Rapid, accurate particle tracking by calculation of radial symmetry centers

3D transcranial ultrasound localization microscopy for discrimination between ischemic and hemorrhagic stroke in early phase

Early diagnosis is a critical part of the emergency care of cerebral hemorrhages and ischemia. A rapid and accurate diagnosis of strokes reduces the delays to appropriate treatments and a better functional recovery. Currently, CTscan and MRI are the gold standards with constraints of accessibility, availability, and possibly some contraindications. The development of Ultrasound Localization Microscopy (ULM) has enabled new perspectives to conventional transcranial ultrasound imaging with increased sensitivity, penetration depth, and resolution. The possibility of volumetric imaging has increased the field-of-view and provided a more precise description of the microvascularisation. In this study, rats (n = 9) were subjected to thromboembolic ischemic stroke or intracerebral hemorrhages prior to volumetric ULM at the early phases after onsets. Although the volumetric ULM performed in the early phase of ischemic stroke revealed a large hypoperfused area in the cortical area of the occluded artery, it showed a more diffused hypoperfusion in the hemorrhagic model. Respective computations of a Microvascular Diffusion Index highlighted different patterns of perfusion loss during the first 24 h of these two strokes’ subtypes. Our study provides the first proof that this methodology should allow early discrimination between ischemic and hemorrhagic stroke with a potential toward diagnosis and monitoring in clinic.

Spatial Organization of Dectin-1 and TLR2 during Synergistic Crosstalk Revealed by Super-resolution Imaging

Innate immune cells recognize and elicit responses against pathogens by integrating signals from different types of cell-surface receptors. How the receptors interact in the membrane to enable their signaling crosstalk is poorly understood. Here, we reveal the nanoscale organization of TLR2 and Dectin-1, a receptor pair known to cooperate in regulating antifungal immunity, through their synergistic signaling crosstalk at macrophage cell membranes. Using super-resolution single-molecule localization microscopy, we show that discrete noncolocalized nanoclusters of Dectin-1 and TLR2 are partially overlapped during their synergistic crosstalk. Compared to when one type of receptor is activated alone, the simultaneous activation of Dectin-1 and TLR2 leads to a higher percentage of both receptors being activated by their specific ligands and consequently an increased level of tyrosine phosphorylation. Our results depict, in nanoscale detail, how Dectin-1 and TLR2 achieve synergistic signaling through the spatial organization of their receptor nanoclusters.

Accurate automatic object 4D tracking in digital in-line holographic microscopy based on computationally rendered dark fields

Building on Gabor seminal principle, digital in-line holographic microscopy provides efficient means for space-time investigations of large volumes of interest. Thus, it has a pivotal impact on particle tracking that is crucial in advancing various branches of science and technology, e.g., microfluidics and biophysical processes examination (cell motility, migration, interplay etc.). Well-established algorithms often rely on heavily regularized inverse problem modelling and encounter limitations in terms of tracking accuracy, hologram signal-to-noise ratio, accessible object volume, particle concentration and computational burden. This work demonstrates the DarkTrack algorithm-a new approach to versatile, fast, precise, and robust 4D holographic tracking based on deterministic computationally rendered high-contrast dark fields. Its unique capabilities are quantitatively corroborated employing a novel numerical engine for simulating Gabor holographic recording of time-variant volumes filled with predefined dynamic particles. Our solution accounts for multiple scattering and thus it is poised to secure an important gap in holographic particle tracking technology and allow for ground-truth-driven benchmarking and quantitative assessment of tracking algorithms. Proof-of-concept experimental evaluation of DarkTrack is presented via analyzing live spermatozoa. Software supporting both novel numerical holographic engine and DarkTrack algorithm is made open access, which opens new possibilities and sets the stage for democratization of robust holographic 4D particle examination.

Spatiotemporal feedforward between PKM2 tetramers and mTORC1 prompts mTORC1 activation

Most mammalian cells couple glucose availability to anabolic processes via the mTORC1 pathway. However, the mechanism by which fluctuations in glucose availability are rapidly translated into mTORC1 signals remains elusive. Here, we show that cells rapidly respond to changes in glucose availability through the spatial coupling of mTORC1 and tetramers of the key glycolytic enzyme pyruvate kinase M2 (PKM2) on lysosomal surfaces in the late G1/S phases. The lysosomal localization of PKM2 tetramers enables rapid increases in local ATP concentrations around lysosomes to activate mTORC1, while bypassing the need to elevate global ATP levels in the entire cell. In essence, this spatial coupling establishes a feedforward loop to enable mTORC1 to rapidly sense and respond to changes in glucose availability. We further demonstrate that this mechanism ensures robust cell proliferation upon fluctuating glucose availability. Thus, we present mechanistic insights into the rapid response of the mTORC1 pathway to changes in glucose availability. The underlying mechanism may be applicable to the control of other cellular processes.

