Biology subjects

Vroomans, R. M.

Publications and source records attributed to Vroomans, R. M..

5 recordsLinked to original sources

bioRxiv2026

Differentiable Vertex Model: Exploring Gradient-Based Optimization for Tissue Morphogenesis

Vertex models are widely used within the field of developmental biology to study tissue morphogenesis. These models are well-suited for modeling deformation at the cellular level where movement is driven by local forces. However, understanding how these microscopic movements coordinate to yield macroscopic phenomena such as the shapes of entire tissues remains a challenge. Here we study a top-down approach using differentiable programming on a simplified vertex model of a laminar tissue, and investigate whether the attributes of individual cells can be tuned to make the mesh as a whole acquire a predefined shape. We let the mesh evolve according to simple rules defined by the input to each polygon, and evaluate the resulting shape against a target boundary. Additionally, we show how the high degeneracy of the output can be reduced by constraining the polygon distributions: first, by adding simple penalties on tissue-wide attributes; and second, by dividing the tissue into regions, within which we bias the attributes toward characteristic values. Our study shows how a simple vertex model can be combined with differentiable programming to model developing tissues, and provides insight into the way individual cells must coordinate to yield macroscopic phenomena such as pre-programmed shapes.

biophysics↗

bioRxiv2025

Evolution of reproduction driven by ecology at the onset of multicellularity

At the origin of multicellularity, genetic programs used by single-celled organisms to interact with their environment become organised into a developmental program. While previous work has clarified the selective advantages of simple multicellularity, the origin of development remains unclear. Here, we investigate the ecological origin of a fundamental developmental process -- multicellular reproduction -- using a computational model where cells forage in a structured environment, and evolve adhesion and regulated environmental responses. Multicellular modes of reproduction are not pre-specified in the model, but must emerge from the evolving dynamics under ecological selection. We find that distinct multicellular life cycles evolve depending on the spatial distribution of resources. Among these are life cycles with a single-celled propagule phase the most prevalent reproductive strategy in multicellular life that evolves as a dispersal strategy to reach new resources. These propagules form through the activation of molecular programs co-opted from the unicellular ancestor, where they mediated interactions with neighbours in its ecological context. Once propagules evolve, multicellular lineages can invade environments previously dominated by unicellular competitors, showing this strategy is adaptive beyond the conditions that permit its evolution. Altogether, our results show that developmental regulation evolves through co-option of ecological interactions during the transition to multicellularity. Significance statementReproduction is a universal feature of life. Yet, the evolution of multicellularity transformed it fundamentally: while single-celled organisms reproduce via cell division, reproduction in multicellular organisms is a complex process involving the coordination of many cells. How these new forms of multicellular reproduction first evolved is currently unknown. Using a computational model, we study how group reproduction emerges from the collective dynamics of individual cells. The model shows that unicellular ancestral life cycles can be repurposed as propagules used for reproduction in multicellular species, suggesting that genetic co-option is a key mechanism through which early development evolves.

evolutionary biology↗

bioRxiv2025

The Variability of Evolvability: Properties of Dynamic Fitness Landscapes Determine How Phenotypic Variability Evolves

The magnitude and shape of phenotypic variation depends on properties of the genotype-to-phenotype (GP) map, which itself can evolve over time. The evolution of GP maps is particularly interesting in variable environments, as GP maps can evolve to bias variation in the direction of past selection, increasing the evolvability of the population over time. However, the degree and manner in which environmental variation shapes GP maps and influences evolutionary dynamics may depend on properties of the fitness landscape. To explore how evolutionary dynamics are affected by variable environments across a wide range of different pairs of fitness landscapes, we evolved GP maps to produce spatial-temporal gene expression patterns that matched two-dimensional patterns generated by different elementary cellular automata (CA) rules. We found remarkable variation in how populations evolved in variable environments. In some cases, changing the environment helped populations find higher fitness peaks; in others, it hindered them. The evolution of evolvability also depended on the fitness landscape pair. In some experiments, the ability to generate adaptive phenotypic variation upon environment change increased over time, while in some others, populations found shared areas between fitness landscapes. On the other hand, environmental variability consistently resulted in higher fitness landscape exploration, average fitness and mutational robustness compared to evolution in static environments, which we hypothesize are tightly connected. In conclusion, work presented here sheds light on important general consequences of environmental variability, while also demonstrating dependency on properties of fitness landscapes, which future research on the evolution of evolvability should consider. Significance statementThe speed and direction of evolution depend on the availability of phenotypic variation. Genotype-to-phenotype maps can over time bias phenotypic variability to more readily produce alternative adaptive phenotypes in fluctuating environments. However, because properties of the fitness landscapes influence evolutionary dynamics, it remains unclear which previously observed dynamics reflect general effects of environmental variability and which are specific to the pair of landscapes used. We found that the height of the fitness peaks discovered, and how the populations became more evolvable, significantly differed across landscape pairs. In contrast, environmental variability consistently increased average fitness and mutational robustness. Thus, future research investigating the inherent consequences of frequent environmental change should be done on a range of dynamic landscapes.

