Cells live in communities where they interact with each other and their environment. By coordinating individuals, such interactions often result in collective behavior that emerge on scales larger than the individuals that are beneficial to the population. At the same time, populations of individuals display genotypic and phenotypic heterogeneity, which diversifies individual behavior, enables division of labor, and enhances the resilience of the population in unexpected or stressful situations. This presents a dilemma: while individuality confers advantages, it can undermine coordination, raising the question of how cell populations reconcile collective behavior with individuality. The first part of this talk will introduce some of the basic concepts that underly collective behavior on the cellular scale using examples from different systems. The second part will examine how populations of cells reconciliate individuality with group behavior during collective migration, and how that leads to adaptation of phenotypic diversity without involving environment-dependent gene regulation or mutations. This work was supported by NIGMS awards R01GM138533, R01GM106189, and R35GM158058

Cells of all kinds work together in multicellular behaviors ranging from collective migration to development. Simple laboratory assays have revealed a number of different behaviors cells engage in and how they’re coordinated. However, natural environments are more spatially complex than these assays in ways that change both how cells can coordinate with one another and what behaviors they might need to perform. To understand how the complexity of natural environments shapes multicellular coordination and behaviors, we focus on how a soil-dwelling microbe communicates and behaves in a naturalistic soil model environment during starvation-induced aggregation. We find that to aggregate in synthetic soil, these cells engage in new behaviors such as bridge building and environmental remodeling that resemble how animals behave. These shared strategies for navigating complex spaces suggest there may also be shared coordination strategies that nature implements at both the cellular and organismal scales.

Multicellular organisms are composed of many distinct cell types that are tightly coordinated to support the functioning of the whole. The degree of collectiveness involved is extraordinarily high, so much so that the collective becomes an individual. This is most evident during development, where cascades of coordinated events unfold as cells work together to perform tasks no single cell could achieve alone. A hallmark of such collective behavior is the emergence of supracellular order. Whether observed in the system’s dynamics or spatial organization, the ability of cellular collectives to self-organize into coherent entities that transcend individual cell boundaries is central to the makeup of an organism. Yet, to an external observer, these collective processes appear highly programmed. The reproducibility and robustness seen in development suggest a level of encoding, raising a provocative question: is all the complexity of multicellular coordination really encoded within the ~1 GB of our genome? If not, where does it come from? This raises a central tension: are emergent collective behaviors programmed, and if so, how? Or do they arise as spontaneous byproducts of collective dynamics with minimal constraint? I will begin with fundamentals of developmental biology to define the scale of the organism and revisit the historical debate between preformation and epigenesis. I will then focus on a specific process -collective cell migration- to highlight key features of biological collectiveness, particularly the concept of supracellularity. From there, I will turn to the concept of emergence, which underpins many forms of collective behavior. Drawing on physics, I will show how out-of-equilibrium systems can spontaneously organize, suggesting a physical route to complexity that does not rely on explicit genomic encoding. This view appears to resolve the paradox of limited genetic information giving rise to intricate organismal structures. But it also opens new questions. Can emergent behaviors be controlled to yield the reproducibility we observe in organisms? Is there a bijective mapping between cell states and whole-organism outcomes that allows collectivity to be encoded? If not, then what exactly is being selected through evolution to give rise to complex multicellular life?

In this talk, I will first provide an overview of some of the most important findings in the field of collective intelligence and the related fields of social learning, wisdom of crowds, collective problem solving, group decision making, belief dynamics, and cultural evolution. I will then introduce the framework of collective adaptation and present ongoing empirical and modeling work on how collectives learn to adjust their cognitions and social networks in response to changing environments.

The neural crest is a highly invasive, multipotent embryonic cell population common to all vertebrates. Neural crest cells migrate all along the anteroposterior axis of the vertebrate embryos, crossing complex microenvironments during their journey and eventually halting their migration to give rise to a variety of derivatives. Considerable progress has been made in recent years in our understanding of the cell and mechanobiology-of-tissue-morphogenesis-and underlying collective cell migration of cranial neural crest cells. On the other hand, the extracellular environment trunk neural crest traverse in vivo is radically different from that experienced by cranial neural crest cells. I will present on overview of cranial and trunk neural crest collective cell migration under the lens of the complex interaction of this extraordinary cell population with its tissue environment.