Anisotropic presentation of ligands on cargos modulates degradative function of phagosomes

Anisotropic arrangement of cell wall components is ubiquitous among bacteria and fungi, but how such functional anisotropy affects interactions between microbes and host immune cells is not known. Here we address this question with regard to phagosome maturation, the process used by host immune cells to degrade internalized microbes. We developed two-faced microparticles as model pathogens that display ligands on only one hemisphere and simultaneously function as fluorogenic sensors for probing biochemical reactions inside phagosomes during degradation. The fluorescent indicator on just one hemisphere gives the particle sensors a moon-like appearance. We show that anisotropic presentation of ligands on particles delays the start of acidification and proteolysis in phagosomes, but does not affect their degradative capacity. Our work suggests that the spatial presentation of ligands on pathogens plays a critical role in modulating the degradation process in phagosomes during host-pathogen interactions.

Raw Data to Results: A Hands-On Introduction and Overview of Computational Analysis for Single-Molecule Localization Microscopy

Single-molecule localization microscopy (SMLM) is an advanced microscopy method that uses the blinking of fluorescent molecules to determine the position of these molecules with a resolution below the diffraction limit (∼5-40 nm). While SMLM imaging itself is becoming more popular, the computational analysis surrounding the technique is still a specialized area and often remains a "black box" for experimental researchers. Here, we provide an introduction to the required computational analysis of SMLM imaging, post-processing and typical data analysis. Importantly, user-friendly, ready-to-use and well-documented code in Python and MATLAB with exemplary data is provided as an interactive experience for the reader, as well as a starting point for further analysis. Our code is supplemented by descriptions of the computational problems and their implementation. We discuss the state of the art in computational methods and software suites used in SMLM imaging and data analysis. Finally, we give an outlook into further computational challenges in the field.

Assessing the use of ellipsoidal microparticles for determining lipid membrane viscosity

The viscosity of lipid membranes sets the timescales of membrane-associated motions, whether driven or diffusive, and therefore influences the dynamics of a wide range of cellular processes. Techniques to measure membrane viscosity remain sparse, however, and reported measurements to date, even of similar systems, give viscosity values that span orders of magnitude. To address this, we improve a method based on measuring both the rotational and translational diffusion of membrane-anchored microparticles and apply this approach and one based on tracking the motion of phase-separated lipid domains to the same system of phase-separated giant vesicles. We find good agreement between the two methods, with inferred viscosities within a factor of two of each other. Our single-particle tracking technique uses ellipsoidal microparticles, and we show that the extraction of physically meaningful viscosity values from their motion requires consideration of their anisotropic shape. The validation of our method on phase-separated membranes makes possible its application to other systems, which we demonstrate by measuring the viscosity of bilayers composed of lipids with different chain lengths ranging from 14 to 20 carbon atoms, revealing a very weak dependence of two-dimensional viscosity on lipid size. The experimental and analysis methods described here should be generally applicable to a variety of membrane systems, both reconstituted and cellular.

3D Transcranial Ultrasound Localization Microscopy in the Rat Brain with a Multiplexed Matrix Probe

OBJECTIVE

Ultrasound Localization Microscopy (ULM) provides images of the microcirculation in-depth in living tissue. However, its implementation in two-dimension is limited by the elevation projection and tedious plane-by-plane acquisition. Volumetric ULM alleviates these issues and can map the vasculature of entire organs in one acquisition with isotropic resolution. However, its optimal implementation requires many independent acquisition channels, leading to complex custom hardware.

METHODS

In this article, we implemented volumetric ultrasound imaging with a multiplexed 32 x 32 probe driven by a single commercial ultrasound scanner. We propose and compare three different sub-aperture multiplexing combinations for localization microscopy in silico and in vitro with a flow of microbubbles in a canal. Finally, we evaluate the approach for micro-angiography of the rat brain.The "light" combination allows a higher maximal volume rate than the "full" combination while maintaining the field of view and resolution.

