Maxime Deforet

Emergence of collective modes and tri-dimensional structures from epithelial confinement

Many in vivo processes, including morphogenesis or tumour maturation, involve small populations of cells within a spatially restricted region. However, the basic mechanisms underlying the dynamics of confined cell assemblies remain largely to be deciphered and would greatly benefit from well-controlled in vitro experiments. Here we show that confluent epithelial cells cultured on finite population-sized domains, exhibit collective low-frequency radial displacement modes as well as stochastic global rotation reversals. A simple mathematical model, in which cells are described as persistent random walkers that adapt their motion to that of their neighbours, captures the essential characteristics of these breathing oscillations. As these epithelia mature, a tri-dimensional peripheral cell cord develops at the domain edge by differential extrusion, as a result of the additional degrees of freedom of the border cells. These results demonstrate that epithelial confinement alone can induce morphogenesis-like processes including spontaneous collective pulsations and transition from 2D to 3D.

Emergence of spatial structure in the tumor microenvironment due to the Warburg effect

Significance Cancer cells undergo dramatic metabolic alterations, such as the Warburg effect where glucose is consumed independently of oxygen, leading to high lactic acid production. Although these alterations can give growth advantages to cancer cells, they have a profound effect in the extracellular environment, and thus it is not clear how they affect healthy cells. Here we show that lactic acid accumulation can impair the survival of tumor-associated macrophages. Using a multidisciplinary combination of computational and experimental methods, we show that this decreased survival can lead to spatial patterns of macrophage localization that resemble how tumor-associated macrophages distribute in real tumors. Spatial patterns can potentiate tumor growth, and thus understanding how they are formed may bring therapeutic insights. Drastic metabolic alterations, such as the Warburg effect, are found in most if not all types of malignant tumors. Emerging evidence shows that cancer cells benefit from these alterations, but little is known about how they affect noncancerous stromal cells within the tumor microenvironment. Here we show that cancer cells are better adapted to metabolic changes in the microenvironment, leading to the emergence of spatial structure. A clear example of tumor spatial structure is the localization of tumor-associated macrophages (TAMs), one of the most common stromal cell types found in tumors. TAMs are enriched in well-perfused areas, such as perivascular and cortical regions, where they are known to potentiate tumor growth and invasion. However, the mechanisms of TAM localization are not completely understood. Computational modeling predicts that gradients—of nutrients, gases, and metabolic by-products such as lactate—emerge due to altered cell metabolism within poorly perfused tumors, creating ischemic regions of the tumor microenvironment where TAMs struggle to survive. We tested our modeling prediction in a coculture system that mimics the tumor microenvironment. Using this experimental approach, we showed that a combination of metabolite gradients and differential sensitivity to lactic acid is sufficient for the emergence of macrophage localization patterns in vitro. This suggests that cancer metabolic changes create a microenvironment where tumor cells thrive over other cells. Understanding differences in tumor-stroma sensitivity to these alterations may open therapeutic avenues against cancer.

Metabolic origins of spatial organization in the tumor microenvironment

Significance Cancers appear as disordered mixtures of different cells, which is partly why they are hard to treat. We show here that despite this chaos, tumors show local organization that emerges from cellular processes common to most cancers: the altered metabolism of cancer cells and the interactions with stromal cells in the tumor microenvironment. With a multidisciplinary approach combining experiments and computer simulations we revealed that the metabolic activity of cancer cells produces gradients of nutrients and metabolic waste products that act as signals that cells use to know their position with respect to blood vessels. This positional information orchestrates a modular organization of tumor and stromal cells that resembles embryonic organization, which we could exploit as a therapeutic target. The genetic and phenotypic diversity of cells within tumors is a major obstacle for cancer treatment. Because of the stochastic nature of genetic alterations, this intratumoral heterogeneity is often viewed as chaotic. Here we show that the altered metabolism of cancer cells creates predictable gradients of extracellular metabolites that orchestrate the phenotypic diversity of cells in the tumor microenvironment. Combining experiments and mathematical modeling, we show that metabolites consumed and secreted within the tumor microenvironment induce tumor-associated macrophages (TAMs) to differentiate into distinct subpopulations according to local levels of ischemia and their position relative to the vasculature. TAMs integrate levels of hypoxia and lactate into progressive activation of MAPK signaling that induce predictable spatial patterns of gene expression, such as stripes of macrophages expressing arginase 1 (ARG1) and mannose receptor, C type 1 (MRC1). These phenotypic changes are functionally relevant as ischemic macrophages triggered tube-like morphogenesis in neighboring endothelial cells that could restore blood perfusion in nutrient-deprived regions where angiogenic resources are most needed. We propose that gradients of extracellular metabolites act as tumor morphogens that impose order within the microenvironment, much like signaling molecules convey positional information to organize embryonic tissues. Unearthing embryology-like processes in tumors may allow us to control organ-like tumor features such as tissue repair and revascularization and treat intratumoral heterogeneity.

