The question of the origin of homochirality of living matter, or the dominance of one handedness for all molecules of life across the entire biosphere, is a long-standing puzzle in the research on the Origin of Life. In the fifties, Frank proposed a mechanism to explain homochirality based on the properties of a simple autocatalytic network containing only a few chemical species. Following this work, chemists struggled to find experimental realizations of this model, possibly due to a lack of proper methods to identify autocatalysis [1]. In any case, a model based on a few chemical species seems rather limited, because prebiotic earth is likely to have consisted of complex ‘soups’ of chemicals. To include this aspect of the problem, we recently proposed a mechanism based on certain features of large out-of-equilibrium chemical networks [2]. We showed that a phase transition towards an homochiral state is likely to occur as the number of chiral species in the system becomes large or as the amount of free energy injected into the system increases. Through an analysis of large chemical databases, we showed that there is no need for very large molecules for chiral species to dominate over achiral ones; it already happens when molecules contain about 10 heavy atoms. We also analyzed the various conventions used to measure chirality and discussed the relative chiral signs adopted by different groups of molecules [3]. We then proposed a generalization of Frank’s model for large chemical networks, which we characterized using random matrix theory. This analysis includes sparse networks, suggesting that the emergence of homochirality is a robust and generic transition. References: [1] A. Blokhuis, D. Lacoste, and P. Nghe, PNAS (2020), 117, 25230. [2] G. Laurent, D. Lacoste, and P. Gaspard, PNAS (2021) 118 (3) e2012741118. [3] G. Laurent, D. Lacoste, and P. Gaspard, Proc. R. Soc. A 478:20210590 (2022).

Nature is replete with extraordinary materials that can grow, move, respond, and adapt. In this talk I will describe our ongoing efforts to develop advanced polymeric materials, inspired by nature. First, I will describe my group’s efforts to develop ultrastiff, ultratough materials inspired by the byssal materials of marine mussels. These adhesive contacts allow mussels to secure themselves to rocks, wood, metals and other surfaces in the harsh conditions of the intertidal zone. By developing a foundational understanding of the structure-mechanics relationships and processing of the natural system, we can design high-performance materials that are extremely strong without compromising extensibility, as well as macroporous materials with tunable toughness and strength. In the second half of the talk, I will describe new efforts to exploit light as a means of remote control and power. By leveraging the phototransduction pathways of highly-absorbing, negatively photochromic molecules, we can drive the motion of amorphous polymeric materials as well as liquid flows. These innovations enable applications in packaging, connective tissue repair, soft robotics, and optofluidics.

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.

A key challenge in modern soft matter is to identify the principles that govern the organisation and functionality in non-equilibrium systems. Current research efforts largely focus on non-equilibrium processes that occur either at the single-molecule scale (e.g. protein and DNA conformations under driving forces), or at the scale of whole tissues, organisms, and active colloidal and microscopic objects. However, the range of the scales in-between — from molecules to large-scaled molecular assemblies that consume energy and perform work — remains under-explored. This is, nevertheless, the scale that is crucial for the function of a living cell, where molecular self-assembly driven far from equilibrium produces mechanical work needed for cell reshaping, transport, motility, division, and healing. Today I will discuss physical modelling of active elastic filaments, called ESCRT-III filaments, that dynamically assemble and disassemble on cell membranes. This dynamic assembly changes the filaments’ shape and mechanical properties and leads to the remodelling and cutting of cells. I will present a range of experimental comparisons of our simulation results: from ESCRT-III-driven trafficking in eukaryotes to division of evolutionary simple archaeal cells.

Neural networks can learn and recognize subtle correlations in high dimensional inputs. However, neural networks are simply many-body systems with strong non-linearities and disordered interactions. Hence, many-body physical systems with similar interactions should be able to show neural network-like behavior. Here we show neural network-like behavior in the nucleation dynamics of promiscuously interacting molecules with multiple stable crystalline phases. Using a combination of theory and experiments, we show how the physics of the system dictates relationships between the difficulty of the pattern recognition task solved, time taken and accuracy. This work shows that high dimensional pattern recognition and learning are not special to software algorithms but can be achieved by the collective dynamics of sufficiently disordered molecular systems.

Over the past five years, our understanding of how mechanical processes act across multiple scales to direct morphogenesis has advanced significantly. Yet, there remain numerous open questions, including the role of mechanics in tissue shaping, cancer dissemination, and cellular aging. The From Molecules to Organs:The Mechanobiology of Morphogenesis conference will bring together world leaders in the fields of mechanobiology and morphogenesis. The three-day conference will span scales, from single molecules up to whole organisms.

Over the past five years, our understanding of how mechanical processes act across multiple scales to direct morphogenesis has advanced significantly. Yet, there remain numerous open questions, including the role of mechanics in tissue shaping, cancer dissemination, and cellular aging. The From Molecules to Organs:The Mechanobiology of Morphogenesis conference will bring together world leaders in the fields of mechanobiology and morphogenesis. The three-day conference will span scales, from single molecules up to whole organisms.

Colloidal dispersions of rod-like particles are widely accepted as convenient model systems to study the phase behavior of liquid-crystal forming systems, commonly found in LCDs. This is due to the fact that colloidal rods exhibit analogous phase behavior to that of elongated molecules, while they can be directly observed by optical microscopy. Recently, there has been a surge of interest in the liquid crystalline behaviour of so-called bent-core, or banana-shaped, molecules. This is due to their ability to form exotic biaxial nematic phases such as the twist-bend and splay-bend nematic phase, which may be of particular interest inherent to their fast switching response in LCDs. Here, we develop model “banana-shaped” colloidal particles with tunable dimensions and curvature, whose structure and dynamics are accessible at the particle level. 
By heating initially straight rods made of SU-8 photoresist, we induce a controllable shape deformation that causes the rods to buckle into banana-shaped particles. We elucidate the phase behavior of differently curved colloidal bananas using confocal microscopy. Although highly curved bananas only form isotropic phases, less curved bananas exhibit very rich phase behavior, including biaxial nematic phases, polar and antipolar smectic-like phases, and even the long-predicted, elusive splay-bend nematic phase.

Life of biological molecules spans time and length scales relevant at atomic to cellular time and length scales. Hence, novel molecular modeling approaches are required to be inherently multi-scale. Here we describe multiple methodologies developed in our laboratory: rapid discrete molecular dynamics simulation algorithm, protein design and structural refinement tools. Using these methodologies, we describe therapeutic strategies to combat this HIV and cancer, as well as design novel approaches for controlling proteins in living cells and organisms.