RESULTS

In the rat brain, 100,000 volumes were acquired within 7 min with a dedicated ultrasound sequence and revealed vessels down to 31 m in diameter with flows from 4.3 mm/s to 28.4 mm/s.

CONCLUSION

This work demonstrates the ability to perform a complete angiography with unprecedented resolution in the living rats brain with a simple and light setup through the intact skull.

SIGNIFICANCE

We foresee that it might contribute to democratize 3D ULM for both preclinical and clinical studies.

Modification to axial tracking for mobile magnetic microspheres

Three-dimensional particle tracking is a routine experimental procedure for various biophysical applications including magnetic tweezers. A common method for tracking the axial position of particles involves the analysis of diffraction rings whose pattern depends sensitively on the axial position of the bead relative to the focal plane. To infer the axial position, the observed rings are compared with reference images of a bead at known axial positions. Often the precision or accuracy of these algorithms is measured on immobilized beads over a limited axial range, while many experiments are performed using freely mobile beads. This inconsistency raises the possibility of incorrect estimates of experimental uncertainty. By manipulating magnetic beads in a bidirectional magnetic tweezer setup, we evaluated the error associated with tracking mobile magnetic beads and found that the error of tracking a moving magnetic bead increases by almost an order of magnitude compared to the error of tracking a stationary bead. We found that this additional error can be ameliorated by excluding the center-most region of the diffraction ring pattern from tracking analysis. Evaluation of the limitations of a tracking algorithm is essential for understanding the error associated with a measurement. These findings promise to bring increased resolution to three-dimensional bead tracking of magnetic microspheres.

Accurate detection of spherical objects in a complex background

The automated detection of particles in microscopy images has become a routinely used method for quantitative image analysis in biology, physics, and other research fields. While the majority of particle detection algorithms have been developed for bulk materials, the detection of particles in a heterogenous environment due to surfaces or other objects in the studied material is of great interest. However, particle detection is hindered by a complex background due to the diffraction of light resulting in a decreased contrast and image noise. We present a new heuristic method for the reliable detection of spherical particles that suppresses false detections due to a heterogenous background without additional background measurements. Further, we discuss methods to obtain particle coordinates with improved accuracy and compare with other methods, in particular with that of Crocker and Grier.

Light-Controlled Aggregation and Gelation of Viologen-Based Coordination Polymers

Ditopic bis-(triazole/pyridine)viologens are bidentate ligands that self-assemble into coordination polymers. In such photo-responsive materials, light irradiation initiates photo-induced electron transfer to generate π-radicals that can self-associate to form π-dimers. This leads to a cascade of events: processes at the supramolecular scale associated with mechanical and structural transition at the macroscopic scale. By tuning the irradiation power and duration, we evidence the formation of aggregates and gels. Using microscopy, we show that the aggregates are dense, polydisperse, micron-sized, spindle-shaped particles which grow in time. Using microscopy and time-resolved micro-rheology, we follow the gelation kinetics which leads to a gel characterized by a correlation length of a few microns and a weak elastic modulus. The analysis of the aggregates and the gel states vouch for an arrested phase separation process, a new scenario to supramolecular systems.

Single-cell nuclear architecture across cell types in the mouse brain

Diverse cell types in tissues have distinct gene expression programs, chromatin states, and nuclear architectures. To correlate such multimodal information across thousands of single cells in mouse brain tissue sections, we use integrated spatial genomics, imaging thousands of genomic loci along with RNAs and epigenetic markers simultaneously in individual cells. We reveal that cell type–specific association and scaffolding of DNA loci around nuclear bodies organize the nuclear architecture and correlate with differential expression levels in different cell types. At the submegabase level, active and inactive X chromosomes access similar domain structures in single cells despite distinct epigenetic and expression states. This work represents a major step forward in linking single-cell three-dimensional nuclear architecture, gene expression, and epigenetic modifications in a native tissue context.