The origin of multicellularity was one of the most significant innovations in the history of life. Our understanding of the evolutionary processes underlying this transition remains limited, however, mainly because extant multicellular lineages are ancient and most transitional forms have been lost to extinction. We bridge this knowledge gap by evolving novel multicellularity in the lab, using the 'snowflake yeast' model system. In this talk, I'll focus on our ongoing Multicellularity Long-Term Evolution Experiment (MuLTEE), in which we've put snowflake yeast through ~10,000 generations of selection for larger size and faster growth. We will examine key steps in the evolution of multicellularity, namely how multicellular traits arise and become heritable, how simple multicellular bodies evolve to become radically stronger and tougher, how cells divide labor through differentiation, and how groups overcome diffusion limitation by generating rapid hydrodynamic flows. Overall, our approach allows us to examine how simple groups of cells can evolve to become increasingly integrated and organismal, providing novel insight into this major evolutionary transition.

Collective behavior is widespread in animal groups, ranging from the coordinated movements of flocks of birds and swarms of insects to the more complex structures of social species. In many cases, such behavior is self-organized, i.e., it is not driven by external factors or leaders, but it is uniquely determined by the mutual interactions between the individuals partaking in the group. There are several aspects that have intrigued multidisciplinary interest in this phenomenon, from the sensory bases of fast responses and local interaction rules to the emergence—via the full interaction network—of global coordination on the large scales. In this section, we will explore several of these fascinating questions. When groups are very large, hundreds to thousands of individuals, their collective properties obey well-defined statistical laws. The mechanistic process of group formation resembles, in this case, the physics of strongly interacting systems. A physics-based approach can therefore provide a powerful framework for data analysis and theoretical modelling. In the second part of my talk, I will discuss how we used such an approach to investigate natural flocks and swarms and how we developed experimentally based theories of their collective behavior. Finally, I will focus on the role of behavioral inertia and system size in determining different regimes of collective coordination and response.

Many groups rely on division of labour between group members to function. Division of labour, in turn, requires stable behavioural variation between group members. We investigated how behavioural variation is generated and modulated by the social environment in an experimentally accessible social insect, the clonal raider ant Ooceraea biroi. We find that increases in colony size can generate a rudimentary division of labour among otherwise identical workers. We then show how different sources of heterogeneity in group composition (e.g. genetic, demographic) have distinct effects on behaviour—ranging from behavioural convergence to behavioural divergence between behavioural types—and evaluate these results against the predictions of a widely used model for self-organised division of labour in social insects. Finally, we are collaborating with chemists to uncover some of the chemical bases of division of labour and cooperative behaviour in the clonal raider ant. I will highlight recent progress in identifying pheromones and characterising their social function, to shed light on the molecular mechanisms that regulate ant sociality.

In this talk, I will present recent work on how human and non-human collectives adapt to changing environments. In fish, I will present work in which we manipulate group composition and resource abundance of fish shoals in the wild, to study their causal role in shaping social network dynamics and foraging success. In humans, I will present work which integrates high-precision GPS tracking and video footage from large-scale foraging competitions with cognitive-computational modeling and agent-based simulations to uncover the decision-making mechanisms underlying human social foraging in the real world.

Microbial communities underpin nearly every ecosystem on Earth, from the open ocean to the human gut. They drive key biogeochemical cycles and affect the health of hosts and environments alike. Understanding these communities is challenging because they are extraordinarily diverse and dynamic. In the first part of my talk, I will give a general introduction to microbial communities – why they matter and how we think they work. I will argue that a central challenge in microbial ecology is connecting two very different kinds of knowledge: the detailed mechanistic understanding we have of a few model species, and the large-scale, sequence-based descriptions we now have of natural communities that rarely contain those model species. In the second part, I will show how my own research addresses this challenge by identifying simplifying principles for marine bacteria and their communities. Focusing on the important polysaccharide chitin, we found that the bacterial members of polysaccharide-degrading communities can be described in three stably coexisting functional groups, which interact by dynamically exchanging metabolites. To dive deeper into these metabolic strategies, we used high-throughput metabolic profiling and comparative genomics to show that the vast diversity of heterotrophic bacteria can be captured by a simple dichotomy: a preference for consuming sugars versus amino and organic acids. This preference is encoded in their genomes, enabling us to make predictions about the metabolic strategies underpinning complex communities from sequencing data. Together, these results illustrate how trait-based frameworks can bridge scales and enable more predictive, theory-driven approaches to microbial community ecology.

