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Towards a Theory of Microbial Ecosystems
A major unresolved question in microbiome research is whether the complex ecological patterns observed in surveys of natural communities can be explained and predicted by fundamental, quantitative principles. Bridging theory and experiment is hampered by the multiplicity of ecological processes that simultaneously affect community assembly and a lack of theoretical tools for modeling diverse ecosystems. Here, I will present a simple ecological model of microbial communities that reproduces large-scale ecological patterns observed across multiple natural and experimental settings including compositional gradients, clustering by environment, diversity/harshness correlations, and nestedness. Surprisingly, our model works despite having a “random metabolisms” and “random consumer preferences”. This raises the natural of question of why random ecosystems can describe real-world experimental data. In the second, more theoretical part of the talk, I will answer this question by showing that when a community becomes diverse enough, it will always self-organize into a stable state whose properties are well captured by a “typical random ecosystems”.
Self-organization of chemically active colloids with non-reciprocal interactions
Cells and microorganisms produce and consume all sorts of chemicals, from nutrients to signalling molecules. The same happens at the nanoscale inside cells themselves, where enzymes catalyse the production and consumption of the chemicals needed for life. In this work, we have found a generic mechanism by which such chemically-active particles, be it cells or enzymes or engineered synthetic colloids, can "sense" each other and ultimately self- organize in a multitude of ways. A peculiarity of these chemical-mediated interactions is that they break action-reaction symmetry : for example, one particle may be repelled from a second particle, which is in turn attracted to the first one, so that it ends up "chasing" it. Such chasing interactions allow for the formation of large clusters of particles that "swim" autonomously. Regarding enzymes, we find that they can spontaneously aggregate into clusters with precisely the right composition, so that the product of one enzyme is passed on, without lack or excess, to the next enzyme in the metabolic cascade.
“Cell Surface Topography: The Role of Protein Size at Cell-Cell Interfaces”
Membrane interfaces formed at junctions between cells are often associated with characteristic patterns of membrane protein organization, such as in epithelial tissues and between cells of the immune system. While this organization can be influenced by receptor clustering, lipid domain formation, and cytoskeletal dynamics, this talk will describe how cell surface molecular height can directly contribute to the spatial arrangement of membrane proteins and downstream signaling. Using a new optical method for characterizing molecular height, together with experiments using giant vesicles in vitro systems and live immune cells, we are investigating how cell surface molecular heights can be key contributors to cell-cell communication.
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