).

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Checkpoints prevent DNA damage or mutations

The cell cycle is tightly regulated by so-called "checkpoints", which prevent errors such as mutations or DNA damage from being passed on to the next generation of cells.
Each 'checkpoint' acts as a kind of quality control monitor (a biological 'checklist') that ensures cell cycle order, integrity and fidelity.
But the "checkpoints" themselves often fail or are "bypassed" by error after a prolonged cell cycle arrest.
If this happens in the human body, the result could be unregulated cell growth and division, as occurs in cancer.
“Checkpoints monitor cells or whole organisms and can stop the cell cycle or the development of the organism when they detect problems”, explains Sahand Jamal Rahi from EPFL's School of Basic Sciences.
“But if cells or organisms get stuck in one mistake for a long time, in many cases they end up dividing or growing anyway, because the process can't stop forever. There is a real risk of dying if the 'checkpoints' do not stop at all, but even waiting forever is in fact death”.

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A new arithmetic of passing “checks”

The fundamental question is therefore the following: how does the cell balance risk and speed when dividing? Although it is a fundamental and life-deciding procedure, passing checkpoints has not yet been well understood, either theoretically or experimentally.
In new scientific work, Rahi and his Lausanne colleagues have presented the first mathematical theory to describe the process of passing checkpoints.
“Many organisms have to predict what will happen”Rahi explains.
“You have a problem and you need to evaluate how serious this problem could be, because the consequences are never certain. One could survive this or not survive that. Thus, the cell makes 'a bet' in any case. In our study, we analyze the probabilities of this bet.

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Brewer's yeast to investigate a fatal… bet

As an example of a real organism, the researchers looked at the budding yeast Saccharomyces cerevisiae, which has been used in winemaking, baking, and brewing for centuries.
"There are systems that monitor organisms and, among these, perhaps the most studied is the 'checkpoint' of DNA damage in yeast"Rahi explains.
“We therefore thought of analyzing this 'system' and verifying whether it was possible to make sense of the 'checkpoint' bypass model. We started with a mathematical analysis based on a very simple question: if these organisms are balancing risk and speed, why do they have to predict the future?”.

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The risk-speed trade-off remains the real issue

This trade-off between risk and speed is similar to the quality control system of an industrial assembly line: how fast can you produce before quality suffers? How do you balance quality and efficiency?
"Other scholars have already reasoned on this risk-speed trade-off for control points, but focusing only on the qualitative aspect"Rahi says.
“The 'gamble' is not something that has been analyzed or taken seriously before. So, I think we can claim ownership of the research idea!”.

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There is always a balance between different probabilities

Scientists have analyzed the relationship between risk and speed.
"The theory basically consists in balancing different probabilities: in summary, we calculate the variation of fitness, of 'physical form' of the cell depending on whether the mechanism determines a stop in the process or whether it proceeds for self-replication"Rahi says.
“The body has to work out a strategy that involves continuously deciding whether to wait or go ahead, depending on the seriousness of the body's situation at that moment. Of course, waiting means having fewer and fewer progeny. The alternative is to take a risk: then the cell divides and there is a probability that it will survive and one that will die".
The theory calculates when risk and speed balance each other, resulting in the optimal 'moment'.
“The result is a very simple equation”Rahi adds.
Although developed for yeast, the theory applies broadly to any cell type because it only takes into account risk and rate, factors that affect all living organisms.
"There is no unique correspondence between what happens in yeast and mammalian cells, because the latter have other constraints than maximizing their growth", says the EPFL researcher.

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Does cancer proliferation have its own “tests”?

“But when cells become cancerous, they decouple their 'physical fitness' from that of the host. And then Darwinian evolution suggests that they should reshape their checkpoints to maximize growth. It is an aspect that interests us; one of our next steps will be to see if cells remodel their checkpoints optimally once they become cancerous”.
Dr. Sahand Jamal Rahi does not expect cancer cells to completely abolish their "checkpoint" systems.

“They don't get rid of their control points because by doing so, they too would be taking too much risk in each division”He says.
“Even the absence of any 'checkpoints' compared to when they were precancerous is not an optimal condition, because as soon as there is a problem they die. Consequently, we are interested to see if they too aim for this optimal equilibrium state that our theory describes..

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