Matti Gralka

Mechanical interactions in bacterial colonies and the surfing probability of beneficial mutations

Bacterial conglomerates such as biofilms and microcolonies are ubiquitous in nature and play an important role in industry and medicine. In contrast to well-mixed cultures routinely used in microbial research, bacteria in a microcolony interact mechanically with one another and with the substrate to which they are attached. Here, we use a computer model of a microbial colony of rod-shaped cells to investigate how physical interactions between cells determine their motion in the colony and how this affects biological evolution. We show that the probability that a faster-growing mutant ‘surfs’ at the colonys frontier and creates a macroscopic sector depends on physical properties of cells (shape, elasticity and friction). Although all these factors contribute to the surfing probability in seemingly different ways, their effects can be summarized by two summary statistics that characterize the front roughness and cell alignment. Our predictions are confirmed by experiments in which we measure the surfing probability for colonies of different front roughness. Our results show that physical interactions between bacterial cells play an important role in biological evolution of new traits, and suggest that these interactions may be relevant to processes such as de novo evolution of antibiotic resistance.

Excess of mutational jackpot events in expanding populations revealed by spatial Luria–Delbrück experiments

The genetic diversity of growing cellular populations, such as biofilms, solid tumours or developing embryos, is thought to be dominated by rare, exceptionally large mutant clones. Yet, the emergence of these mutational jackpot events is only understood in well-mixed populations, where they stem from mutations that arise during the first few cell divisions. To study jackpot events in spatially structured populations, we track mutant clones in microbial populations using fluorescence microscopy and population sequencing. High-frequency mutations are found to be massively enriched in microbial colonies compared with well-shaken liquid cultures, as a result of late-occurring mutations surfing at the edge of range expansions. Thus, jackpot events can be generated not only when mutations arise early but also when they occur at favourable locations, which exacerbates their role in adaptation and disease. In particular, because spatial competition with the wild type keeps most mutant clones in a quiescent state, strong selection pressures that kill the wild type promote drug resistance.

Collective motion conceals fitness differences in crowded cellular populations

Many cellular populations are tightly-packed, for example microbial colonies and biofilms [39, 10, 41], or tissues and tumors in multi-cellular organisms [11, 29]. Movement of one cell inside such crowded assemblages requires movement of others, so that cell displacements are correlated over many cell diameters [28, 6, 31]. Whenever movement is important for survival or growth [15, 34, 38, 9], such correlated rearrangements could couple the evolutionary fate of different lineages. Yet, little is known about the interplay between mechanical stresses and evolution in dense cellular populations. Here, by tracking deleterious mutations at the expanding edge of yeast colonies, we show that crowding-induced collective motion prevents costly mutations from being weeded out rapidly. Joint pushing by neighboring cells generates correlated movements that suppress the differential displacements required for selection to act. Such mechanical screening of fitness differences allows the mutants to leave more descendants than expected under non-mechanical models, thereby increasing their chance for evolutionary rescue [2, 5]. Our work suggests that mechanical interactions generally influence evolutionary outcomes in crowded cellular populations, which has to be considered when modeling drug resistance or cancer evolution [1, 22, 34, 30, 36, 42].

Emergence of evolutionary driving forces in pattern-forming microbial populations

Evolutionary dynamics are controlled by a number of driving forces, such as natural selection, random genetic drift and dispersal. In this perspective article, we aim to emphasize that these forces act at the population level, and that it is a challenge to understand how they emerge from the stochastic and deterministic behaviour of individual cells. Even the most basic steric interactions between neighbouring cells can couple evolutionary outcomes of otherwise unrelated individuals, thereby weakening natural selection and enhancing random genetic drift. Using microbial examples of varying degrees of complexity, we demonstrate how strongly cell–cell interactions influence evolutionary dynamics, especially in pattern-forming systems. As pattern formation itself is subject to evolution, we propose to study the feedback between pattern formation and evolutionary dynamics, which could be key to predicting and potentially steering evolutionary processes. Such an effort requires extending the systems biology approach from the cellular to the population scale. This article is part of the theme issue ‘Self-organization in cell biology’.