Collective behaviors, like those of ants, birds, and bacteria, inspire us with the promise of more immense achievements with fewer resources, and understanding these behaviors is vital in comprehending the world around us. Further, bacterial communities are dynamic societies where microbes communicate cooperatively and antagonistically with siblings and non-siblings. Individual bacteria must navigate the complexities of these interactions even as the whole population expands. In this seminar, I will discuss how bacteria use a local sense of identity to assemble and move as a community. Our model organism, Proteus mirabilis, lives in human and animal intestines and the environment and can cause disease after moving to the bladder. Individual cells move on the scale of micrometers per second; populations swarm on the order of millimeters per hour. Our data shows how P. mirabilis communicates identity between cells and how this identity-based signaling regulates cell development and population-wide swarming. Our research addresses how an organism's identity, communication, and local environment influence collective behaviors.

The gut microbiota is an important host-associated microbial community, but what drives community assembly and dynamics in the gut is still not clear. We have analyzed the spatial distribution of bacteria in the gut of mice harboring a simplified microbiota, and found that bacteria preferentially cluster close to cells of the same species. We found that this is likely because microbial growth in the matrix of gut content leads to microcolony formation: due to its physical properties, gut content provides a stable matrix when undisturbed, but behaves more liquid-like when the gut walls apply force during a contraction. This spatial structure emerging from microbial activity can have important consequences. Depending on substrate availability and total microbial biomass, transient spatial structure can alter selection in such a system, which can change from favoring higher growth rate to a regime where metabolic efficiency is favored. Our findings offer insights into ecological and evolutionary forces at play in the gut, and enhance our understanding of how the host controls microbiota function through gut contractions and food intake.

Collective behavior operates as a distributed system without central control, using networks of interactions that in the aggregate allow the system to adjust to the current situation.. Collective behavior is extremely diverse. I will suggest hypotheses for how ecology shapes the evolution of collective behavior so that the dynamics of behavior, in rate, feedback regime and modularity of interaction networks, fits the dynamics of the environment. As examples I will discuss the regulation of foraging behavior in two ant species, harvester ants in the desert and turtle ants in the tropical forest. Harvester ant colonies in the desert, in a stable but harsh environment, regulate foraging activity slowly, using centralized information flow with low modularity, and feedback in which the default is not to forage so stimulation is needed to activate foraging. Turtle ants form trail networks in the canopy of the tropical forest. In an unstable but humid environment, where activity is easy, the trail is regulated locally depending on the physical configuration of each node in the vegetation, and the ants use highly modular search that fits the modular distribution of resources. The feedback regime is set with the default to go unless inhibited. The trail network can adjust to changing conditions and resources. These examples point to general trends in how collective behavior evolves in particular environments to respond to changing conditions.

Human cooperation has always been underpinned by shared beliefs: mythologies, ideologies, and cultural narratives. These create a common ground among diverse individuals. While traditional views hold that these narratives must carry explicit moral imperatives to foster prosocial behaviour, we demonstrate that even arbitrary beliefs can effectively catalyse cooperation. Using evolutionary game dynamics, we reveal how these beliefs operate as coordination devices, fostering trust by aligning individual actions toward shared goals. Such narratives, even when morally neutral, transform self-interested actors into a cohesive group, suggesting that the power of collective imagination is rooted first in its ability to unite and, perhaps later, define morality. Socially structured communities with dense clusters only accelerate the spread of trust and collective action. These insights suggest that narrative and social connectivity are vital to sustaining cooperation, reflecting a deeply ingrained human tendency to seek common ground through shared stories.

The lecture will provide a general overview of collective behavior and collective intelligence in biological systems and the relationships between these concepts. It will discuss the mechanistic aspects of group living, in particular, those that lead to self-organization and the emergence of complex, large-scale collective behaviors. It will also review the conditions under which group behaviors can become intelligent, or lead to collective failure. The lecture will be accompanied by a discussion of two papers that both invite a reflection on the power and limitations of the reductionist approach in the field of collective behavior, and in science in general.