Emiliano Perez Ipiña
Postdoctoral researcher
Contact
Emiliano Perez Ipiña
Postdoctoral researcher
Motility and Sensing in Microorganisms
I am interested in the diffusion and motility of microorganisms, such as bacteria and cells, the interaction with their habitats, the propagation of information inside biological systems, and the robustness of signal processing under fluctuating environments.
In my research, I aim to explain experimental observations with simple theoretical models that allow me to identify the fundamental elements underlying these biological processes. To do so, I combine tools from statistical physics, stochastic processes, and active matter physics together with detailed data analysis methods.
In my research, I aim to explain experimental observations with simple theoretical models that allow me to identify the fundamental elements underlying these biological processes. To do so, I combine tools from statistical physics, stochastic processes, and active matter physics together with detailed data analysis methods.
The Interplay between Motility, Migration, and the Environment in Microorganisms
The movement of microorganisms, including some eukaryotic cells and bacteria, is essential for numerous biological functions.
The motility mechanisms of bacteria and eukaryotic cells are very different, but they share something in common: motility and its transport properties are the result of a complex interplay between the internal machinery of cells and the environment.
Cells need to sense and respond to environmental signals that tell them when and where to move. They also need to navigate complex landscapes, such as crawling across the extracellular matrix (ECM) or swimming through the bloodstream. In addition, cells can create their own signals by secreting and degrading chemoattractants to establish self-generated gradients or modify their environment by reorganizing the ECM and creating a footprint.
To fully understand the mechanisms underlying cell movement and migration, we need to study these phenomena in the context in which they occur. Thus, it is essential to consider the relationship between cells and their environment when studying the complex process of motility and migration.
Cells need to sense and respond to environmental signals that tell them when and where to move. They also need to navigate complex landscapes, such as crawling across the extracellular matrix (ECM) or swimming through the bloodstream. In addition, cells can create their own signals by secreting and degrading chemoattractants to establish self-generated gradients or modify their environment by reorganizing the ECM and creating a footprint.
To fully understand the mechanisms underlying cell movement and migration, we need to study these phenomena in the context in which they occur. Thus, it is essential to consider the relationship between cells and their environment when studying the complex process of motility and migration.
- Cell migration directed by secreted footprints
Cell migration often requires adhesion to the extracellular matrix (ECM). As they move, cells can modify the ECM and leave a footprint behind, for example by depositing new matrix proteins such as fibronectin or laminin. Do cells interact with their own footprint to modify their motility behavior? In vitro experiments with MDCK epithelial cells show that they do. By using their own footprint, cells can direct their motility and adjust their behavior to be more confined or exploratory, resulting in a range of motility patterns from oscillations to circular motion, looping or exploring large regions. Furthermore, cells can also use other cells' footprints to guide their motion, opening up new mechanisms of guided migration not just at the individual but also at the collective level.
- Perez Ipiña, E., d'Alessandro, J., Ladoux, B., Camley, B. A. Secreted footprints let cells switch between confined, oscillatory, and exploratory migration. bioRxiv 2023.09.14.557437 (2023) [link].
- How accurate cells can sense chemical gradients when their own position is uncertain?
Eukaryotic cells sense chemical gradients to guide their motion. They do this by comparing the concentration at their front and back. However, individual cells struggle to detect shallow gradients, as the concentration difference is too small to distinguish from intrinsic fluctuations. To overcome this limitation, cells can form groups and integrate concentration measurements from a larger region. However, accurately identifying each cell's position within the gradient is essential to ensure accurate measurements. If cells have some uncertainty about their position, how this affects gradient sensing accuracy?
`
- Perez Ipiña, E., & Camley, B. A. (2022). Collective gradient sensing with limited positional information. Physical Review E, 105(4), 044410 [link].
- Perez Ipiña, E., & Ponce Dawson, S. (2016). Fluctuations, correlations, and the estimation of concentrations inside cells. PloS one, 11(3), e0151132 [link].
- Perez Ipiña, E., & Dawson, S. P. (2014). How long should a system be observed to obtain reliable concentration estimates from the measurement of fluctuations? Biophysical journal, 107(11), 2674-2683 [link].
- A physical approach to bacterial infections
Bacterial infections rely on bacteria locating target cells. To do so, bacteria use chemotaxis to guide themselves toward preferred niches. However, when bacteria move from the lumen to the intestinal wall, the hydrodynamics interactions force bacteria to swim in smooth circular trajectories and highly reduce their ability to tumble and chemotax. This opens the question: how bacteria moving near surfaces, a required first step prior to infection, can locate target cells? Different bacteria use different strategies. Escherichia coli can adhere to the surface to break the circular trajectories and restart motion into a new direction maximizing their diffusivity over the surface. Controlling their adhesion to the surface they can recover a mechanism that would allow them to perform chemotaxis and guide their motion. Salmonella, on the other hand, uses a random search strategy to locate target cells.
- Otte, S., Perez Ipiña, E., Pontier-Bres, R., Czerucka, D., & Peruani, F. (2021). Statistics of pathogenic bacteria in the search of host cells. Nature communications, 12(1), 1-9 [link].
- Perez Ipiña, E., Otte, S., Pontier-Bres, R., Czerucka, D., & Peruani, F. (2019). Bacteria display optimal transport near surfaces. Nature Physics, 15(6), 610-615 [link].
