Non-genetic adaptation by collective migration.

Collective behaviors require coordination of individuals. Thus, a population must adjust its phenotypic distribution to adapt to changing environments. How can a population regulate its phenotypic distribution? One strategy is to utilize specialized networks for gene regulation and maintaining distinct phenotypic subsets. Another involves genetic mutations, which can be augmented by stress-response pathways. Here, we studied how a migrating bacterial population regulates its phenotypic distribution to traverse across diverse environments. We generated isogenic Escherichia coli populations with varying distributions of swimming behaviors and observed their phenotype distributions during migration in liquid and porous environments. Surprisingly, we found that during collective migration, the distributions of swimming phenotypes adapt to the environment without mutations or gene regulation. Instead, adaptation is caused by the dynamic and reversible enrichment of high-performing swimming phenotypes within each environment. This adaptation mechanism is supported by a recent theoretical study, which proposed that the phenotypic composition of a migrating population results from a balance between cell growth generating diversity and collective migration eliminating the phenotypes that are unable to keep up with the migrating group. Furthermore, by examining chemoreceptor abundance distributions during migration towards different attractants, we found that this mechanism acts on multiple chemotaxis-related traits simultaneously. Our findings reveal that collective migration itself can enable cell populations with continuous, multi-dimensional phenotypes to flexibly and rapidly adapt their phenotypic composition to diverse environmental conditions. Significance statement: Conventional cell adaptation mechanisms, like gene regulation and random phenotypic switching, act swiftly but are limited to a few traits, while mutation-driven adaptations unfold slowly. By quantifying phenotypic diversity during bacterial collective migration, we discovered an adaptation mechanism that rapidly and reversibly adjusts multiple traits simultaneously. By dynamically balancing the elimination of phenotypes unable to keep pace with generation of diversity through growth, this process enables populations to tune their phenotypic composition based on the environment, without the need for gene regulation or mutations. Given the prevalence of collective migration in microbes, cancers, and embryonic development, non-genetic adaptation through collective migration may be a universal mechanism for populations to navigate diverse environments, offering insights into broader applications across various fields.

Exploring the dynamics of vascular adaptation.

A combination of in toto imaging and theory suggests a new mechanism for the remodeling of veins in vascular networks.

Optimal inference of molecular interaction dynamics in FRET microscopy.

Intensity-based time-lapse fluorescence resonance energy transfer (FRET) microscopy has been a major tool for investigating cellular processes, converting otherwise unobservable molecular interactions into fluorescence time series. However, inferring the molecular interaction dynamics from the observables remains a challenging inverse problem, particularly when measurement noise and photobleaching are nonnegligible-a common situation in single-cell analysis. The conventional approach is to process the time-series data algebraically, but such methods inevitably accumulate the measurement noise and reduce the signal-to-noise ratio (SNR), limiting the scope of FRET microscopy. Here, we introduce an alternative probabilistic approach, B-FRET, generally applicable to standard 3-cube FRET-imaging data. Based on Bayesian filtering theory, B-FRET implements a statistically optimal way to infer molecular interactions and thus drastically improves the SNR. We validate B-FRET using simulated data and then apply it to real data, including the notoriously noisy in vivo FRET time series from individual bacterial cells to reveal signaling dynamics otherwise hidden in the noise.

HI-NESS: a family of genetically encoded DNA labels based on a bacterial nucleoid-associated protein.

The interplay between three-dimensional chromosome organisation and genomic processes such as replication and transcription necessitates in vivo studies of chromosome dynamics. Fluorescent organic dyes are often used for chromosome labelling in vivo. The mode of binding of these dyes to DNA cause its distortion, elongation, and partial unwinding. The structural changes induce DNA damage and interfere with the binding dynamics of chromatin-associated proteins, consequently perturbing gene expression, genome replication, and cell cycle progression. We have developed a minimally-perturbing, genetically encoded fluorescent DNA label consisting of a (photo-switchable) fluorescent protein fused to the DNA-binding domain of H-NS - a bacterial nucleoid-associated protein. We show that this DNA label, abbreviated as HI-NESS (H-NS-based indicator for nucleic acid stainings), is minimally-perturbing to genomic processes and labels chromosomes in eukaryotic cells in culture, and in zebrafish embryos with preferential binding to AT-rich chromatin.

