Pulses and delays, anticipation and memory: seeing bacterial stress responses from a single-cell perspective

Combining multiple stressors blocks bacterial migration and growth

In nature, organisms experience combinations of stressors. However, laboratory studies use batch cultures, which simplify reality and focus on population-level responses to individual stressors.1,2,3,4,5 In recent years, bacterial stress responses have been examined with single-cell resolution using microfluidics.6,7,8,9,10,11,12 Here, we use a microfluidic approach to simultaneously provide a physical stressor (shear flow) and a chemical stressor (H2O2) to the human pathogen Pseudomonas aeruginosa. By treating cells with levels of flow and H2O2 that commonly co-occur in human host tissues,13,14,15,16,17,18 we discover that previous reports significantly overestimate the H2O2 levels required to block bacterial growth. Specifically, we establish that flow increases H2O2 effectiveness 50-fold, explaining why previous studies lacking flow required much higher concentrations. Using natural H2O2 levels, we identify the core H2O2 regulon, characterize OxyR-mediated dynamic regulation, and demonstrate that multiple H2O2 scavenging systems have redundant roles. By examining single-cell behavior, we serendipitously discover that the combined effects of H2O2 and flow block pilus-driven surface migration. Thus, our results counter previous studies and reveal that natural levels of H2O2 and flow synergize to restrict bacterial motility and survival. By studying two stressors at once, our research highlights the limitations of oversimplifying nature and demonstrates that physical and chemical stress can combine to yield unpredictable effects.

Combining multiple stressors unexpectedly blocks bacterial migration and growth

In nature, organisms experience combinations of stressors. However, laboratory studies typically simplify reality and focus on the effects of an individual stressor. Here, we use a microfluidic approach to simultaneously provide a physical stressor (shear flow) and a chemical stressor (H 2 O 2 ) to the human pathogen Pseudomonas aeruginosa . By treating cells with levels of flow and H 2 O 2 that commonly co-occur in nature, we discover that previous reports significantly overestimate the H 2 O 2 levels required to block bacterial growth. Specifically, we establish that flow increases H 2 O 2 effectiveness 50-fold, explaining why previous studies lacking flow required much higher concentrations. Using natural H 2 O 2 levels, we identify the core H 2 O 2 regulon, characterize OxyR-mediated dynamic regulation, and dissect the redundant roles of multiple H 2 O 2 scavenging systems. By examining single-cell behavior, we serendipitously discover that the combined effects of H 2 O 2 and flow block pilus-driven surface migration. Thus, our results counter previous studies and reveal that natural levels of H 2 O 2 and flow synergize to restrict bacterial colonization and survival. By studying two stressors at once, our research highlights the limitations of oversimplifying nature and demonstrates that physical and chemical stress can combine to yield unpredictable effects.

Estimating mutation rates under heterogeneous stress responses

Exposure to environmental stressors, including certain antibiotics, induces stress responses in bacteria. Some of these responses increase mutagenesis and thus potentially accelerate resistance evolution. Many studies report increased mutation rates under stress, often using the standard experimental approach of fluctuation assays. However, single-cell studies have revealed that many stress responses are heterogeneously expressed in bacterial populations, which existing estimation methods have not yet addressed. We develop a population dynamic model that considers heterogeneous stress responses (subpopulations of cells with the response off or on) that impact both mutation rate and cell division rate, inspired by the DNA-damage response in Escherichia coli (SOS response). We derive the mutant count distribution arising in fluctuation assays under this model and then implement maximum likelihood estimation of the mutation-rate increase specifically associated with the expression of the stress response. Using simulated mutant count data, we show that our inference method allows for accurate and precise estimation of the mutation-rate increase, provided that this increase is sufficiently large and the induction of the response also reduces the division rate. Moreover, we find that in many cases, either heterogeneity in stress responses or mutant fitness costs could explain similar patterns in fluctuation assay data, suggesting that separate experiments would be required to identify the true underlying process. In cases where stress responses and mutation rates are heterogeneous, current methods still correctly infer the effective increase in population mean mutation rate, but we provide a novel method to infer distinct stress-induced mutation rates, which could be important for parameterising evolutionary models.

The dynamic-process characterization and prediction of synthetic gene circuits by dynamic delay model

Differential equation models are widely used to describe genetic regulations, predict multicomponent regulatory circuits, and provide quantitative insights. However, it is still challenging to quantitatively link the dynamic behaviors with measured parameters in synthetic circuits. Here, we propose a dynamic delay model (DDM) which includes two simple parts: the dynamic determining part and the doses-related steady-state-determining part. The dynamic determining part is usually supposed as the delay time but without a clear formula. For the first time, we give the detail formula of the dynamic determining function and provide a method for measuring all parameters of synthetic elements (include 8 activators and 5 repressors) by microfluidic system. Three synthetic circuits were built to show that the DDM can notably improve the prediction accuracy and can be used in various synthetic biology applications.

