Predicting evolution of life

Thanks to evolution, the great diversity of life came into being. If we could predict or control the course of evolution, we would be able to solve major social problems. Preventing bee extinction, for example; or tackling resistant bacteria; and we may even reverse environmental pollution.

Join this network | Meeting calendar

Predicting evolution of life

Insight into the origins of life, in interaction with the environment, is one of the most important scientific developments of the last 200 years. Next step is the prediction of evolutionary processes. Evolutionary biology will play an important role in solving some of the major challenges we face today. The development of bacterial resistance, resistance to pesticides, outbreaks of new diseases, and the adaptation of species to urbanisation and climate change. It will also become easier to promote biodiversity.

Researchers are working on two conditions to predict evolution. 

1. Researchers need to understand exactly which processes take place during evolution, at different levels of hierarchy and scale. This means that evolution of a species depends on other species in the same food chain and the same ecosystem. But also from (bio)molecules to cells, from organisms to ecosystems to the entire biosphere of our planet. The real breakthrough will be predicting the evolution of current species that will adapt to their changing environment in the coming years. Do you want to join us?

2. Researchers are also mapping out the changes we expect to see on our planet. If we have a good understanding of changes in climate, landscape and oceans, it is possible to predict what effects this will have on the evolution of animals and plants on Earth.

Join this network group

As a subgroup we are organizing a series of workshops for the Dutch evolution community. The goal of this workshop series is to teach each other techniques and “languages” used in different subfields of evolution, to, for example, facilitate future collaborations.

The format is as follows: two speakers will give a 15-20 minutes (online) lecture about a specific topic. After the lectures there will be 45 minutes for questions/discussions or for example to work on a small assignment.

It’s good to know that these are educational talks rather than seminars showing newest and coolest results.
PS: We very much appreciate suggestions for topics/speakers

When: Third Tuesday of the Month at 16:00 CET.

Where: on Zoom

Who: For everyone who feels part of the Dutch Evolution community and who wants to learn! (PhDs / Post-Docs / Staff) 

How: please register here for the sessions or if you would like to be added to the mailing list*. One day before the workshop, you will receive an email with a Zoom link and password.

Contact: Bregje Wertheim or Liedewij Laan.

* If you register for the free membership of the Origins Center scientific community, you automatically receive mails from the knowledge networks you have selected in the registration form.


Tuesday February 16th
What do we talk about when we talk about protein networks?
Werner Daalman and Bas Teusink

Abstract Werner Karl-Gustav Daalman, post-doc Laan Lab, Dept. Bionanoscience, TU Delft, the Netherlands
Functions inside cells are performed by networks of interacting proteins. The networks can be very complex, but a good description of these is nevertheless required for understanding emergence of function and the potential to evolve. Talking about network often involves terms as modularity, redundancy and hierarchy, which can be defined in various manners. I present definitions that are both intuitive and practically useful, as continuously illustrated by applications to a model network, budding yeast polarity. Finally, I will show how terms concerning network architecture are a matter of perspective, and that choosing the right perspective may bring quantitative predictions on phenotypes and evolution within reach for the network of your interest.

Abstract Bas Teusink, professor Systems Bioinformatics, TU Delft, the Netherlands
Metabolism is the basis of life: its enzymes create networks through which chemical flows provide the energy, chemicals and building blocks that make cells and organisms grow and divide, do work, or communicate with each other. For long metabolism was seen as the boring enabler of the more interesting biology, such as signaling, gene regulation or cell differentiation, but in fact -especially for unicellular organisms- it is quite the opposite. Regulatory mechanisms are there to orchestrate and serve processes with a purpose, and that purpose, of course, is fitness; For unicellular organisms, a large determinant of fitness is specific growth rate. And for growth, metabolism is what you need. A corollary of this is that the outcome of all the regulation has a purpose, to tune metabolic processes for optimal growth. Hence, the outcome of regulation, the metabolic network fluxes, may be predicted through growth rate optimization. This is the basis for constrained-based metabolic models and Flux Balance Analysis, a technique that allows accurate genotype-to-phenotype maps for microbes.
In my tutorial talk I will give examples of the power of the approach. In the workshop, we will together analyze a toy model with Flux Balance Analysis, the techniques that we also use for genome-scale metabolic models, to illustrate how it works, and what its limitations are.

Tuesday March 16th
Cell-based models: ecology, evolution and development
Enrico Sandro Colizzi (LU) and Renske Vroomans (UvA)

Abstract Sandro Colizzi (LU)
The cell is the unit of biology — a little machine capable of self-replication. Much of the complexity of biology plays out in the interactions between multiple cells. For instance, the interactions between microbes determine their ecology. During embryonic development, thousands of cells interact to generate multicellular organisms. These interactions produce emergent behaviour, where collectives of cells can perform functions that single cells cannot. These emergent functions can be selected by evolution. Therefore, we need good and flexible models of cells to understand this complexity. We will present recent and “classical” results in cell-based modelling in ecology, evolution and development.

Abstract Renske Vroomans (UvA)
A widespread and flexible cell model is the Cellular Potts Model – which has been used for almost 30 years. It is particularly suitable for studying emergent behaviours in cell populations, because it allows for an intuitive implementation of cell-level behaviour, such as cell migration, division and adhesion. Moreover, it is straightforward to add intracellular processes such as cytoskeletal dynamics, gene expression, etc. and for integration into an evolutionary framework. In the workshop, we will give an overview of the model, with emphasis on adapting the formalism to different uses.

Origins Center Networks


Liedewij Laan

Member Steering Committee

TU Delft

Liedewij Laan

Member Steering Committee

TU Delft



Fields of interest:

As pioneers of the emerging field of evolutionary cell biophysics, we aim to understand how the building blocks of a cell constrain and facilitate evolution of cellular functions. The function we focus on is symmetry breaking in budding yeast. We do experimental evolution, quantitative cell biology and modeling in live cells in combination with minimal in vitro systems to understand the molecular mechanisms of adaptive mutations and to predict fitness, both with bottom-up (biophysics) and top-down (statistical) approaches.

cell biophysics, predicting evolution, minimal synthetic systems


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