Jordi Garcia Ojalvo

Group website


Research Outline

The Dynamical Systems Biology laboratory studies the dynamics of living systems, from unicellular organisms to human beings. We use dynamical phenomena to identify the molecular mechanisms of biological processes such as cellular decision-making and spatial self-organization. Using a combination of theoretical modelling and experimental tools including time-lapse fluorescence microscopy and microfluidics, we investigate dynamical phenomena such as pulses and oscillations, and study how multiple instances of these processes coexist inside cells and tissues in a coordinated way. At a larger level of organization, we use mathematical models of neurons and neural tissues to link the structural properties of brain networks with their function.

 

Research Lines

Cellular computation

We study how cells process external information, by analyzing how the architecture of their regulatory networks allow them to encode the recent history of the cell and predict future changes in their environment.

Stress response in bacteria at the single-cell level

We investigate how bacterial cells self-organize in space and time when subject to different kinds of stresses, including nutrient starvation and antibiotics.

Dynamics of cellular signaling

We analyze the temporal organization of signaling processes at the single-cell level in organisms ranging from yeast to mammalian cells. We also study the regulation of the immune response in the context of autoimmune diseases such as multiple sclerosis.

Brain dynamics

We study the dynamics of the brain at different scales, from the microscopic scale of neuronal networks to the macroscopic scale of the full brain, in the context of a variety of pathologies including Down's syndrome and Alzheimer's disease.

 

 

Team during 2019-20

PhD students: Leticia Galera Laporta, Lara Escuaín de Poole, Carlos Toscano Ochoa, Keith Kennedy, Gabriel Torregrosa Cortés, Maria Kokkaleniou, Pablo Casaní Galdón, Alda Sabalic

 

Postdocs: Gang Zhou, Leila Cababie

 

Technicians: Miquel Sas Gil, Cristina Fernández Avilés

 

Selected publications 

Galera-Laporta, L., & Garcia-Ojalvo, J. (2020). Antithetic population response to antibiotics in a polybacterial community. Science Advances, 6(10), eaaz5108. https://doi.org/10.1126/sciadv.aaz5108

 

Lee, D. D., Galera-Laporta, L., Bialecka-Fornal, M., Moon, E. C., Shen, Z., Briggs, S. P., Garcia-Ojalvo, J., & Süel, G. M. (2019). Magnesium Flux Modulates Ribosomes to Increase Bacterial Survival. Cell, 177(2), 352-360.e13. https://doi.org/10.1016/j.cell.2019.01.042

 

Matsuda, M., Hayashi, H., Garcia-Ojalvo, J., Yoshioka-Kobayashi, K., Kageyama, R., Yamanaka, Y., Ikeya, M., Toguchida, J., Alev, C., & Ebisuya, M. (2020). Species-specific segmentation clock periods are due to differential biochemical reaction speeds. Science, 369(6510), 1450–1455. https://doi.org/10.1126/science.aba7668

 

Saiz, N., Mora-Bitria, L., Rahman, S., George, H., Herder, J., Garcia-Ojalvo, J., & Hadjantonakis, A.-K. (2020). Growth factor-mediated coupling between lineage size and cell fate choice underlies robustness of mammalian development. ELife, 9, e56079. https://doi.org/10.7554/eLife.56079

 

Yang, C.-Y., Bialecka-Fornal, M., Weatherwax, C., Larkin, J. W., Prindle, A., Liu, J., Garcia-Ojalvo, J., & Süel, G. M. (2020). Encoding Membrane-Potential-Based Memory within a Microbial Community. Cell Systems, 10(5), 417-423.e3. https://doi.org/10.1016/j.cels.2020.04.002

 

Other relevant information 

  • Invited talks in the following conferences:

    • Int. Conference on Quantitative Biology, Yantai, China, June 23, 2019 

    • Statphys 27, Buenos Aires, July 11, 2019 

    • Annual meeting of the German Physical Society, online, March 18, 2020

  • Invitations for research stays in other institutions:

    • University of California San Diego, January 13-19, 2020

    • California Institute of Technology, March 6-14, 2020 

 

 

Co-culture of B. subtilis (magenta) and E. coli (blue) bacteria under low antibiotic stress

 

Agent based simulation of the cell-fate decision between epiblast (red cells) and primitive endoderm (blue cells) in the early mouse embryo (top row), and in a two-dimensional disk of pluripotent cells (bottom row).