Ultrasound microvasculature imaging with entropy-based radiality super-resolution (ERSR)

Objective:Microvasculature is highly relevant to the occurrence and development of pathologies such as cancer and diabetes. Ultrasound localization microscopy (ULM) has bypassed the diffraction limit and demonstrated its great potential to provide new imaging modality and establish new diagnostic criteria in clinical application. However, sparse microbubble distribution can be a significant bottleneck for improving temporal resolution, even for further clinical translation. Other important challenges for ULM to tackle in clinic also include high microbubble concentration and low frame rate.Approach:As part of the efforts to facilitate clinical translation, this paper focused on the low frame rate and the high microbubble distribution issue and proposed a new super-resolution imaging strategy called entropy-based radiality super-resolution (ERSR). The feasibility of ERSR is validated with simulations, phantom experiment and contrast-enhanced ultrasound scan of rabbit sciatic nerve with clinical accessible ultrasound system.Main results:ERSR can achieve 10 times improvement in spatial resolution compared to conventional ultrasound imaging, higher temporal resolution (∼10 times higher) and contrast-to-noise ratio under high-density microbubbles, compared with ULM under low-density microbubbles.Significance:We conclude ERSR could be a valuable imaging tool with high spatio-temporal resolution for clinical diagnosis and assessment of diseases potentially.

Force spectroscopy with electromagnetic tweezers

Force spectroscopy using magnetic tweezers (MTs) is a powerful method to probe the physical characteristics of single polymers. Typically, molecules are functionalized for specific attachment to a glass surface at one end and a micrometer-scale paramagnetic bead at the other end. By applying an external magnetic field, multiple molecules can be stretched and twisted simultaneously without exposure to potentially damaging radiation. The majority of MTs utilize mobile, permanent magnets to produce forces on the beads (and the molecule under test). However, translating and rotating the permanent magnets may require expensive precision actuators, limit the rate at which force can be changed, and may induce vibrations that disturb tether dynamics and bead tracking. Alternatively, the magnetic field can be produced with an electromagnet, which allows fast force modulation and eliminates motor-associated vibration. Here, we describe a low-cost quadrapolar electromagnetic tweezer design capable of manipulating DNA-tethered MyOne paramagnetic beads with forces as high as 15 pN. The solid-state nature of the generated B-field modulated along two axes is convenient for accessing the range of forces and torques relevant for studying the activity of DNA motor enzymes like polymerases and helicases. Our design specifically leverages technology available at an increasing number of university maker spaces and student-run machine shops. Thus, it is an accessible tool for undergraduate education that is applicable to a wide range of biophysical research questions.

Molecular organization of cytokinesis node predicts the constriction rate of the contractile ring

The molecular organization of cytokinesis proteins governs contractile ring function. We used single molecule localization microscopy in live cells to elucidate the molecular organization of cytokinesis proteins and relate it to the constriction rate of the contractile ring. Wild-type fission yeast cells assemble contractile rings by the coalescence of cortical proteins complexes called nodes whereas cells without Anillin/Mid1p (Δmid1) lack visible nodes yet assemble contractile rings competent for constriction from the looping of strands. We leveraged the Δmid1 contractile ring assembly mechanism to determine how two distinct molecular organizations, nodes versus strands, can yield functional contractile rings. Contrary to previous interpretations, nodes assemble in Δmid1 cells. Our results suggest that Myo2p heads condense upon interaction with actin filaments and an excess number of Myo2p heads bound to actin filaments hinders constriction thus reducing the constriction rate. Our work establishes a predictive correlation between the molecular organization of nodes and the behavior of the contractile ring.

Ferroelectric phase-transition frustration near a tricritical composition point

Phase transition describes a mutational behavior of matter states at a critical transition temperature or external field. Despite the phase-transition orders are well sorted by classic thermodynamic theory, ambiguous situations interposed between the first- and second-order transitions were exposed one after another. Here, we report discovery of phase-transition frustration near a tricritical composition point in ferroelectric Pb(Zr_1-xTi_x)O₃. Our multi-scale transmission electron microscopy characterization reveals a number of geometrically frustrated microstructure features such as self-assembled hierarchical domain structure, degeneracy of mesoscale domain tetragonality and decoupled polarization-strain relationship. Associated with deviation from the classic mean-field theory, dielectric critical exponent anomalies and temperature dependent birefringence data unveil that the frustrated transition order stems from intricate competition of short-range polar orders and their decoupling to long-range lattice deformation. With supports from effective Hamiltonian Monte Carlo simulations, our findings point out a potentially universal mechanism to comprehend the abnormal critical phenomena occurring in phase-transition materials.

