Abstracts

Bartlomiej Waclaw - Dioscuri Centre for Physics and Chemistry of Bacteria Warszawa and The University of Edinburgh

Substrate geometry affects population dynamics in a bacterial biofilm

Biofilms inhabit a range of environments, such as dental plaques or soil micropores, often characterized by intricate, non-even surfaces. However, the impact of surface irregularities on the population dynamics of biofilms remains elusive as most biofilm experiments are conducted on flat surfaces. Here, we show that the shape of the surface on which a biofilm grows influences genetic drift and selection within the biofilm. We culture E. coli biofilms in micro-wells with an undulating bottom surface and observe the emergence of clonal sectors whose size corresponds to that of the undulations, despite no physical barrier separating different areas of the biofilm. The sectors are remarkably stable over time and do not invade each other; we attribute this stability to the characteristics of the velocity field within the growing biofilm, which hinders mixing and clonal expansion. A microscopically-detailed computer model fully reproduces these findings and highlights the role of mechanical (physical) interactions such as adhesion and friction in microbial evolution. The model also predicts clonal expansion to be severely limited even for clones with a significant growth advantage - a finding which we subsequently confirm experimentally using a mixture of antibiotic-sensitive and antibiotic-resistant mutants in the presence of sub-lethal concentrations of the antibiotic rifampicin. The strong suppression of selection contrasts sharply with the behavior seen in bacterial colonies on agar commonly used to study range expansion and evolution in biofilms. Our results show that biofilm population dynamics can be controlled by patterning the surface, and demonstrate how a better understanding of the physics of bacterial growth can pave the way for new strategies in steering microbial evolution.

Witold Postek, Klaudia Staskiewicz, Elin Lilja, Bartlomiej Waclaw - Substrate geometry affects population dynamics in a bacterial biofilm - arXiv:2308.16046

Martina Dal Bello - Massachusetts Institute of Technology and Yale University

The distribution of fast and slow-growing bacteria changes predictably with seawater temperature and salinity

Identifying universal principles for how organismal processes scale up to determine community properties is central in ecology and microbiome research. Growth rates of individual bacteria strongly depend on environmental variables, with temperature generally increasing metabolic processes and growth rates up to an optimum and salinity decreasing the same processes once a critical salt concentration is crossed. Nevertheless, how individual responses to changes in salinity and temperature shape the outcome of species competition and the structure of bacterial communities is still unclear. Here we start by highlighting theoretical predictions of how changes in growth rates promoted by either temperature or salinity differentially modulate the impact of mortality on the abundance distribution of fast and slow growers. We then show that, in datasets of marine microbiomes collected along axes of temperature variation, increasing seawater temperatures universally favor slower-growing taxa. Finally, we use enriched marine bacterial cultures to demonstrate that increasing salinity favors instead faster-growing taxa. Our results offer a general framework to link changes in growth rates promoted by key environmental variables to the structure of bacterial communities.

Shiladitya Banerjee - Carnegie Mellon University

Gene Expression Tradeoffs Determine Bacterial Survival and Adaptation to Antibiotic Stress

To optimize their fitness, cells must respond efficiently to various stresses. This necessitates striking a balance between conserving resources for survival and allocating resources for growth and proliferation. The fundamental principles governing these tradeoffs is poorly understood. In this talk, I will discuss our recent study that introduced a quantitative framework for bacterial physiology that establishes a connection between the physiological state of cells and their survival outcomes in dynamic environments, particularly in the context of antibiotic exposure. Predicting bacterial survival responses to varying antibiotic doses proves challenging due to the profound influence of the physiological state on critical parameters, such as the minimum inhibitory concentration (MIC) and killing rates, even within an isogenic cell population. Our proposed quantitative model bridges the gap by linking extracellular antibiotic concentration and nutrient quality to intracellular damage accumulation and gene expression. This framework allows us to predict and explain the control of cellular growth rate, death rate, MIC, and survival fraction in a wide range of time-varying environments. Surprisingly, our model reveals that cell death is rarely due to antibiotic levels being above the maximum physiological limit, but instead survival is limited by the inability to alter gene expression sufficiently quickly to transition to a less susceptible physiological state. Moreover, bacteria tend to overexpress stress response genes at the expense of reduced growth, conferring greater protection against further antibiotic exposure. This strategy is in contrast to those employed in different nutrient environments, in which bacteria allocate resources to maximize growth rate. This highlights an important tradeoff between the cellular capacity for growth and the ability to survive antibiotic exposure.

Minsu Kim - Emory University

Selective inheritance of phenotypic resistance to antibiotics in isogenic bacterial populations

Non-optimal antibiotic use, e.g., under- or over-treatment, is associated with severe side effects, e.g., treatment failure or emergence of superbugs. Although antibiotics have been used for several decades, there is a great deal of controversy regarding the optimal antibiotic treatment strategy. One major challenge in addressing this issue is that our quantitative understanding of bacterial response to antibiotics is limited. 

