Mathematical modelling of ribosome evolution

Ribosomes are tiny machines inside cells that play a key role in cell growth. Before cells divide, they need to duplicate all their components. Ribosomes are needed for this process because they produce proteins, the main building blocks of cells. The more efficient ribosomes are, the faster cells can grow, making them more successful than their competitors. In this project, we will investigate whether the ribosomes of microorganisms have evolved to be as efficient as possible. We will build a simple computer model of a microbial cell and simulate its growth in various environments. By creating several versions of this cell with different ribosome compositions, we will determine which cells grow the fastest. This can indicate which ribosome version would be most successful in evolution. We will then compare the results with the real-life ribosome compositions of different microbes. Initially, our results might not match real data, but this can still provide valuable insights. It may suggest that our virtual cell is too simple or that some processes are not accurately represented. We will then refine the model by adding more details or adjusting the parameters. This repeated process will help identify the most important factors and processes that shaped ribosome composition through evolution. Finally, we will test the refined model with other types of microorganisms and environmental conditions to see if our conclusions hold. Ultimately, this model will improve our understanding of cell growth and provide insights into cell evolution.

How do cells grow - and why does it matter? In this project, we aimed to better understand how cells grow. To do this, we adapted and applied the relatively new computational method called Growth Balance Analysis (GBA). This allows us to build a simplified computer model of a cell and check whether our understanding of cell growth matches the behavior of real cells. A key focus was on the ribosome, the cell's "protein factory." Ribosomes produce all the proteins a cell needs to live and grow. The question for the cell is: What should my protein factory look like? Should it consist of long-lived proteins, short-lived RNA, or a mixture of both? Our model shows that a compromise works best. Cells use their resources very efficiently, adjusting their composition to grow as quickly as possible under different conditions. The design of ribosomes also follows this principle: a mixture of about one-third protein and two-thirds RNA turns out to be optimal. GBA helps reveal the "costs" of cellular decisions. You can think of it like running a company: every investment, such as producing a particular protein, has a price and brings a certain benefit to growth. This way, GBA helps us understand how the cell operates as economically as possible. These insights are not only exciting for basic research. In biotechnology, microbes are used to produce medicines, fuels, or other products. This process places considerable stress on the cells. Methods like GBA allow us to predict how these stresses can be reduced, enabling microbes to work more efficiently - and making the production of valuable products more sustainable and productive.