Phase transition brings a plethora of exotic phenomena and intriguing effects such as spin and charge frustration. However, the phase transition order is not always explicit. Here, the authors discover phase transition frustration near a tricritical composition point in ferroelectric Pb(Zr,Ti)O₃.

TRAIT2D: a Software for Quantitative Analysis of Single Particle Diffusion Data

Single particle tracking (SPT) is one of the most widely used tools in optical microscopy to evaluate particle mobility in a variety of situations, including cellular and model membrane dynamics. Recent technological developments, such as Interferometric Scattering microscopy, have allowed recording of long, uninterrupted single particle trajectories at kilohertz framerates. The resulting data, where particles are continuously detected and do not displace much between observations, thereby do not require complex linking algorithms. Moreover, while these measurements offer more details into the short-term diffusion behaviour of the tracked particles, they are also subject to the influence of localisation uncertainties, which are often underestimated by conventional analysis pipelines. we thus developed a Python library, under the name of TRAIT2D (Tracking Analysis Toolbox - 2D version), in order to track particle diffusion at high sampling rates, and analyse the resulting trajectories with an innovative approach. The data analysis pipeline introduced is more localisation-uncertainty aware, and also selects the most appropriate diffusion model for the data provided on a statistical basis. A trajectory simulation platform also allows the user to handily generate trajectories and even synthetic time-lapses to test alternative tracking algorithms and data analysis approaches. A high degree of customisation for the analysis pipeline, for example with the introduction of different diffusion modes, is possible from the source code. Finally, the presence of graphical user interfaces lowers the access barrier for users with little to no programming experience.

TRAIT2D: a Software for Quantitative Analysis of Single Particle Diffusion Data

Single particle tracking (SPT) is one of the most widely used tools in optical microscopy to evaluate particle mobility in a variety of situations, including cellular and model membrane dynamics. Recent technological developments, such as Interferometric Scattering microscopy, have allowed recording of long, uninterrupted single particle trajectories at kilohertz framerates. The resulting data, where particles are continuously detected and do not displace much between observations, thereby do not require complex linking algorithms. Moreover, while these measurements offer more details into the short-term diffusion behaviour of the tracked particles, they are also subject to the influence of localisation uncertainties, which are often underestimated by conventional analysis pipelines. we thus developed a Python library, under the name of TRAIT2D (Tracking Analysis Toolbox - 2D version), in order to track particle diffusion at high sampling rates, and analyse the resulting trajectories with an innovative approach. The data analysis pipeline introduced is more localisation-uncertainty aware, and also selects the most appropriate diffusion model for the data provided on a statistical basis. A trajectory simulation platform also allows the user to handily generate trajectories and even synthetic time-lapses to test alternative tracking algorithms and data analysis approaches. A high degree of customisation for the analysis pipeline, for example with the introduction of different diffusion modes, is possible from the source code. Finally, the presence of graphical user interfaces lowers the access barrier for users with little to no programming experience.

Embedded nanometer position tracking based on enhanced phasor analysis

We present an embedded real-time 1D position tracking device at a nanometer precision. The embedded algorithm extracts the most appropriate region of the signal without manual intervention and estimates the position based on the phase shift from the signal's first Fourier harmonic. Using simulated datasets, we demonstrate that the proposed approach can achieve a similar precision to the state-of-the-art maximum likelihood fitting-based method while executing over four orders of magnitude faster. We further implemented this algorithm on a low-power microprocessor and developed a simple, compact, and low-cost embedded position tracking device. We demonstrate nanometer tracking precision in real-time drift tracking experiments.

Tuning the performance of a micrometer-sized Stirling engine through reservoir engineering

Colloidal heat engines are paradigmatic models to understand the conversion of heat into work in a noisy environment - a domain where biological and synthetic nano/micro machines function. While the operation of these engines across thermal baths is well-understood, how they function across baths with noise statistics that is non-Gaussian and also lacks memory, the simplest departure from the thermal case, remains unclear. Here we quantified the performance of a colloidal Stirling engine operating between an engineered memoryless non-Gaussian bath and a Gaussian one. In the quasistatic limit, the non-Gaussian engine functioned like a thermal one as predicted by theory. On increasing the operating speed, due to the nature of noise statistics, the onset of irreversibility for the non-Gaussian engine preceded its thermal counterpart and thus shifted the operating speed at which power is maximum. The performance of nano/micro machines can be tuned by altering only the nature of reservoir noise statistics.

