Biological neurons grown in the laboratory in the form of neuronal cultures are one of the most compelling examples of a complex system, in which an ensemble of initially disconnected neurons is able to reconnect and form a de novo complex network within days. This network may exhibit different forms of collective activity that depend on the underpinned connectivity between neurons. By using resources from neuroengineering, one can control this connectivity and build in vitro systems that mimic key organizational features of the brain, specifically modularity. Such systems are useful not only to understand the emergence of collective behavior in neuronal assemblies, but also to design brain-on-chip models to explore and treat neurological disorders in a controlled manner. In this talk, I will review the strategies that we have implemented in my laboratory at the University of Barcelona to prepare and analyze neuronal cultures for both the physics and medical communities. I will also introduce recent developments in the context of biological computation on biohybrid devices, where electronic and biological circuits interact with one another.

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Complex systems unfold nonlinear interactions and can suffer regime shifts which are of paramount importance since they can involve the emergence and persistence of a disease or the extinction of a species within an ecosystem. Such regime shifts can be achieved by different mechanisms and their understanding is crucial to potentially anticipate them and have information about the time scales of such shifts. Dynamical systems theory and computational research allows the study of such mechanisms in a general way or for specific complex systems such as ecosystems or viral infections. In this seminar, I will discuss different mechanisms causing regime shifts, paying special attention to critical transitions given by tipping points. I will discuss important dynamical properties arising close to critical transitions such as transients and the so-called warning signals. These signals provide a powerful way to detect that a given system is approaching a critical transition without the necessity to have a detailed knowledge of the underlying system dynamics. To foster discussion and possible new collaborations, I will provide examples of these topics identified in experimental and natural systems.

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I will talk about two project involving oriented tissue flows.

1) Most animals display one or more body axes (e.g. head-to-tail, left-right, ventral-dorsal), which usually emerge during early embryogenesis. In our work, we demonstrate that large-scale tissue flows can play an important role for the formation of body axes. To this end, we used aggregates of mouse stem cells, called gastruloids. Gastruloids are initially spherically symmetric, but later form an axis defined by the polarized expression patterns of specific proteins such as T/Brachyury or E-cadherin. While such early embryonic pattern formation is usually studied in the context of genetic and bio-chemical interactions, we show that also advection of cells with tissue flows contribute approximately 1/3 to the overall polarization. We then more closely analyzed the flow field in the gastruloids and found that the dominant component was a recirculating flow. We further showed that this large-scale flow could be understood as a Marangoni flow, i.e. driven by interface and surface tension differences. We further independently confirmed the existence of differential interface and surface tensions though aggregate fusion experiments. Taken together, we found that in polarized gastruloids, differential tensions drive recirculation flows, which in turn further amplify polarization. We expect such a feedback loop to act also in many other systems in vitro and in vivo.

2) Oriented tissue deformation is a fundamental process omnipresent during animal development. However, how exactly cells coordinate to achieve robust oriented deformation on the tissue scale remains elusive. From a physics perspective, deforming tissues can be described as oriented active materials. However, it is known that oriented active materials can inherently exhibit instabilities such as the Simha-Ramaswamy instability. This instability destroys the homogeneously deforming state of active materials. This raises the question of how robust anisoropic tissue deformation can be possible during animal development. In particular, we ask whether the presence of a chemical signalling gradient (e.g. a morphogen gradient) can help stabilize oriented tissue deformation. Using a combination of vertex and hydrodynamic models, we find that stability depends on whether the signalling gradient acts to extend or contract the tissue along the gradient direction. In particular, gradient-extensile coupling can be stable, while gradient-contractile coupling is generally unstable. Intriguingly, developing tissues seem to exclusively use the gradient-extensile and not the unstable gradient-contractile coupling, suggesting that nature might just never have evolved the latter. Our work points to a potential new developmental principle that is directly rooted in active matter physics.

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Around four billion years ago, chemical and geological processes on the ancient Earth caused increases in complexity of organic molecules, creating RNA, DNA, protein, polysaccharide, membrane-forming amphipaths, and metabolism. But how?

In our center are learning to understand the origins of life through the geology, physics, chemistry and biochemistry of water. Water serves as a medium, as a chemical hub, and as an energy currency during experimental chemical evolution. We have developed an experimental platform that allows us to perform and evaluate chemical evolution. Based in part on our results, here we describe why (we think) the origins of life:

(i) represents an experimentally addressable and solvable problem that one day will be understood and generally accepted,
(ii) is not technically difficult - it happened on the Hadean Earth, in the absence of post docs, pH meters, rotavaps, HPLCs, NMRs, and mass spectrometers,
(iii) is not a series of idiosyncratic and spectacular one-off events but is reproducible and even mundane,
(iv) is a specific example of a class of processes that we call general chemical evolution, and
(v) can be redirected and exploited for a broad array of chemical applications ranging from materials science, to nanotechnology, to medicine, to astrobiology (i.e., there is money to be made).

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During the differentiation of blood stem cells, gene expression needs to be tightly controlled, but it is unclear how gene regulatory elements encode this specificity. Here, we took a bottom-up approach and attempted to engineer lineage- and stage-specific enhancers from scratch, by systematically embedding transcription factor (TF) binding sites into random DNA. In total, we designed 60,000 candidate enhancers, and measured their ability to drive transcription in seven hematopoietic progenitor states, using a primary cell differentiation model. Our results reveal dose- and context-dependent duality behavior of TFs, encoding of specificity by low-affinity sites, and an unexpected ability of stem cell TFs to turn lineage TFs into repressors. I will also discuss ideas to describe our results with mechanistic models.

If you would like to attend the seminar, please register here