Speaker: Miguel Bernabeu  (Oxford)
Host: Kristina Haase  (EMBL BCN)

The aging process represents one of biology's most complex system-level phenomena. A major challenge is moving from observing its correlates to identifying its fundamental, targetable bottlenecks. In this talk, I will explore a reverse-engineering approach, using pharmacological interventions in model organisms to deconstruct the mechanisms of aging and pinpoint promising avenues for intervention.  I will discuss how we can leverage existing biological data and what new, targeted measurements are required to fill critical gaps. A key question is the selection of appropriate model organisms that offer the right balance of physiological complexity, experimental tractability, and translational relevance for aging research. Furthermore, I will examine the role of artificial intelligence in this endeavor: while AI excels at finding generalizable patterns, its success is critically dependent on the quality and nature of the underlying data—an area where significant improvements are needed.  I will present examples from my work across multiple species, including the development of a scalable high-throughput platform for pharmaco-biology in Daphnia. This system allows us to characterize drug-induced perturbations and link them to lifespan and healthspan outcomes. We will discuss a computational framework to regress macro-phenotypes to the molecular pathways. Finally, I will outline central challenges in the field and propose concrete directions for researchers interested in joining the effort to reverse engineer aging.

Plant development occurs as an interplay of signalling, growth, and environmental cues, becoming a highly dynamic and complex system. In our lab, we study the dynamics of plant developing tissues, combining mathematical modelling, confocal microscopy, and quantitative image analysis.In this talk, I will first explain how cells become different from one another as they divide and grow in the Arabidopsis plant sepal, focusing on the case of giant cell patterning. I will demonstrate that giant cells appear in a random spatial pattern and become clustered while the surrounding cells divide. This finding shows that cell proliferation can have a fundamental role in shaping spatial patterns. Secondly, I will present our work on the dynamics of the floral transition in Arabidopsis, by which the plant changes from producing leaves to producing flowers. Our results indicate that a time-dependent bistable switch underlies the floral transition dynamics, leading to a critical slowing down and introducing an unexpected timescale on the transition. I will also discuss how this behaviour relates to the transition robustness and its reversibility.

Protein secretion is an essential process in cell physiology, responsible for the release of proteins such as collagens, insulin, neurotransmitters, and many others. To achieve this, proteins follow the so-called secretory pathway, which begins at the endoplasmic reticulum (ER). Thus, the first and fundamental step is the export of proteins from the ER. However, the mechanisms by which diverse cargoes (from small soluble proteins to large and complex molecules) are selectively sorted and packaged for export remain incompletely understood. In this talk, I will present our current experimental and theoretical approaches to uncover the biophysical principles governing ER export.

First, using a single-molecule microscopy technique (single-particle tracking, sptPALM), we directly probe the dynamic behavior of secretory proteins at ER exit sites in living cells, with spatial and temporal resolutions of ~10 nm and 10 ms. These measurements reveal how molecular mobility, confinement, and interactions contribute to cargo selection and concentration prior to export.

Second, I will introduce a physical modeling framework that captures the formation and function of export carriers, with a particular focus on large cargoes that challenge conventional vesicular transport mechanisms. The model highlights how physical constraints such as membrane deformation, crowding, and protein self-organization shape export efficiency and carrier architecture.

Together, these complementary approaches are beginning to provide a quantitative view of ER export as an emergent process arising from the interplay between molecular interactions and membrane mechanics.