Super-resolution fluorescence imaging of extracellular environments

The extracellular matrix (ECM) is an important biophysical environment that plays a role in a number of physiological processes. The ECM is highly dynamic, with changes occurring as local, nanoscale, physicochemical variations in physical confinement and chemistry from the perspective of biological molecules. The length and time scale of ECM dynamics are challenging to measure with current spectroscopic techniques. Super-resolution fluorescence microscopy has the potential to probe local, nanoscale, physicochemical variations in the ECM. Here, we review super-resolution imaging and analysis methods and their application to study model nanoparticles and biomolecules within synthetic ECM hydrogels and the brain extracellular space (ECS). We provide a perspective of future directions for the field that can move super-resolution imaging of the ECM towards more biomedically-relevant samples. Overall, super-resolution imaging is a powerful tool that can increase our understanding of extracellular environments at new spatiotemporal scales to reveal ECM processes at the molecular-level.

Host-emitted amino acid cues regulate bacterial chemokinesis to enhance colonization

Animal microbiomes are assembled predominantly from environmental microbes, yet the mechanisms by which individual symbionts regulate their transmission into hosts remain underexplored. By tracking the experimental evolution of Aeromonas veronii in gnotobiotic zebrafish, we identify bacterial traits promoting host colonization. Multiple independently evolved isolates with increased immigration harbored mutations in a gene we named sensor of proline diguanylate cyclase enzyme (SpdE) based on structural, biochemical, and phenotypic evidence that SpdE encodes an amino-acid-sensing diguanylate cyclase. SpdE detects free proline and to a lesser extent valine and isoleucine, resulting in reduced production of intracellular c-di-GMP, a second messenger controlling bacterial motility. Indeed, SpdE binding to amino acids increased bacterial motility and host colonization. Hosts serve as sources of SpdE-detected amino acids, with levels varying based on microbial colonization status. Our work demonstrates that bacteria use chemically regulated motility, or chemokinesis, to sense host-emitted cues that trigger active immigration into hosts.

Cubic spline-based depth-dependent localization of mitochondria-endoplasmic reticulum contacts by three-dimensional light-sheet super-resolution microscopy

The contact distance between mitochondria (Mito) and endoplasmic reticulum (ER) has received considerable attention owing to their crucial function in maintaining lipid and calcium homeostasis. Herein, cubic spline algorithm-based depth-dependent fluorescence-free three-dimensional light-sheet super-resolution microscopy (3D LSRM) with dual-wavelength illumination sources was investigated to study the distance of Mito-ER contacts in various live cells. To detect wavelength-dependent scattering, 12 nm gold nanoparticles (AuNPs) and 20 nm silver nanoparticles (AgNPs) as fluorescence-free nanoprobes were conjugated with Mito and ER. The cubic spline algorithm-based method showed improved localization precision in lateral and axial directions compared with that for previously used least squares and least cubic algorithms. The cubic spline-based depth-dependent localization was applied to the spatial localization of nanoprobes in super-resolution images, in which the average distance of Mito and ER was 22.4 nm in HeLa cells, 22.2 nm in RAW264.7 macrophage cells, 21.9 nm in AGS cells, 21.4 nm in HT29 cells, and 21.3 nm in HEK293 cells. The distances were ∼12% larger than those previously determined by electron microscopy, which demonstrated that this method was accessible and reliable for studying the intracellular structures of various live cells at the subdiffraction limit resolution.

Enhanced Signal-to-Noise and Fast Calibration of Optical Tweezers Using Single Trapping Events

The trap stiffness us the key property in using optical tweezers as a force transducer. Force reconstruction via maximum-likelihood-estimator analysis (FORMA) determines the optical trap stiffness based on estimation of the particle velocity from statistical trajectories. Using a modification of this technique, we determine the trap stiffness for a two micron particle within 2 ms to a precision of ∼10% using camera measurements at 10 kfps with the contribution of pixel noise to the signal being larger the level Brownian motion. This is done by observing a particle fall into an optical trap once at a high stiffness. This type of calibration is attractive, as it avoids the use of a nanopositioning stage, which makes it ideal for systems of large numbers of particles, e.g., micro-fluidics or active matter systems.