Bacterial coexistence driven by motility and spatial competition.

Elucidating elementary mechanisms that underlie bacterial diversity is central to ecology1,2 and microbiome research3. Bacteria are known to coexist by metabolic specialization4, cooperation5 and cyclic warfare6-8. Many species are also motile9, which is studied in terms of mechanism10,11, benefit12,13, strategy14,15, evolution16,17 and ecology18,19. Indeed, bacteria often compete for nutrient patches that become available periodically or by random disturbances2,20,21. However, the role of bacterial motility in coexistence remains unexplored experimentally. Here we show that-for mixed bacterial populations that colonize nutrient patches-either population outcompetes the other when low in relative abundance. This inversion of the competitive hierarchy is caused by active segregation and spatial exclusion within the patch: a small fast-moving population can outcompete a large fast-growing population by impeding its migration into the patch, while a small fast-growing population can outcompete a large fast-moving population by expelling it from the initial contact area. The resulting spatial segregation is lost for weak growth-migration trade-offs and a lack of virgin space, but is robust to population ratio, density and chemotactic ability, and is observed in both laboratory and wild strains. These findings show that motility differences and their trade-offs with growth are sufficient to promote diversity, and suggest previously undescribed roles for motility in niche formation and collective expulsion-containment strategies beyond individual search and survival.

Modelling the ballistic-to-diffusive transition in nematode motility reveals variation in exploratory behaviour across species.

A quantitative understanding of organism-level behaviour requires predictive models that can capture the richness of behavioural phenotypes, yet are simple enough to connect with underlying mechanistic processes. Here, we investigate the motile behaviour of nematodes at the level of their translational motion on surfaces driven by undulatory propulsion. We broadly sample the nematode behavioural repertoire by measuring motile trajectories of the canonical laboratory strain Caenorhabditis elegans N2 as well as wild strains and distant species. We focus on trajectory dynamics over time scales spanning the transition from ballistic (straight) to diffusive (random) movement and find that salient features of the motility statistics are captured by a random walk model with independent dynamics in the speed, bearing and reversal events. We show that the model parameters vary among species in a correlated, low-dimensional manner suggestive of a common mode of behavioural control and a trade-off between exploration and exploitation. The distribution of phenotypes along this primary mode of variation reveals that not only the mean but also the variance varies considerably across strains, suggesting that these nematode lineages employ contrasting 'bet-hedging' strategies for foraging.

Mycorrhizal Fungi Respond to Resource Inequality by Moving Phosphorus from Rich to Poor Patches across Networks.

The world's ecosystems are characterized by an unequal distribution of resources [1]. Trade partnerships between organisms of different species-mutualisms-can help individuals cope with such resource inequality [2-4]. Trade allows individuals to exchange commodities they can provide at low cost for resources that are otherwise impossible or more difficult to access [5, 6]. However, as resources become increasingly patchy in time or space, it is unknown how organisms alter their trading strategies [7, 8]. Here, we show how a symbiotic fungus mediates trade with a host root in response to different levels of resource inequality across its network. We developed a quantum-dot-tracking technique to quantify phosphorus-trading strategies of arbuscular mycorrhizal fungi simultaneously exposed to rich and poor resource patches. By following fluorescent nanoparticles of different colors across fungal networks, we determined where phosphorus was hoarded, relocated, and transferred to plant hosts. We found that increasing exposure to inequality stimulated trade. Fungi responded to high resource variation by (1) increasing the total amount of phosphorus distributed to host roots, (2) decreasing allocation to storage, and (3) differentially moving resources within the network from rich to poor patches. Using single-particle tracking and high-resolution video, we show how dynamic resource movement may help the fungus capitalize on value differences across the trade network, physically moving resources to areas of high demand to gain better returns. Such translocation strategies can help symbiotic organisms cope with exposure to resource inequality.

Cell Boundary Confinement Sets the Size and Position of the E. coli Chromosome.

