Organisms are subject to the laws of physics, so the process of evolution is constrained by these fundamental laws. Classic and recent studies of the biophysical limits facing organisms have shown how fundamental physical constraints can be used to predict broad-scale relationships between body size and organismal biomechanics and physiology. In this talk I will focus on recent work which derives scaling laws for myriad features of single-cell organisms. I will then show how these laws are useful for ecological modeling, detecting life beyond Earth, and building new types of life. 

Research in the field of "stochastic thermodynamics" has uncovered a set of fundamental relationships between energy, information, and temporal irreversibility in nonequilibrium stochastic processes. Recently, these relationships have been used to derive thermodynamic bounds on the performance of molecular machines, including very general tradeoffs such as “thermodynamic uncertainty relations” and “thermodynamic speed limits”. I will review the basics of the field, as well as some promising recent developments and applications to molecular-scale biological systems. I will also discuss the challenges faced when applying these approaches at the cellular scale.

Several molecular markers have been described to predict stem cell potential with great success, e.g., in tissues like the blood, where a clear hierarchy of functional cell types can be identified. In other tissues, neutral competitive dynamics has been reported to remove a large fraction of biochemically identifiable stem cells, thereby creating a severe mismatch between cell-specific biochemical identity and the actual role of them as functional stem cells within the collective. In the case of the intestinal epithelium, this mismatch goes even further: In spite the number of biochemically identifiable (LGR5+) stem cells is the same in the crypts of both large and small intestines, lineage tracing techniques show that the number of them that actually play the role of stem cell displays remarkable differences. In that context, a natural question arises: How to determine the functional number and location of stem cells? To address this problem, I will revise a recent mathematical approach that proposes a new stem cell regulation mechanism, leading the final stem cell population to emerge only from the collective stochastic dynamics of cell movements and geometric considerations. Within this framework, one can accurately predict the robust emergence of a region made of functional stem cells and the actual number of them, as well as the lineage-survival probabilities, among other observables. The presented approach does not neglect the key role of biomarkers: Instead, it points towards the existence of complementary regulatory mechanisms --based on collective phenomena, stochastic dynamics and organ geometry--, playing an active role in determining the emergence and location of different cell functionalities.

The spontaneous generation of patterns and structures occurs in many living systems and is linked to biological form and function. Such processes often take place on domains which themselves evolve in time, and they can be guided by or coupled to geometrical features. The role of geometry in the self-organisation of functional structures however is not understood. I will present two biophysical examples that illustrate how geometry directs spatial organization at different scales. I will discuss how boundary geometry controls a topological defect transition that guides lumen nucleation in embryonic development [1], and how shape can act as a form of memory in cell-cell signaling [2].

[1] Guruciaga et al. arXiv:2403.08710 (2024)

[2] Dullweber et al. arXiv:2402.08664v2 (2024)

Computational methods are an ideal complement for inferring non directly measurable quantities such as forces or growth distribution. I will present a continuum approach where growth tensor is deduced with different objectives: for computing optimal locomotion of soft bodies on non-isotropic substrates, and for inferring the growth distribution that best matches a set of experimental measurements. Importantly, the uncertainty on the boundary conditions is also included in the inverse analysis, jointly with an iterative regularisation process. The methodology is applied  to different worm locomotion strategies, and axolotl limb growth. In each case it is revealed that non-isotropic friction and growth pattern are necessary conditions for reproducing experimental motions and deformations.

The exploration of vast genotype spaces poses a major challenge to evolving populations. As the number of genotype sequences representing viable phenotypes grows exponentially with genome length, understanding how populations navigate and adapt within such spaces becomes paramount. In this contribution, we delve into the dynamics of populations within genotype spaces using data from the environmental adaptation of populations of a small phage infecting E. coli (Qbeta phage) and SARS-CoV-2 genomes. Despite the vastness of the spaces they have in principle access to, even the largest realizable viral populations cover only a tiny fraction of possible sequences, constrained by a local, blind exploration of the nearest attainable. We explore how these populations achieve phenotypic improvements and evolutionary innovations, presenting data-driven insights from extensive datasets. Our analysis reveals crucial features of empirical populations that challenge established theoretical expectations, shedding light on the dynamic interplay between genotype and phenotype in the evolutionary process.

TBA

Correctly sized body parts are crucial for organismal function. For example, small discrepancies in limb length severely obstruct motility, and overgrowth of cardiac muscle is a prevalent cause of heart failure. The growth of different cells and organs must therefore be tightly coordinated to prevent that even small differences in growth rates amplify to large differences in size during development. How growth signals are propagated from cell to cell, and how organs integrate combinatorial signals from different tissues is a fundamental, yet poorly addressed question of high biomedical relevance. We address this question by combining live imaging and genetics using C. elegans with mathematical modelling.

We have developed time-lapse microscopy to precisely monitor the growth of the digestive tract of C. elegans in coordination with total body growth in hundreds of individual animals at high time resolution. Using these tools, we find a remarkable robustness of organ size that persists even under strong tissue-specific perturbation of growth and involves feedback control across multiple tissues. In a genetic screen, we identified a role for mechano-transduction via the transcriptional co-activator YAP-1 and stress signaling via p38 and Jun kinases in this control. We currently investigate how these conserved pathways coordinate growth in space and time during development to robustly yield an appropriate body plan.

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.

The collective migration of cohesive groups of cells is a hallmark of the tissue remodeling events that underlie embryonic morphogenesis, wound repair, and cancer invasion. Collective cell migration is characterized by the emergence of supra-cellular properties that control large-scale tissue organization. This suggests that a coarse-grained approach based on a hydrodynamic description of tissues as continuous active materials may shed some light on our understanding of the underlying physics of various tissue processes. Within this spirit, we reflect on the extent to which biological complexity can be encoded in a series of material parameters to build predictive, purely mechanical models of tissues based on very general physical principles. We present an overview of such a hydrodynamic approach to cell tissues as active polar fluids and discuss some examples where relatively simple models have been instrumental in elucidating relevant physical mechanisms behind collective cell behavior in epithelia, including active wetting, collective durotaxis, and spontaneous motility of cell clusters.