Synthetic biology is one of the most exciting strategies for the investigation of living organisms and lies at the intersection of biology and engineering. Originally developed in prokaryotes, the idea of deciphering biological phenomena through building artificial genetic circuits and studying their behaviours has rapidly demonstrated its potential in a broad range of fields in the life sciences. From the assembly of synthetic genomes to the generation of novel biological functions, yeast cells have imposed themselves as the most powerful eukaryotic model for this approach. However, we are only beginning to explore the possibilities of synthetic biology, and the perspectives it offers in a genetically amenable system such as yeasts are endless.

Monitoring cellular responses to changes in growth conditions and perturbation of targeted pathways is integral to the investigation of biological processes. However, manipulating cells and their environment during live-cell-imaging experiments still represents a major challenge. While the coupling of microfluidics with microscopy has emerged as a powerful solution to this problem, this approach remains severely underexploited. Indeed, most microdevices rely on the polymer polydimethylsiloxane (PDMS), which strongly absorbs a variety of molecules commonly used in cell biology. This effect of the microsystems on the cellular environment hampers our capacity to accurately modulate the composition of the medium and the concentration of specific compounds within the microchips, with implications for the reliability of these experiments. To overcome this critical issue, we developed new PDMS-free microdevices dedicated to live-cell imaging that show no interference with small molecules. They also integrate a module for maintaining precise sample temperature both above and below ambient as well as for rapid temperature shifts. Importantly, changes in medium composition and temperature can be efficiently achieved within the chips while recording cell behaviour by microscopy. Compatible with different model systems, our platforms provide a versatile solution for the dynamic regulation of the cellular environment during live-cell imaging.

Cell proliferation is regulated by cyclin-dependent kinases (Cdks) and requires the periodic expression of particular gene clusters in different cell cycle phases. However, the interplay between the networks that generate these transcriptional oscillations and the core cell cycle machinery remains largely unexplored. In this work, we use a synthetic regulable Cdk1 module to demonstrate that periodic expression is governed by quantitative changes in Cdk1 activity, with different clusters directly responding to specific activity levels. We further establish that cell cycle events neither participate in nor interfere with the Cdk1-driven transcriptional program, provided that cells are exposed to the appropriate Cdk1 activities. These findings contrast with current models that propose self-sustained and Cdk1-independent transcriptional oscillations. Our work therefore supports a model in which Cdk1 activity serves as a quantitative platform for coordinating cell cycle transitions with the expression of critical genes to bring about proper cell cycle progression.

In present-day eukaryotes, the cell division cycle is controlled by a complex network of interacting proteins, including members of the cyclin and cyclin-dependent protein kinase (Cdk) families, and the Anaphase Promoting Complex (APC). Successful progression through the cell cycle depends on precise, temporally ordered regulation of the functions of these proteins. In light of this complexity, it is surprising that in fission yeast, a minimal Cdk network consisting of a single cyclin-Cdk fusion protein can control DNA synthesis and mitosis in a manner that is indistinguishable from wild type. To improve our understanding of the cell cycle regulatory network, we built and analysed a mathematical model of the molecular interactions controlling the G1/S and G2/M transitions in these minimal cells. The model accounts for all observed properties of yeast strains operating with the fusion protein. Importantly, coupling the model's predictions with experimental analysis of alternative minimal cells, we uncover an explanation for the unexpected fact that elimination of inhibitory phosphorylation of Cdk is benign in these strains while it strongly affects normal cells. Furthermore, in the strain without inhibitory phosphorylation of the fusion protein, the distribution of cell size at division is unusually broad, an observation that is accounted for by stochastic simulations of the model. Our approach provides novel insights into the organization and quantitative regulation of wild type cell cycle progression. In particular, it leads us to propose a new mechanistic model for the phenomenon of mitotic catastrophe, relying on a combination of unregulated, multi-cyclin-dependent Cdk activities.