Although the spatiotemporal structure of the genome is crucial to its biological function, many basic questions remain unanswered on the morphology and segregation of chromosomes. Here, we experimentally show in Escherichia coli that spatial confinement plays a dominant role in determining both the chromosome size and position. In non-dividing cells with lengths increased to 10 times normal, single chromosomes are observed to expand > 4-fold in size. Chromosomes show pronounced internal dynamics but exhibit a robust positioning where single nucleoids reside robustly at mid-cell, whereas two nucleoids self-organize at 1/4 and 3/4 positions. The cell-size-dependent expansion of the nucleoid is only modestly influenced by deletions of nucleoid-associated proteins, whereas osmotic manipulation experiments reveal a prominent role of molecular crowding. Molecular dynamics simulations with model chromosomes and crowders recapitulate the observed phenomena and highlight the role of entropic effects caused by confinement and molecular crowding in the spatial organization of the chromosome.

Long-term positioning and polar preference of chemoreceptor clusters in E. coli.

The bacterial chemosensory arrays are a notable model for studying the basic principles of receptor clustering and cellular organization. Here, we provide a new perspective regarding the long-term dynamics of these clusters in growing E. coli cells. We demonstrate that pre-existing lateral clusters tend to avoid translocation to pole regions and, therefore, continually shuttle between the cell poles for many generations while being static relative to the local cell-wall matrix. We also show that the polar preference of clusters results fundamentally from reduced clustering efficiency in the lateral region, rather than a developmental-like progression of clusters. Furthermore, polar preference is surprisingly robust to structural alterations designed to probe preference due to curvature sorting, perturbing the cell envelope physiology affects the cluster-size distribution, and the size-dependent mobility of receptor complexes differs between polar and lateral regions. Thus, distinct envelope physiology in the polar and lateral cell regions may contribute to polar preference.

Bacterial Chemoreceptor Imaging at High Spatiotemporal Resolution Using Photoconvertible Fluorescent Proteins.

We describe two methods for high-resolution fluorescence imaging of the positioning and mobility of E. coli chemoreceptors fused to photoconvertible fluorescent proteins. Chemoreceptors such as Tar and Tsr are transmembrane proteins expressed at high levels (thousands of copies per cell). Together with their cognate cytosolic signaling proteins, they form clusters on the plasma membrane. Theoretical models imply that the size of these clusters is an important parameter for signaling, and recent PALM imaging has revealed a broad distribution of cluster sizes. We describe experimental setups and protocols for PALM imaging in fixed cells with ~10 nm spatial precision, which allows analysis of cluster-size distributions, and localized-photoactivation single-particle tracking (LPA-SPT) in live cells at ~10 ms temporal resolution, which allows for analysis of cluster mobility.

Build your own soil: exploring microfluidics to create microbial habitat structures.

Soil is likely the most complex ecosystem on earth. Despite the global importance and extraordinary diversity of soils, they have been notoriously challenging to study. We show how pioneering microfluidic techniques provide new ways of studying soil microbial ecology by allowing simulation and manipulation of chemical conditions and physical structures at the microscale in soil model habitats.

Phenotypic diversity and temporal variability in a bacterial signaling network revealed by single-cell FRET.

We present in vivo single-cell FRET measurements in the Escherichia coli chemotaxis system that reveal pervasive signaling variability, both across cells in isogenic populations and within individual cells over time. We quantify cell-to-cell variability of adaptation, ligand response, as well as steady-state output level, and analyze the role of network design in shaping this diversity from gene expression noise. In the absence of changes in gene expression, we find that single cells demonstrate strong temporal fluctuations. We provide evidence that such signaling noise can arise from at least two sources: (i) stochastic activities of adaptation enzymes, and (ii) receptor-kinase dynamics in the absence of adaptation. We demonstrate that under certain conditions, (ii) can generate giant fluctuations that drive signaling activity of the entire cell into a stochastic two-state switching regime. Our findings underscore the importance of molecular noise, arising not only in gene expression but also in protein networks.

Super-resolution imaging of light-matter interactions near single semiconductor nanowires.

Nanophotonics is becoming invaluable for an expanding range of applications, from controlling the spontaneous emission rate and the directionality of quantum emitters, to reducing material requirements of solar cells by an order of magnitude. These effects are highly dependent on the near field of the nanostructure, which constitutes the evanescent fields from propagating and resonant localized modes. Although the interactions between quantum emitters and nanophotonic structures are increasingly well understood theoretically, directly imaging these interactions experimentally remains challenging. Here we demonstrate a photoactivated localization microscopy-based technique to image emitter-nanostructure interactions. For a 75 nm diameter silicon nanowire, we directly observe a confluence of emission rate enhancement, directivity modification and guided mode excitation, with strong interaction at scales up to 13 times the nanowire diameter. Furthermore, through analytical modelling we distinguish the relative contribution of these effects, as well as their dependence on emitter orientation.