Automated velocity mapping of migrating cell populations (AVeMap)

Characterizing the migration of a population of cells remains laborious and somewhat subjective. Advances in genetics and robotics allow researchers to perform many experiments in parallel, but analyzing the large sets of data remains a bottleneck. Here we describe a rapid, fully automated correlation-based method for cell migration analysis, compatible with standard video microscopy. This method allows for the computation of quantitative migration parameters via an extensive dynamic mapping of cell displacements.

Integration of Metabolic and Quorum Sensing Signals Governing the Decision to Cooperate in a Bacterial Social Trait.

Many unicellular organisms live in multicellular communities that rely on cooperation between cells. However, cooperative traits are vulnerable to exploitation by non-cooperators (cheaters). We expand our understanding of the molecular mechanisms that allow multicellular systems to remain robust in the face of cheating by dissecting the dynamic regulation of cooperative rhamnolipids required for swarming in Pseudomonas aeruginosa. We combine mathematical modeling and experiments to quantitatively characterize the integration of metabolic and population density signals (quorum sensing) governing expression of the rhamnolipid synthesis operon rhlAB. The combined computational/experimental analysis reveals that when nutrients are abundant, rhlAB promoter activity increases gradually in a density dependent way. When growth slows down due to nutrient limitation, rhlAB promoter activity can stop abruptly, decrease gradually or even increase depending on whether the growth-limiting nutrient is the carbon source, nitrogen source or iron. Starvation by specific nutrients drives growth on intracellular nutrient pools as well as the qualitative rhlAB promoter response, which itself is modulated by quorum sensing. Our quantitative analysis suggests a supply-driven activation that integrates metabolic prudence with quorum sensing in a non-digital manner and allows P. aeruginosa cells to invest in cooperation only when the population size is large enough (quorum sensing) and individual cells have enough metabolic resources to do so (metabolic prudence). Thus, the quantitative description of rhlAB regulatory dynamics brings a greater understating to the regulation required to make swarming cooperation stable.

Tissue fusion over nonadhering surfaces

Significance Tissue fusion is a frequent and important event in embryonic development during which two facing identical tissues meet and bridge collectively over a gap before merging into a continuous structure. Illustrations of tissue fusion include the formation of the palate or epithelial wound healing. In vivo fusion events, particularly in embryonic development, often involve the purse-string contraction of a pluricellular actomyosin cable present at the free edge. By studying the fusion of a monolayer over imprinted nonadherent domains, we provide evidence and characterize the purse-string mechanism in the situation where cells do not develop adhesions with their underlying substrate. A model that also involves active epithelial fluctuations describes well the experimental observations. Tissue fusion eliminates physical voids in a tissue to form a continuous structure and is central to many processes in development and repair. Fusion events in vivo, particularly in embryonic development, often involve the purse-string contraction of a pluricellular actomyosin cable at the free edge. However, in vitro, adhesion of the cells to their substrate favors a closure mechanism mediated by lamellipodial protrusions, which has prevented a systematic study of the purse-string mechanism. Here, we show that monolayers can cover well-controlled mesoscopic nonadherent areas much larger than a cell size by purse-string closure and that active epithelial fluctuations are required for this process. We have formulated a simple stochastic model that includes purse-string contractility, tissue fluctuations, and effective friction to qualitatively and quantitatively account for the dynamics of closure. Our data suggest that, in vivo, tissue fusion adapts to the local environment by coordinating lamellipodial protrusions and purse-string contractions.

