Ranking data to understand plant processes

Modern techniques enable scientists to precisely establish which substances are occurring where in the plant and which are coming to expression at a certain moment. But how can all these data be correlated? This is work for the bioinformaticians of Plant Research International.

The plant is putting into action many simultaneous and consecutive processes to grow, flower and produce fruits. The timing of what happens depends on the genes that are initiating or – conversely – halting the processes. Several (intermediate) products are formed which are sometimes again leading to subsequent reactions and which can all be measured separately.

Anyone who wishes to control such a process in the plant, e.g., to achieve a higher yield, should precisely know which gene is playing a role in a certain process and which substances are causing what. Modern measuring techniques enable precise establishment from each plant extract which genes are active and which metabolites and proteins these contain. All these measuring techniques yield enormous amounts of data of which a correlation can not immediately be found.

This is why our scientists are developing programmes to show those correlations. First, they develop software for automatically selecting faulty measuring data; measuring equipment can indeed make errors. And they set up databanks for ranking the data and are making the data easily accessible for subsequent research.

Mathematical models

They then draw up mathematical models to show the correlations between components. Such a model correlation is subsequently checked in laboratory experiments. Sometimes, the model is found to be wrong. Too few elements may have been included or the description of the correlation between the elements has not been described properly. The final objective is to make a model that is simulating the complex reality in the best possible way.

Such a model allows prediction of, e.g., the amount of substances an enzyme is producing in the presence of a certain amount of a different substance. This opens the road to the next step: affecting the process described by the model. If you would add or remove a certain substance, would the plant start flowering earlier or – conversely – later? This is how detailed understanding of a process will ultimately lead to possibilities to alter (processes in) plants.

Once the process is known at micro level, the scientists are moving one level upward. Until they finally understand how a plant is functioning in its ecosystem. This method is often referred to as systems biology.