Individual dynamic microtubules can generate pushing or pulling forces when their growing or shrinking ends are in contact with cellular objects such as the cortex or chromosomes. These microtubules can operate in parallel bundles, for example when interacting with mitotic chromosomes. Here, we investigate the force-generating capabilities of a bundle of growing microtubules and study the effect that force has on the cooperative dynamics of such a bundle. We used an optical tweezers setup to study microtubule bundles growing against a microfabricated rigid barrier in vitro . We show that multiple microtubules can generate a pushing force that increases linearly with the number of microtubules present. In addition, the bundle can cooperatively switch to a shrinking state, due to a force-induced coupling of the dynamic instability of single microtubules. In the presence of GMPCPP, bundle catastrophes no longer occur, and high bundle forces are reached more effectively. We reproduce the observed behavior with a simple simulation of microtubule bundle dynamics that takes into account previously measured force effects on single microtubules. Using this simulation, we also show that a constant compressive force on a growing bundle leads to oscillations in bundle length that are of potential relevance for chromosome oscillations observed in living cells.

Cells are organized by functional modules, which typically contain components whose removal severely compromises the module's function. Despite their importance, these components are not absolutely conserved between parts of the tree of life, suggesting that cells can evolve to perform the same biological functions with different proteins. We evolved Saccharomyces cerevisiae for 1000 generations without the important polarity gene BEM1. Initially the bem1∆ lineages rapidly increase in fitness and then slowly reach >90% of the fitness of their BEM1 ancestors at the end of the evolution. Sequencing their genomes and monitoring polarization reveals a common evolutionary trajectory, with a fixed sequence of adaptive mutations, each improving cell polarization by inactivating proteins. Our results show that organisms can be evolutionarily robust to physiologically destructive perturbations and suggest that recovery by gene inactivation can lead to rapid divergence in the parts list for cell biologically important functions.

Evolution has traditionally been a historical and descriptive science, and predicting future evolutionary processes has long been considered impossible. However, evolutionary predictions are increasingly being developed and used in medicine, agriculture, biotechnology and conservation biology. Evolutionary predictions may be used for different purposes, such as to prepare for the future, to try and change the course of evolution or to determine how well we understand evolutionary processes. Similarly, the exact aspect of the evolved population that we want to predict may also differ. For example, we could try to predict which genotype will dominate, the fitness of the population or the extinction probability of a population. In addition, there are many uses of evolutionary predictions that may not always be recognized as such. The main goal of this review is to increase awareness of methods and data in different research fields by showing the breadth of situations in which evolutionary predictions are made. We describe how diverse evolutionary predictions share a common structure described by the predictive scope, time scale and precision. Then, by using examples ranging from SARS‐CoV2 and influenza to CRISPR‐based gene drives and sustainable product formation in biotechnology, we discuss the methods for predicting evolution, the factors that affect predictability and how predictions can be used to prevent evolution in undesirable directions or to promote beneficial evolution (i.e. evolutionary control). We hope that this review will stimulate collaboration between fields by establishing a common language for evolutionary predictions.