Cellular organization in lab-evolved and extant multicellular species obeys a maximum entropy law.

The prevalence of multicellular organisms is due in part to their ability to form complex structures. How cells pack in these structures is a fundamental biophysical issue, underlying their functional properties. However, much remains unknown about how cell packing geometries arise, and how they are affected by random noise during growth - especially absent developmental programs. Here, we quantify the statistics of cellular neighborhoods of two different multicellular eukaryotes: lab-evolved 'snowflake' yeast and the green alga Volvox carteri. We find that despite large differences in cellular organization, the free space associated with individual cells in both organisms closely fits a modified gamma distribution, consistent with maximum entropy predictions originally developed for granular materials. This 'entropic' cellular packing ensures a degree of predictability despite noise, facilitating parent-offspring fidelity even in the absence of developmental regulation. Together with simulations of diverse growth morphologies, these results suggest that gamma-distributed cell neighborhood sizes are a general feature of multicellularity, arising from conserved statistics of cellular packing.

Topological constraints in early multicellularity favor reproductive division of labor.

Reproductive division of labor (e.g. germ-soma specialization) is a hallmark of the evolution of multicellularity, signifying the emergence of a new type of individual and facilitating the evolution of increased organismal complexity. A large body of work from evolutionary biology, economics, and ecology has shown that specialization is beneficial when further division of labor produces an accelerating increase in absolute productivity (i.e. productivity is a convex function of specialization). Here we show that reproductive specialization is qualitatively different from classical models of resource sharing, and can evolve even when the benefits of specialization are saturating (i.e. productivity is a concave function of specialization). Through analytical theory and evolutionary individual-based simulations, we demonstrate that reproductive specialization is strongly favored in sparse networks of cellular interactions that reflect the morphology of early, simple multicellular organisms, highlighting the importance of restricted social interactions in the evolution of reproductive specialization.

Cyberphysical risks of hacked internet-connected vehicles.

The integration of automotive technology with internet connectivity promises to both dramatically improve transportation while simultaneously introducing the potential for new unknown risks. Internet-connected vehicles are like digital data because they can be targeted for malicious hacking. Unlike digital data, however, internet-connected vehicles are cyberphysical systems that physically interact with each other and their environment. As such, the extension of cybersecurity concerns into the cyberphysical domain introduces new possibilities for self-organized phenomena in traffic flow. Here we study a scenario envisioned by cybersecurity experts leading to a large number of internet-connected vehicles being suddenly and simultaneously disabled. We investigate posthack traffic using agent-based simulations and discover the critical relevance of percolation for probabilistically predicting the outcomes on a multilane road in the immediate aftermath of a vehicle-targeted cyberattack. We develop an analytic percolation-based model to rapidly assess road conditions given the density of disabled vehicles and apply it to study the street network of Manhattan (New York City, New York, USA) revealing the city's vulnerability to this particular cyberphysical attack. While a comprehensive investigation of city-scale traffic around hacked vehicles is an extremely complicated problem, we find that the statistical physics of percolation can provide an estimate of the number of vehicles that critically disrupts citywide traffic flow. Our upper-bound estimate represents a quantification of citywide traffic disruptions when multiple vehicles are hacked.

Drivers of Spatial Structure in Social Microbial Communities.

Microbes are social organisms, interacting primarily through secreted biomolecules. Many traits have evolved based solely on their effects upon other community members, yet even individually beneficial traits often create social side effects that are mediated by spatial population structure. Predicting the evolution of many microbial traits thus requires a comprehensive understanding of their social consequences. In this review, we examine the critical role of population spatial structure in microbial social evolution. We briefly review key mechanisms structuring microbial communities, focusing primarily on the universal roles of cellular death and reproduction. Finally, we explain how spatial assortment can be efficiently calculated in two-dimensional, surface-attached populations.

Immotile Active Matter: Activity from Death and Reproduction.

Unlike equilibrium atomic solids, biofilms-soft solids composed of bacterial cells-do not experience significant thermal fluctuations at the constituent level. However, living cells stochastically reproduce and die, provoking a mechanical response. We investigate the mechanical consequences of cellular death and reproduction by measuring surface-height fluctuations of biofilms containing two mutually antagonistic strains of Vibrio cholerae that kill one another on contact via the type VI secretion system. While studies of active matter typically focus on activity via constituent mobility, here, activity is mediated by reproduction and death events in otherwise immobilized cells. Biofilm surface topography is measured in the nearly homeostatic limit via white light interferometry. Although biofilms are far from equilibrium systems, measured surface-height fluctuation spectra resemble the spectra of thermal permeable membranes but with an activity-mediated effective temperature, as predicted by Risler, Peilloux, and Prost [Phys. Rev. Lett. 115, 258104 (2015)PRLTAO0031-900710.1103/PhysRevLett.115.258104]. By comparing the activity of killer strains of V. cholerae with that of genetically modified strains that cannot kill each other and validating with individual-based simulations, we demonstrate that extracted effective temperatures increase with the amount of death and reproduction and that death and reproduction can fluidize biofilms. Together, these observations demonstrate the unique physical consequences of activity mediated by death and reproduction events.