Revealing the dynamic adsorption and diffusion of peptide amphiphile on supported lipid bilayer by single molecule experiment and simulation

Dynamic adsorption and diffusion of peptide amphiphiles (PAs) with different numbers of alkyl tails on supported lipid bilayers (SLBs) were investigated by single molecule tracking experiment and molecule dynamic simulation. Experimental results show two distinct populations of PAs with different residence time. Residence time of adsorbed PAs increases with the increase of the alkyl tails, whereas diffusion coefficient monotonically decreases with rising the number of alkyl tails and also decreases with increasing the mobility of SLBs. All-atom molecule dynamic simulation results prove that the adsorption and diffusion of PAs on SLB surface are mainly determined by interactions between PAs and SLBs and also the intrinsic mobility of PAs in aqueous solution. The electrostatic interactions and the mobility of PAs are two dominated but contradictory coefficients for the adsorption and diffusion of PAs. By increasing the alkyl tails, the mobility of PAs decreases while the electrostatic property does not change significantly, resulting in the increase of residence time and decrease of diffusivity of PAs. Additionally, for the PAs with large number of alkyl tails (≥ 3 alkyl tails), steric hindrance of alkyl tails leads to the decrease of adsorption probability of PAs on SLB surface. These findings lay the groundwork for guiding the design of PAs with high cell affinity, potentially useful for efficient drug delivery.

Locally adaptive thresholding centroid localization in confocal microscopy

We introduce an iteration-free approach, based on a centroid algorithm with a locally adaptive threshold, for nanometer-level peak position localization of the axial response signal in confocal microscopy. This approach has localization accuracies that are near theoretical limits, especially when there is a small number of sampling points within the discrete signal. The algorithm is also orders of magnitude faster compared to fitting schemes based on maximum likelihood estimation. Simulations and experiments demonstrate the localization performance of the approach.

Precision single-particle localization using radial variance transform

We introduce an image transform designed to highlight features with high degree of radial symmetry for identification and subpixel localization of particles in microscopy images. The transform is based on analyzing pixel value variations in radial and angular directions. We compare the subpixel localization performance of this algorithm to other common methods based on radial or mirror symmetry (such as fast radial symmetry transform, orientation alignment transform, XCorr, and quadrant interpolation), using both synthetic and experimentally obtained data. We find that in all cases it achieves the same or lower localization error, frequently reaching the theoretical limit.

Simultaneous spatiotemporal super-resolution and multi-parametric fluorescence microscopy

Super-resolution microscopy and single molecule fluorescence spectroscopy require mutually exclusive experimental strategies optimizing either temporal or spatial resolution. To achieve both, we implement a GPU-supported, camera-based measurement strategy that highly resolves spatial structures (~100 nm), temporal dynamics (~2 ms), and molecular brightness from the exact same data set. Simultaneous super-resolution of spatial and temporal details leads to an improved precision in estimating the diffusion coefficient of the actin binding polypeptide Lifeact and corrects structural artefacts. Multi-parametric analysis of epidermal growth factor receptor (EGFR) and Lifeact suggests that the domain partitioning of EGFR is primarily determined by EGFR-membrane interactions, possibly sub-resolution clustering and inter-EGFR interactions but is largely independent of EGFR-actin interactions. These results demonstrate that pixel-wise cross-correlation of parameters obtained from different techniques on the same data set enables robust physicochemical parameter estimation and provides biological knowledge that cannot be obtained from sequential measurements.

Fast and Accurate Nanoparticle Characterization Using Deep-Learning-Enhanced Off-Axis Holography

Characterization of suspended nanoparticles in their native environment plays a central role in a wide range of fields, from medical diagnostics and nanoparticle-enhanced drug delivery to nanosafety and environmental nanopollution assessment. Standard optical approaches for nanoparticle sizing assess the size via the diffusion constant and, as a consequence, require long trajectories and that the medium has a known and uniform viscosity. However, in most biological applications, only short trajectories are available, while simultaneously, the medium viscosity is unknown and tends to display spatiotemporal variations. In this work, we demonstrate a label-free method to quantify not only size but also refractive index of individual subwavelength particles using 2 orders of magnitude shorter trajectories than required by standard methods and without prior knowledge about the physicochemical properties of the medium. We achieved this by developing a weighted average convolutional neural network to analyze holographic images of single particles, which was successfully applied to distinguish and quantify both size and refractive index of subwavelength silica and polystyrene particles without prior knowledge of solute viscosity or refractive index. We further demonstrate how these features make it possible to temporally resolve aggregation dynamics of 31 nm polystyrene nanoparticles, revealing previously unobserved time-resolved dynamics of the monomer number and fractal dimension of individual subwavelength aggregates.