Microfluidic approaches in microbial ecology

Microbial life is at the heart of many diverse environments and regulates most natural processes, from the functioning of animal organs to the cycling of global carbon. Yet, the study of microbial ecology is often limited by challenges in visualizing microbial processes and replicating the environmental conditions under which they unfold. Microfluidics operates at the characteristic scale at which microorganisms live and perform their functions, thus allowing for the observation and quantification of behaviors such as growth, motility, and responses to external cues, often with greater detail than classical techniques. By enabling a high degree of control in space and time of environmental conditions such as nutrient gradients, pH levels, and fluid flow patterns, microfluidics further provides the opportunity to study microbial processes in conditions that mimic the natural settings harboring microbial life. In this review, we describe how recent applications of microfluidic systems to microbial ecology have enriched our understanding of microbial life and microbial communities. We highlight discoveries enabled by microfluidic approaches ranging from single-cell behaviors to the functioning of multi-cellular communities, and we indicate potential future opportunities to use microfluidics to further advance our understanding of microbial processes and their implications.

In Situ Single-Cell Bacterial Imaging Provides Mechanistic Insight into the Photodynamic Action of Photosensitizer-Loaded Hydrogels

Hydrogels, three-dimensional hydrophilic polymeric networks with high water retaining capacity, have gained prominence in wound management and drug delivery due to their tunability, softness, permeability, and biocompatibility. Electron-beam polymerized poly(ethylene glycol) diacrylate (PEGDA) hydrogels are particularly useful for phototherapies such as antimicrobial photodynamic therapy (aPDT) due to their excellent optical properties. This work takes advantage of the transparency of PEGDA hydrogels to investigate bacterial responses to aPDT at the single-cell level, in real-time and in situ. The photosensitizer methylene blue (MB) was loaded in PEGDA hydrogels by using two methods: reversible loading and irreversible immobilization within the 3D polymer network. MB release kinetics and singlet oxygen generation were studied, revealing the distinct behaviors of both hydrogels. Real-time imaging of Escherichia coli was conducted during aPDT in both hydrogel types, using the Min protein system to report changes in bacterial physiology. Min oscillation patterns provided mechanistic insights into bacterial photoinactivation, revealing a dependence on the hydrogel preparation method. This difference was attributed to the mobility of MB within the hydrogel, affecting its direct interaction with bacterial membranes. These findings shed light on the complex interplay between hydrogel properties and the bacterial response during aPDT, offering valuable insights for the development of antibacterial wound dressing materials. The study demonstrates the capability of real-time, single-cell fluorescence microscopy to unravel dynamic bacterial behaviors in the intricate environment of hydrogel surfaces during aPDT.

Dynamic responses of Salmonella Typhimurium to re-exposure to sublethal ciprofloxacin

This study was designed to evaluate the history-dependent behaviors of Salmonella Typhimurium re-exposed to sublethal levels of ciprofloxacin. The S. Typhimurium cells were pre-exposed to 0 (CON), 1/16 (LOW), 1/8 (MED), and 1/4 (HIGH) minimum inhibitory concentrations (MICs) of ciprofloxacin, followed by re-exposure to the same concentrations. The bacterial growth, postantibiotic effect (PAE), relative fitness, and swimming motility of treatments were evaluated in the absence of ciprofloxacin. The lag phase duration (LPD) was estimate to assess bacterial recovery under ciprofloxacin exposure. A disk diffusion assay was used to determine the cross-resistance and collateral sensitivity of CON, LOW, MED, and HIGH treatments to ciprofloxacin (CIP), ceftriaxone (CEF), erythromycin (ERY), gentamicin (GEN), and polymyxin B (POL). The S. Typhimurium cells pre-exposed to ciprofloxacin were susceptible in antibiotic-free media, showing delayed growth. The highest PAE (>1 h) and bacterial fluctuation (CV = 5%) were observed at the High treatment compared to the CON. The HIGH treatment had the lowest relative fitness levels (0.87) and swimming motility (55 mm). The LPD was significantly decreased at the LOW treatment (1.8 h) when re-exposed to 1/16 × MIC of ciprofloxacin. The LOW, MED, and HIGH treatments showed the cross-resistance to POL and the collateral sensitivity to CEF, ERY, and GEN. The pre-exposure to ciprofloxacin could induce phenotypic diversity, corresponding to the history-dependent behaviors. These results provide important insights for the dynamic nature of bacterial populations when re-exposed to sublethal concentrations of antibiotics.

Chaos in a bacterial stress response

Cellular responses to environmental changes are often highly heterogeneous and exhibit seemingly random dynamics. The astonishing insight of chaos theory is that such unpredictable patterns can, in principle, arise without the need for any random processes, i.e., purely deterministically without noise. However, while chaos is well understood in mathematics and physics, its role in cell biology remains unclear because the complexity and noisiness of biological systems make testing difficult. Here, we show that chaos explains the heterogeneous response of Escherichia coli cells to oxidative stress. We developed a theoretical model of the gene expression dynamics and demonstrate that chaotic behavior arises from rapid molecular feedbacks that are coupled with cell growth dynamics and cell-cell interactions. Based on theoretical predictions, we then designed single-cell experiments to show we can shift gene expression from periodic oscillations to chaos on demand. Our work suggests that chaotic gene regulation can be employed by cell populations to generate strong and variable responses to changing environments.

