ERC Grants

Jakob Ruess, inventor of new models for cell biology

Changed on 29/11/2022
Jakob Ruess, a researcher in Mathematics Applied to Biology and member of the InBio project team, has recently been awarded a European ERC Starting Grant. Over the next five years, through his BridgingScales project, he will be able to explore a new approach to the mathematical modelling of cellular processes.

Mathematical methods for biology

Jakob Ruess, a researcher in the InBio project team, jointly run by Inria and the Institut Pasteur, has some good news with which to end 2022: he has been awarded a prestigious ERC Starting Grant. This grant is awarded annually by the European Research Council (ERC) and recognises scientists with innovative ideas as they embark on their own independent research programs. It provides them with the means to build a research team around an original theme.

Jakob Ruess received the award for BridgingScales, a project focused on the mathematical modelling of cellular processes, a subject that has interested him since his PhD. “I began my research career studying mathematics, a field that has always fascinated me,” he says. “At first, I was fascinated by the theoretical questions of this discipline, particularly those related to stochastic processes, but during my PhD research, my focus changed to how mathematics can be applied to biology.”

Stochastic processes at the heart of living organisms

His PhD was on stochastic modelling of cellular processes, a field that he is now exploring in all its complexity. In living organisms, right at the heart of cells, everything is a chemical reaction, from activating a gene to producing a protein.

Randomness plays a key role in single cells, because two completely identical cells can behave very differently,” says Jakob Ruess. “This behavioural heterogeneity may explain, for example, some forms of bacterial resistance to antibiotics and why cancer cells sometimes respond differently to treatment.

Understanding the behaviour of an individual cell and the dynamics of a population of cells is therefore crucial for many applications in medicine and in synthetic biology, an emerging field of science and biotechnology that combines biology and engineering to build and produce new biological systems and functions. Scientists are, for example, working towards designing “biological oscillators” that work in a similar way to their mechanical and electrical counterparts, such as springs and transistors that are commonly found in engines, computers and telephones.

Systems that are difficult to control

Biological systems such as these could produce, regularly at a predefined interval, a chemical compound needed to treat a disease. However, although researchers know how to design systems to control the behaviour of a single cell, controlling and synchronising the behaviour of a population of cells is a real challenge. This is due to the heterogeneity and interdependence of the individual behaviours of these cells.

“There is intrinsically a strong coupling between single-cell processes and the dynamics of cell populations. Research tends to focus on one or the other of these aspects; it rarely looks at how they interact,” explains Jakob Ruess. “The BridgingScales project aims to understand these interactions, drawing on the coupling of mathematical models adapted to the stochastic modelling of single-cell processes on the one hand, and to the description of the dynamics of cell populations on the other.”

Biotechnology applications

The ERC Starting Grant recognises the scientific innovation and ambition of this project. The €1.5 million awarded over the next five years will give Jakob Ruess ample opportunity to explore this new avenue of research. At the theoretical level, he will be able to develop new mathematical methods for simulating biological systems and identifying the parameters that control how they evolve. The goal is also to find applications in biotechnology research, especially using “optogenetic” systems, which react to light, for example inducing the producing of a protein.

As he prepares to embark on this project, Jakob Ruess can barely contain his pride in having been awarded the grant after an extremely demanding selection process. “I worked on writing this project for weeks on end at the end of last year. I was even working on it on New Year’s Eve!”, he recalls. Throughout the application process, the constant guidance and crucial support that Inria afforded him was invaluable, especially when it came to proofreading the project document and preparing for interviews with the selection panel.

Team-based research

The grant not only recognises his bold scientific endeavours, but also provides an incentive to build a research team: This is a unique opportunity in my career: having the means to both define a project and choose whom to work with to contribute to it, he concludes.

The challenges ahead for Jakob Ruess and his future team are considerable, as tackling the modelling of living organisms is no small challenge! But this complexity is exactly what has motivated the researcher for many years. He now holds all the cards to meet these challenges head on and to embark on a new stage in his career!

Jakob Ruess: a few key dates

  • 2010: Master’s degree in mathematics at the University of Heidelberg (Germany).

  • 2012: Best Graduate Student Paper Award, awarded by the Swiss Institute of Bioinformatics.

  • 2014: PhD at ETH Zurich, in the Automatic Control Laboratory.

  • 2015: ETH Zurich PhD Medal winner.

  • 2014-2016: Postdoctoral fellow at the Institute of Science and Technology Austria.

  • 2016: Jakob Ruess joins Inria, working firstly in the Lifeware team, then in the InBio team. In 2018, he received a four-year “PEDR”-award from Inria.

InBio, a multidisciplinary team in biology and mathematics

Jakob Ruess is, alongside Grégory Batt, one of the pillars of InBio, a joint Inria/Institut Pasteur project team whose interdisciplinary research is internationally recognised. The researchers combine experimental approaches in biology and mathematical methods, based on control theory, the modelling of stochastic processes or statistical approaches and active learning techniques, and apply them to synthetic biology, for example, for use in fields such as agro-pharmaceuticals, chemistry, health and medicine.

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