Previously, we showed that bactericidal drugs induce population fluctuations, leading to stochastic population dynamics. Detailed single-cell-level analyses of these fluctuations reveal that cell survival under antibiotic treatment is not random but depends on family relationship and age. This dependence leads to the enrichment of robust lineages through selective inheritance of resistance factors in an otherwise susceptible population. These findings establish the presence of ‘phenotypic resistance’ within a minority population and how it propagates through cell-to-cell heterogeneity.

Somenath Bakshi - Cambridge University

Connecting the dynamics of antimicrobial response across scales

The cellular physiology of microbes can vary significantly within a population, even when they are exposed to identical external conditions. Recent theoretical and experimental studies have shown that this diversity is crucial for population fitness and evolution. Our research focuses on understanding how this physiological heterogeneity impacts the response to antimicrobials at the cellular level and influences resistance evolution over extended periods.

To tackle this question, we have established an experimental framework to connect the single-cell level antimicrobial response of microbes with the short-term and long-term behaviours of their populations. Currently, we are employing this approach to analyse the extent of cellular heterogeneity and its role in shaping the population dynamics of microbial systems, specifically within the context of: 1) Heterogeneous response and recovery from antibiotic treatment, 2) Antibiotic persistence, and 3) The arms race between Bacteriophages and Bacteria.

In this presentation, I will describe the background and motivation for this approach, discuss the key challenges, outline the necessary technical advancements made in our lab, and illustrate its potential with selected key findings from the three research areas mentioned above.

Andrea Weisse - The University of Edinburgh

The role of RNA repair in transient resistance to translation-targeting antibiotics

RNA is susceptible to damage from internal and external factors. Given the integral role of RNA, its repair is essential for maintaining proper cell function. RNA repair has so far, however, received little attention compared to the widely studied repair of DNA, potentially due to the perception of RNA as a short-lived molecule for which repair is inessential. Yet, the most abundant types of RNA, namely rRNAs and tRNAs involved in translation, are long-lived, and unrepaired damage to them has the potential to severely impact cell physiology and growth. 

 A highly conserved RNA repair system, the Rtc system, maintains core RNA components of the translational apparatus. In bacteria, Rtc expression is induced upon exposure to translation-targeting antibiotics. Its expression enables cells to rescue growth conferring transient resistance to these antibiotics, but the mechanisms by which this resistance arises are largely unknown. 

 We developed a model of Rtc-regulated maintenance of long-lived RNAs that form part of the translational apparatus. We investigate the mechanistic action of Rtc leading to transient resistance and find that its regulatory structure robustly promotes bistability, giving rise to a resistant sub-population that can co-exist with non-expressing, susceptible cells. The finding suggests a complex response underlying Rtc-induced resistance with individual cell fates determining antibiotic efficacy. Analysing the molecular determinants that lead to growth rescue vs suppression, we identify components within the Rtc system that may be targeted to potentiate antibiotic effects, thus raising prospects of containing levels of resistance to a widely used class of antibiotics.  

Jordi van Gestel - EMBL Heidelberg

Evolution in a complex world: predator-prey interactions in the soil

Soils are a hotspot of microbial predation, with numerous bacterivorous protists scavenging for bacterial prey. Despite this predation pressure, most functional genomic studies on soil bacteria are performed in the absence of trophic interaction partners. This biases our view on the selection pressures that shape bacterial evolution. Here, we aim to overcome this bias by studying how, under predation, selection affects B. subtilis’ growth and survival. By screening thousands of genetic mutants with and without predation, we reveal that tens of different genes affect predation resistance, most of which have never been associated with predation before. We also show that mutations can rapidly emerge de novo and mostly occur in three loci only. These mutational hotspots either cause filamentation or biofilm formation and prevent protists from engulfing bacterial cells. Resistance however comes with a major cost. Mutants grow slower than susceptible cells and are rapidly replaced in the absence of predation. This strong antagonistic selection favors genetic regulation. Indeed, in one of the loci, we discovered a putative genetic switch that allows cells to switch back-and-forth between a slow-growing resistant state and a fast-grow susceptible state.

Luca Ciandrini - Montpellier University

Beyond ribo-centric cellular growth laws: The role of transcript abundance and protein turnover in shaping cellular physiology

Decades of experimental observations have underscored the critical role of ribosome quantities in governing cellular growth. These insights have led to the formulation of ribosome-centric “growth laws,” which emerge from mass conservation and biosynthetic flux balance, modulated by resource allocation shifts under varying conditions. However, it is increasingly evident that mRNA levels and RNA polymerase availability significantly impact growth in biologically relevant scenarios.

In this presentation, I will introduce a comprehensive transcription/translation gene expression model that integrates all these factors to explain observed growth rates. This model sheds light on how experimental growth laws arise from fundamental principles governing ribosome and RNA polymerase (RNAP) allocation. Specifically, the model captures the relationship between mRNA levels and growth rates, predicts the physiological cost of expressing unnecessary proteins, and provides insights into the response to transcription-inhibiting antibiotics.

If time permits, I will also delve into the essential role of protein turnover for a holistic understanding of ribosome allocation in slow-growing bacteria.