Signaling noise enhances chemotactic drift of E. coli.

Noise in the transduction of chemotactic stimuli to the flagellar motor of E. coli will affect the random run-and-tumble motion of the cell and the ability to perform chemotaxis. Here we use numerical simulations to show that an intermediate level of noise in the slow methylation dynamics enhances drift while not compromising localization near concentration peaks. A minimal model shows how such an optimal noise level arises from the interplay of noise and the dependence of the motor response on the network output. Our results suggest that cells can exploit noise to improve chemotactic performance.

Salmonella chemoreceptors McpB and McpC mediate a repellent response to L-cystine: a potential mechanism to avoid oxidative conditions.

Chemoreceptors McpB and McpC in Salmonella enterica have been reported to promote chemotaxis in LB motility-plate assays. Of the chemicals tested as potential effectors of these receptors, the only response was towards L-cysteine and its oxidized form, L-cystine. Although enhanced radial migration in plates suggested positive chemotaxis to both amino acids, capillary assays failed to show an attractant response to either, in cells expressing only these two chemoreceptors. In vivo fluorescence resonance energy transfer (FRET) measurements of kinase activity revealed that in wild-type bacteria, cysteine and cystine are chemoeffectors of opposing sign, the reduced form being a chemoattractant and the oxidized form a repellent. The attractant response to cysteine was mediated primarily by Tsr, as reported earlier for Escherichia coli. The repellent response to cystine was mediated by McpB/C. Adaptive recovery upon cystine exposure required the methyl-transferase/-esterase pair, CheR/CheB, but restoration of kinase activity was never complete (i.e. imperfect adaptation). We provide a plausible explanation for the attractant-like responses to both cystine and cysteine in motility plates, and speculate that the opposing signs of response to this redox pair might afford Salmonella a mechanism to gauge and avoid oxidative environments.

Response rescaling in bacterial chemotaxis.

Sensory systems rescale their response sensitivity upon adaptation according to simple strategies that recur in processes as diverse as single-cell signaling, neural network responses, and whole-organism perception. Here, we study response rescaling in Escherichia coli chemotaxis, where adaptation dynamically tunes the cells' motile response during searches for nutrients. Using in vivo fluorescence resonance energy transfer (FRET) measurements on immobilized cells, we demonstrate that the design of this prokaryotic signaling network follows the fold-change detection (FCD) strategy, responding faithfully to the shape of the input profile irrespective of its absolute intensity. Using a microfluidics-based assay for free swimming cells, we confirm intensity-independent gradient responses at the behavioral level. By theoretical analysis, we identify a set of sufficient conditions for FCD in E. coli chemotaxis, which leads to the prediction that the adaptation timescale is invariant with respect to the background input level. Additional FRET experiments confirm that the adaptation timescale is invariant over an ∼10,000-fold range of background concentrations. These observations in a highly optimized bacterial system support the concept that FCD represents a robust sensing strategy for spatial searches. To our knowledge, these experiments provide a unique demonstration of FCD in any biological sensory system.

Microfluidics for bacterial chemotaxis.