evolutionary biology↗

bioRxiv2022

Evolution of selfish multicellularity: collective organisation of individual spatio-temporal regulatory strategies

BackgroundThe unicellular ancestors of modern-day multicellular organisms were remarkably complex. They had an extensive set of regulatory and signalling genes, an intricate life cycle and could change their behaviour in response to environmental changes. At the transition to multicellularity, some of these behaviours were co-opted to organise the development of the nascent multicellular organism. Here, we focus on the transition to multicellularity before the evolution of stable cell differentiation, to reveal how the emergence of clusters affects the evolution of cell behaviour. ResultsWe construct a computational model of a population of cells that can evolve the regulation of their behavioural state - either division or migration - in a unicellular or multicellular context. They compete for reproduction and for resources to survive in a seasonally changing environment. We find that the evolution of multicellularity strongly determines the co-evolution of cell behaviour, by altering the competition dynamics between cells. When adhesion cannot evolve, cells compete for survival by rapidly migrating towards resources before dividing. When adhesion evolves, emergent collective migration alleviates the pressure on individual cells to reach resources. This allows cells to selfishly maximise replication. Migrating adhesive clusters display striking patterns of spatio-temporal cell state changes that visually resemble animal development. ConclusionsOur model demonstrates how emergent selection pressures at the onset of multicellularity can drive the evolution of cellular behaviour to give rise to developmental patterns.

evolutionary biology↗

bioRxiv2021

Evolution of genome fragility enables microbial division of labor

Division of labor can evolve when social groups benefit from the functional specialization of its members. Recently, a novel means of coordinating division of labor was found in the antibiotic-producing bacterium Streptomyces coelicolor, where functionally specialized cells are generated through large-scale genomic re-organization. Here, we investigate how the evolution of a genome architecture enables such mutation-driven division of labor, using a multi-scale mathematical model of bacterial evolution. We let bacteria compete on the basis of their antibiotic production and growth rate in a spatially structured environment. Bacterial behavior is determined by the structure and composition of their genome, which encodes antibiotics, growth-promoting genes and fragile genomic loci that can induce chromosomal deletions. We find that a genomic organization evolves that partitions growth-promoting genes and antibiotic-coding genes to distinct parts of the genome, separated by fragile genomic loci. Mutations caused by these fragile sites mostly delete growth-promoting genes, generating antibiotic-producing mutants from non-producing (and weakly-producing) progenitors, in agreement with experimental observations. Mutants protect their colony from competitors but are themselves unable to replicate. We further show that this division of labor enhances the local competition between colonies by promoting antibiotic diversity. These results show that genomic organization can co-evolve with genomic instabilities to enable reproductive division of labor. Motivation of current workDivision of labor can evolve if trade-offs are present between different traits. To organize a division of labor, the genome architecture must evolve to enable differentiated cellular phenotypes. Cell differentiation may be coordinated through gene regulation, as occurs during embryonic development. Alternatively, when mutation rates are high, mutations themselves can guide cell and functional differentiation; however, how this evolves and is organized at the genome level remains unclear. Here, using a model of antibiotic-producing bacteria based on multicellular Streptomyces, we show that if antibiotic production trades off with replication, genome architecture can evolve to support a mutation-driven division of labor. These results are consistent with recent experimental observations and may underlie division of labor in many bacterial groups.

evolutionary biology↗