DELVIGNE LAB
Harnessing cellular entropy from artificial cells to complex communities
Our Research
We study how cell populations adapt and diversify using cutting-edge tools like flow cytometry and microfluidics. Our findings on cellular entropy and adaptation mechanisms drive innovations in bioprocessing and microbial stability, with broader implications for cancer research and beyond.
Innovative Methods
We use advanced technologies like automated flow cytometry, single-cell microfluidics, and custom-built tools to explore cell dynamics and interactions. Our innovative approaches, such as the Segregostat and modular modeling, drive breakthroughs in biological process control.
Meet Our Research Team
Our lab brings together a diverse group of researchers and technicians, each contributing their expertise to advance microbiology and biotechnology research. Together, we work on innovative projects with a commitment to understanding complex biological systems.
Our Publications
Our publications present the progression of our work on cellular population dynamics and phenotypic diversification. By sharing these studies, we hope to contribute to a deeper understanding of biological systems. We invite you to explore our findings.
Partners & Projects
We collaborate with outstanding partners and multiple research units to tackle complex scientific challenges. These partnerships enhance the impact of our work and drive innovation in microbiology and biotechnology.
Latest News
Stay updated with the latest from our lab, including research, publications, collaborations, and upcoming events. Follow our journey as we explore new frontiers in microbiology and biotechnology.
Our Laboratory’s Contributions:
Phenotypic diversification within isogenic cell populations is a well-established phenomenon, giving rise to collective behaviors such as bet-hedging and division of labor. In our laboratory, we investigate how cells within a population respond to extracellular stimuli and the resulting coordinated cell population dynamics. To explore this, we employ a range of single-cell analytical tools, including automated and reactive flow cytometry, microfluidics, and other cutting-edge technologies. We have also developed the concept of cellular entropy to quantify the degree of diversification in cell populations. Our research has revealed that the switching cost, or the loss of growth fitness for cells that decide to switch, is a major driver of cell population diversification.
Interestingly, we have observed that cellular systems with high switching costs, such as those resulting from the activation of burden some gene circuits or the switch to sporulation and competence, exhibit a Fitness-Entropy (F-E) compensation mechanism. This process, also known as bet-hedging, allows the cell population to cope with complex decisions by increasing cell-to-cell heterogeneity. However, this compensation mechanism is not instantaneous and requires time for establishment. To address this, we designed a cell-machine interface using reactive flow cytometry, known as the Segregostat, which enables the stimulation of cell populations in a timing-compatible manner. This technology has allowed us to control gene expression in various cell populations, including Gram-negative and Gram-positive bacteria, as well as eukaryotic systems like yeast. We have applied this approach to ensure the stabilization of cell populations for continuous bioprocessing, leading to collaborations with industrial partners such as Puratos, DSM, and GSK Biologicals. Building on this research, we are also investigating the stabilization of microbial co-cultures and the control of more complex phenotypes, such as general stress response and protein secretion for controlled delivery.
Ultimately, we believe that the F-E compensation mechanism is at the heart of cell collective behavior. In the future, we aim to elucidate the molecular basis of this mechanism and extend our investigation to more complex eukaryotic systems and collective behaviors, such as cancer development and tissue organization. To further understand the F-E compensation mechanism, we propose to challenge its validity in highly simplified systems using artificial cells. By adopting a top-down approach, we aim to decouple the complex interactions within natural cellular systems and investigate the fundamental principles governing this phenomenon in a controlled and simplified environment. This will enable us to test the robustness of the fitness-entropy compensation mechanism and identify its essential components, ultimately providing a deeper understanding of the underlying molecular mechanisms.