Constraint-based modeling of metabolism - interpreting predictions of growth and ATP synthesis in human and yeast

Doctoral thesis, 2019

Every human develops from a single cell. The cell grows and divides billions of times. An imbalance in this process may affect health. One example is stunting. Children that are malnourished grow slower than healthy children. Another example is cancer. Cancer cells grow much faster than healthy cells. Cell growth depends on chemical processes known as metabolism. Metabolism transforms nutrients into the building blocks of the cell. The blocks are joined using energy delivered by the molecule ATP. ATP is charged with energy by metabolism.  The energy originates from the breakdown of nutrients. Metabolism is made up of many different enzymes. These are small proteins that catalyze chemical reactions in the cell. The metabolism of a diseased cell is often different from a healthy. Cancer cells consume nutrients faster than healthy cells, as a result they also release more byproducts. Lactate is one of the byproducts, which is also produced in muscles when they are working hard. Cancer cells also release the byproduct glutamate, but it is unknown why. By studying metabolism we can learn more about growth and disease. But human cells are challenging to study. One approach is to study simpler organisms. Baker’s yeast, Saccharomyces cerevisiae, is the source of much of our knowledge about how growing cells divide. Another approach is to model the cells in a computer. An example is constraint based models of metabolism. They are used to simulate how cells are affected by physical constraints, both internal and external. An internal constraint may be that that different types of enzymes work with different speed. An external constraint may be if a nutrient is available or not.

I used constraint based models of metabolism to study growth and production of ATP. Several findings came out of the simulations. 1) Breastfed infant’s growth is constrained by the rate of ATP production. 2) Cells can switch enzymes to increase the rate of ATP production. But this comes at the cost of a more wasteful extraction of nutrients. The behavior of both yeast cells, cancer cells and human muscles can be explained by this. 3) The rate of growth can be predicted for cells that are fed different nutrients. 4) Cancer cells excrete glutamate because it is a byproduct of growth. The rate of growth in cancer cells can be decreased by blocking glutamate excretion.

Computer models are powerful tools. They allow knowledge to be integrated from different scientific studies and experiments. The models make predictions about reality. By interpreting the predictions it is possible to extract knowledge that may have been overlooked. Computer models highlight gaps in human knowledge. They advance our understanding of cells towards future improvements of human health.