Hyperswarming adaptations in a bacterium improve collective motility without enhancing single cell motility

Pseudomonas aeruginosa is a monoflagellated bacterium that can use its single polar flagellum to swim through liquids and move collectively over semisolid surfaces, a behavior called swarming. Previous studies have shown that experimental evolution in swarming colonies leads to the selection of hyperswarming bacteria with multiple flagella. Here we show that the advantage of such hyperswarmer mutants cannot be explained simply by an increase in the raw swimming speed of individual bacteria in liquids. Cell tracking of time-lapse microscopy to quantify single-cell swimming patterns reveals that both wild-type and hyperswarmers alternate between forward and backward runs, rather than doing the run-and-tumble characteristic of enteric bacteria such as E. coli. High-throughput measurement of swimming speeds reveals that hyperswarmers do not swim faster than wild-type in liquid. Wild-type reverses swimming direction in sharp turns without a significant impact on its speed, whereas multiflagellated hyperswarmers tend to alternate fast and slow runs and have wider turning angles. Nonetheless, macroscopic measurement of swimming and swarming speed in colonies shows that hyperswarmers expand faster than wild-type on surfaces and through soft agar matrices. A mathematical model explains how wider turning angles lead to faster spreading when swimming through agar. Our study describes for the first time the swimming patterns in multiflagellated P. aeruginosa mutants and reveals that collective and individual motility in bacteria are not necessarily correlated. Understanding bacterial adaptations to surface motility, such as hyperswarming, requires a collective behavior approach.

A simple rule for the evolution of fast dispersal at the edge of expanding populations

Abstract Predicting evolution of expanding populations is critical to control biological threats such as invasive species and cancer metastasis. Expansion is primarily driven by reproduction and dispersal, but nature abounds with examples of evolution where organisms pay a reproductive cost to disperse faster. When does selection favor this ‘survival of the fastest?’ We searched for a simple rule, motivated by evolution experiments where swarming bacteria evolved into an hy-perswarmer mutant which disperses ∼ 100% faster but pays a growth cost of ∼ 10% to make many copies of its flagellum. We analyzed a two-species model based on the Fisher equation to explain this observation: the population expansion rate (v) results from an interplay of growth (r) and dispersal (D) and is independent of the carrying capacity: . A mutant can take over the edge only if its expansion rate (v2) exceeds the expansion rate of the established species’ (v1); this simple condition (v2 > v1) determines the maximum cost in slower growth that a faster mutant can pay and still be able to take over. Numerical simulations and time-course experiments where we tracked evolution by imaging bacteria suggest that our findings are general: less favorable conditions delay but do not entirely prevent the success of the fastest. Thus, the expansion rate defines a traveling wave fitness, which could be combined with trade-offs to predict evolution of expanding populations.Evolution by natural selection is commonly perceived as a process that favors those that replicate faster to leave more offspring; nature, however, seem to abound with examples where organisms forgo some replicative potential to disperse faster. When does selection favor invasion of the fastest? Motivated by evolution experiments with swarming bacteria we searched for a simple rule. In experiments, a fast hyperswarmer mutant that pays a reproductive cost to make many copies of its flagellum invades a population of mono-flagellated bacteria by reaching the expanding population edge; a two-species mathematical model explains that invasion of the edge occurs only if the invasive species’ expansion rate, v2, which results from the combination of the species growth rate and its dispersal speed (but not its carrying capacity), exceeds the established species’, v1. The simple rule that we derive, v2 > v1, appears to be general: less favorable initial conditions, such as smaller initial sizes and longer distances to the population edge, delay but do not entirely prevent invasion. Despite intricacies of the swarming system, experimental tests agree well with model predictions suggesting that the general theory should apply to other expanding populations with trade-offs between growth and dispersal, including non-native invasive species and cancer metastases.

Metabolism and the Evolution of Social Behavior

Abstract How does metabolism influence social behavior? This fundamental question at the interface of molecular biology and social evolution is hard to address with experiments in animals, and therefore, we turned to a simple microbial system: swarming in the bacterium Pseudomonas aeruginosa. Using genetic engineering, we excised a locus encoding a key metabolic regulator and disrupted P. aeruginosa’s metabolic prudence, the regulatory mechanism that controls expression of swarming public goods and protects this social behavior from exploitation by cheaters. Then, using experimental evolution, we followed the joint evolution of the genome, the metabolome and the social behavior as swarming re-evolved. New variants emerged spontaneously with mutations that reorganized the metabolome and compensated in distinct ways for the disrupted metabolic prudence. These experiments with a unicellular organism provide a detailed view of how metabolism—currency of all physiological processes—can determine the costs and benefits of a social behavior and ultimately influence how an organism behaves towards other organisms of the same species.