Convection shapes the trade-off between antibiotic efficacy and the selection for resistance in spatial gradients

Since penicillin was discovered about 90 years ago, we have become used to using drugs to eradicate unwanted pathogenic cells. However, using drugs to kill bacteria, viruses or cancer cells has the serious side effect of selecting for mutant types that survive the drug attack. A crucial question therefore is how one could eradicate as many cells as possible for a given acceptable risk of drug resistance evolution. We address this general question in a model of drug resistance evolution in spatial drug gradients, which recent experiments and theories have suggested as key drivers of drug resistance. Importantly, our model takes into account the influence of convection, resulting for instance from blood flow. Using stochastic simulations, we study the fates of individual resistance mutations and quantify the trade-off between the killing of wild-type cells and the rise of resistance mutations: shallow gradients and convection into the antibiotic region promote wild-type death, at the cost of increasing the establishment probability of resistance mutations. We can explain these observed trends by modeling the adaptation process as a branching random walk. Our analysis reveals that the trade-off between death and adaptation depends on the relative length scales of the spatial drug gradient and random dispersal, and the strength of convection. Our results show that convection can have a momentous effect on the rate of establishment of new mutations, and may heavily impact the efficiency of antibiotic treatment.

Watching Populations Melt Down

One of the curious features ofDarwinian Evolution is that it requireserrors to be made during genome repli-cation.Otherwise,beneficialmutationscould not occur and adaptation wouldarrest. Not surprisingly, however,random DNA copy errors usually donot lead to improvement—most muta-tions are deleterious or have little ef-fect (1). Because, as far as we know,evolution has not found away to selec-tively boost beneficial mutations, onewonders how large replication errorrates could possibly be without over-whelming the population with delete-rious mutations (2). This question ofmaximal sustainable mutation rateshas fascinated theoretical evolutionarybiologists for decades (2,3), yetexperimental results are scarce. Now,Max Lavrentovich (a theorist), MaryWahl (an experimenter), and theircolleagues (4) describe an elegantway to watch microbial populationson the verge of succumbing to delete-rious mutants.The simplest model for the trade-off between natural selection anddeleterious mutations is illustrated ina two-state population model inFig. 1. One-way mutations occurringat rate m per generation supply acontinuous flux from the wild-type tothe mutant type. This flux is compen-sated by the wild-type growing 1 þ stimes faster than the mutant type. Asa consequence, both types reach ‘‘mu-tation-selection balance’’ when thefraction of the mutant type is m/s (5).Hence, if the rate of deleterious muta-tions is larger than their typical effect,the wild-type goes extinct and the mu-tants take over. If this process con-tinues due to further deleteriousmutations, the population is at risk ofcontinuously accumulating deleteriousmutations in a phenomenon called‘‘mutational meltdown’’ (3) or ‘‘errorcatastrophe’’ (2) (for a discussion ofthese two terms and their differences,see Wilke (6)). Obviously, then, natureneeds to ensure that mutation rates donot exceed the selective disadvantageof typical mutations to avoid thecomplete loss of the wild-type. Indeed,sophisticated error correction mecha-nisms are in place, which keep muta-tion rates below 10

Excess of mutational jackpot events in growing populations due to gene surfing

One of the hallmarks of spontaneous mutations in growing populations is the emergence of mutational jackpot events - large mutant clones arising from mutations that by chance occur early in the development of a cellular population so that their progenitors benefit from prolonged growth. Due to their sheer size, these jackpot events, first discovered by Luria and Delbrück [1], are thought to have momentous roles in short-term evolutionary processes, including the adaptation from standing variation [2–4], evolutionary rescue [5], drug resistance evolution [6–10], and the somatic evolution of genetic diseases [11, 12]. However, because the emergence of jackpot events has been understood only in uniformly growing populations [1, 10, 13], it is currently impossible to predict their impact on the evolution of many naturally structured populations. To study jackpot events in spatially structured populations, we tracked mutant clones in microbial populations using fluorescent microscopy and population sequencing. High-frequency mutations were massively enriched in microbial colonies compared to well-shaken liquid cultures, as a result of late-occurring mutations surfing at the edge of range expansions [14–16]. We provide a mathematical theory that explains the observed excess of jackpot events and predicts their role in promoting rare evolutionary outcomes. In particular, we show that resistant clones generated by surfing can become unleashed under high selection pressures, and thus represent a drug resistance hazard for high-dose drug treatments. An excess of mutational jackpot events is shown to be a general consequence of non-uniform growth and, therefore, could be relevant to the mutational load of developing biofilm communities, solid tumors and multi-cellular organisms.