Microfluidics is revolutionizing the way we study the motile behavior of cells, by enabling observations at high spatial and temporal resolution in carefully controlled microenvironments. An important class of such behavior is bacterial chemotaxis, which plays a fundamental role in a broad range of processes, including disease pathogenesis, biofilm formation, bioremediation, and even carbon cycling in the ocean. In biophysical research, bacterial chemotaxis represents a powerful model system to understand how cells and organisms sense and respond to gradients. Using microfluidics to study chemotaxis of free-swimming bacteria presents experimental challenges that are distinct from those arising in chemotaxis studies of surface-adherent cells. Recently, these challenges have been met by the development of advanced microdevices, able to generate flow-free, steady gradients of arbitrary shape. Much attention to date has been focused on tool development. Yet, we are now at an exciting turning point where science begins to balance technology. Indeed, recent microfluidic studies provided new insights on both the mechanisms governing bacterial gradient sensing (e.g. tuning of response sensitivity, discrimination between conflicting gradients) and the large-scale consequences of chemotaxis (e.g. in the oceans). Here we outline the principles underlying recently proposed gradient generators for bacterial chemotaxis, illustrate the advantage of the microfluidic approach through selected examples, and identify a broader set of scientific questions that may now be addressed with this rapidly developing technology. The latest generation of microfluidic gradient generators, in particular, holds appeal for both biophysicists seeking to unravel the fundamental mechanisms of bacterial chemotaxis, and ecologists wishing to model chemotaxis in realistic environments. Time is ripe for a deeper integration between technology and biology in fully bringing to bear microfluidics on studies of this fascinating microbial behavior.

Bacterial chemotaxis in linear and nonlinear steady microfluidic gradients.

Diffusion-based microfluidic devices can generate steady, arbitrarily shaped chemical gradients without requiring fluid flow and are ideal for studying chemotaxis of free-swimming cells such as bacteria. However, if microfluidic gradient generators are to be used to systematically study bacterial chemotaxis, it is critical to evaluate their performance with actual quantitative chemotaxis tests. We characterize and compare three diffusion-based gradient generators by confocal microscopy and numerical simulations, select an optimal design and apply it to chemotaxis experiments with Escherichia coli in both linear and nonlinear gradients. Comparison of the observed cell distribution along the gradients with predictions from an established mathematical model shows very good agreement, providing the first quantification of chemotaxis of free-swimming cells in steady nonlinear microfluidic gradients and opening the door to bacterial chemotaxis studies in gradients of arbitrary shape.

A modular gradient-sensing network for chemotaxis in Escherichia coli revealed by responses to time-varying stimuli.

The Escherichia coli chemotaxis-signaling pathway computes time derivatives of chemoeffector concentrations. This network features modules for signal reception/amplification and robust adaptation, with sensing of chemoeffector gradients determined by the way in which these modules are coupled in vivo. We characterized these modules and their coupling by using fluorescence resonance energy transfer to measure intracellular responses to time-varying stimuli. Receptor sensitivity was characterized by step stimuli, the gradient sensitivity by exponential ramp stimuli, and the frequency response by exponential sine-wave stimuli. Analysis of these data revealed the structure of the feedback transfer function linking the amplification and adaptation modules. Feedback near steady state was found to be weak, consistent with strong fluctuations and slow recovery from small perturbations. Gradient sensitivity and frequency response both depended strongly on temperature. We found that time derivatives can be computed by the chemotaxis system for input frequencies below 0.006 Hz at 22 degrees C and below 0.018 Hz at 32 degrees C. Our results show how dynamic input-output measurements, time honored in physiology, can serve as powerful tools in deciphering cell-signaling mechanisms.

Modeling the chemotactic response of Escherichia coli to time-varying stimuli.

In their natural environment, cells need to extract useful information from complex temporal signals that vary over a wide range of intensities and time scales. Here, we study how such signals are processed by Escherichia coli during chemotaxis by developing a general theoretical model based on receptor adaptation and receptor-receptor cooperativity. Measured responses to various monotonic, oscillatory, and impulsive stimuli are all explained consistently by the underlying adaptation kinetics within this model. For exponential ramp signals, an analytical solution is discovered that reveals a remarkable connection between the dependence of kinase activity on the exponential ramp rate and the receptor methylation rate function. For exponentiated sine-wave signals, spectral analysis shows that the chemotaxis pathway acts as a lowpass filter for the derivative of the signal with the cutoff frequency determined by an intrinsic adaptation time scale. For large step stimuli, we find that the recovery time is determined by the constant maximum methylation rate, which provides a natural explanation for the observed recovery time additivity. Our model provides a quantitative system-level description of the chemotaxis signaling pathway and can be used to predict E. coli chemotaxis responses to arbitrary temporal signals. This model of the receptor system reveals the molecular origin of Weber's law in bacterial chemotaxis. We further identify additional constraints required to account for the related observation that the output of this pathway is constant under exponential ramp stimuli, a feature that we call "logarithmic tracking."