Abutilon theophrasti's Resilience against Allelochemical-Based Weed Management in Sustainable Agriculture - Due to Collection of Highly Advantageous Microorganisms?

Abutilon theophrasti Medik. (velvetleaf) is a problematic annual weed in field crops which has invaded many temperate parts of the world. Since the loss of crop yields can be extensive, approaches to manage the weed include not only conventional methods, but also biological methods, for instance by microorganisms releasing phytotoxins and plant-derived allelochemicals. Additionally, benzoxazinoid-rich rye mulches effective in managing common weeds like Amaranthus retroflexus L. have been tested for this purpose. However, recent methods for biological control are still unreliable in terms of intensity and duration. Rye mulches were also ineffective in managing velvetleaf. In this review, we present the attempts to reduce velvetleaf infestation by biological methods and discuss possible reasons for the failure. The resilience of velvetleaf may be due to the extraordinary capacity of the plant to collect, for its own survival, the most suitable microorganisms from a given farming site, genetic and epigenetic adaptations, and a high stress memory. Such properties may have developed together with other advantageous abilities during selection by humans when the plant was used as a crop. Rewilding could be responsible for improving the microbiomes of A. theophrasti.

Min Oscillations as Real-time Reporter of Sublethal Effects in Photodynamic Treatment of Bacteria

The Min protein system is a cell division regulator in Escherichia coli. Under normal growth conditions, MinD is associated with the membrane and undergoes pole-to-pole oscillations. The period of these oscillations has been previously proposed as a reporter for the bacterial physiological state at the single-cell level and has been used to monitor the response to sublethal challenges from antibiotics, temperature, or mechanical fatigue. Using real-time single-cell fluorescence imaging, we explore here the effect of photodynamic treatment on MinD oscillations. Irradiation of bacteria in the presence of the photosensitizer methylene blue disrupts the MinD oscillation pattern depending on its concentration. In contrast to antibiotics, which slow down the oscillation, photodynamic treatment results in an abrupt interruption, reflecting divergent physiological mechanisms leading to bacterial death. We show that MinD oscillations are sensitive to mild photodynamic effects that are overlooked by traditional methods, expanding the toolbox for mechanistic studies in antimicrobial photodynamic therapy.

Single-molecule localisation microscopy: accounting for chance co-localisation between foci in bacterial cells

Using single-molecule fluorescence microscopes, individual biomolecules can be observed within live bacterial cells. Using differently coloured probes, physical associations between two different molecular species can be assessed through co-localisation measurements. However, bacterial cells are finite and small (~ 1 μm) relative to the resolution limit of optical microscopes (~ 0.25 μm). Furthermore, the images produced by optical microscopes are typically two-dimensional projections of three-dimensional objects. These limitations mean that a certain proportion of object pairs (molecules) will inevitably be assigned as being co-localised, even when they are distant at molecular distance scales (nm). What is this proportion? Here, we attack this problem, theoretically and computationally, by creating a model of the co-localisation expected purely due to chance. We thus consider a bacterial cell wherein objects are distributed at random and evaluate the co-localisation in a fashion that emulates an experimental analysis. We consider simplified geometries where we can most transparently investigate the effect of a finite size of the cell and the effect of probing a three-dimensional cell in only two dimensions. Coupling theory to simulations, we also study the co-localisation expected due to chance using parameters relevant to bacterial cells. Overall, we show that the co-localisation expected purely due to chance can be quite substantial and describe the parameters that it depends upon.

Reframing cognition: getting down to biological basics

The premise of this two-part theme issue is simple: the cognitive sciences should join the rest of the life sciences in how they approach the quarry within their research domain. Specifically, understanding how organisms on the lower branches of the phylogenetic tree become familiar with, value and exploit elements of an ecological niche while avoiding harm can be expected to aid understanding of how organisms that evolved later (including Homo sapiens) do the same or similar things. We call this approach basal cognition. In this introductory essay, we explain what the approach involves. Because no definition of cognition exists that reflects its biological basis, we advance a working definition that can be operationalized; introduce a behaviour-generating toolkit of capacities that comprise the function (e.g. sensing/perception, memory, valence, learning, decision making, communication), each element of which can be studied relatively independently; and identify a (necessarily incomplete) suite of common biophysical mechanisms found throughout the domains of life involved in implementing the toolkit. The articles in this collection illuminate different aspects of basal cognition across different forms of biological organization, from prokaryotes and single-celled eukaryotes-the focus of Part 1-to plants and finally to animals, without and with nervous systems, the focus of Part 2. By showcasing work in diverse, currently disconnected fields, we hope to sketch the outline of a new multidisciplinary approach for comprehending cognition, arguably the most fascinating and hard-to-fathom evolved function on this planet. Doing so has the potential to shed light on problems in a wide variety of research domains, including microbiology, immunology, zoology, biophysics, botany, developmental biology, neurobiology/science, regenerative medicine, computational biology, artificial life and synthetic bioengineering. This article is part of the theme issue 'Basal cognition: conceptual tools and the view from the single cell'.