Integrated spatial genomics reveals global architecture of single nuclei

Identifying the relationships between chromosome structures, nuclear bodies, chromatin states, and gene expression is an overarching goal of nuclear organization studies^1–4. Because individual cells appear to be highly variable at all these levels⁵, it is essential to map different modalities in the same cells. Here, we report the imaging of 3,660 chromosomal loci in single mouse embryonic stem cells (mESCs) by DNA seqFISH+, along with 17 chromatin marks and subnuclear structures by sequential immunofluorescence (IF) and the expression profile of 70 RNAs. We found many loci were invariantly associated with IF marks in single mESCs. These loci form “fixed points” in the nuclear organizations in single cells and often appear on the surfaces of nuclear bodies and zones defined by combinatorial chromatin marks. Furthermore, highly expressed genes appear to be pre-positioned to active nuclear zones, independent of bursting dynamics in single cells. Our analysis also uncovered several distinct mESCs subpopulations with characteristic combinatorial chromatin states. Using clonal analysis, we show that the global levels of some chromatin marks, such as H3K27me3 and macroH2A1 (mH2A1), are heritable over at least 3–4 generations, whereas other marks fluctuate on a faster time scale. This seqFISH+ based spatial multimodal approach can be used to explore nuclear organization and cell states in diverse biological systems.

Fundamental limits and optimal estimation of the resonance frequency of a linear harmonic oscillator

All physical oscillators are subject to thermodynamic and quantum perturbations, fundamentally limiting measurement of their resonance frequency. Analyses assuming specific ways of estimating frequency can underestimate the available precision and overlook unconventional measurement regimes. Here we derive a general, estimation-method-independent Cramer Rao lower bound for a linear harmonic oscillator resonance frequency measurement uncertainty, seamlessly accounting for the quantum, thermodynamic and instrumental limitations, including Fisher information from quantum backaction- and thermodynamically-driven fluctuations. We provide a universal and practical maximum-likelihood frequency estimator reaching the predicted limits in all regimes, and experimentally validate it on a thermodynamically-limited nanomechanical oscillator. Low relative frequency uncertainty is obtained for both very high bandwidth measurements (≈ 10-5 for τ = 30 μs ) and measurements using thermal fluctuations alone (<10-6). Beyond nanomechanics, these results advance frequency-based metrology across physical domains.

Macrophage activation on "phagocytic synapse" arrays: Spacing of nanoclustered ligands directs TLR1/2 signaling with an intrinsic limit

The activation of Toll-like receptor heterodimer 1/2 (TLR1/2) by microbial components plays a critical role in host immune responses against pathogens. TLR1/2 signaling is sensitive to the chemical structure of ligands, but its dependence on the spatial distribution of ligands on microbial surfaces remains unexplored. Here, we reveal the quantitative relationship between TLR1/2-triggered immune responses and the spacing of ligand clusters by designing an artificial "phagocytic synapse" nanoarray platform to mimic the cell-microbe interface. The ligand spacing dictates the proximity of receptor clusters on the cell surface and consequently the pro-inflammatory responses of macrophages. However, cell responses reach their maximum at small ligand spacings when the receptor nanoclusters become adjacent to one another. Our study demonstrates the feasibility of using spatially patterned ligands to modulate innate immunity. It shows that the receptor clusters of TLR1/2 act as a driver in integrating the spatial cues of ligands into cell-level activation events.

High-Precision Protein-Tracking With Interferometric Scattering Microscopy

The mobility of proteins and lipids within the cell, sculpted oftentimes by the organization of the membrane, reveals a great wealth of information on the function and interaction of these molecules as well as the membrane itself. Single particle tracking has proven to be a vital tool to study the mobility of individual molecules and unravel details of their behavior. Interferometric scattering (iSCAT) microscopy is an emerging technique well-suited for visualizing the diffusion of gold nanoparticle-labeled membrane proteins to a spatial and temporal resolution beyond the means of traditional fluorescent labels. We discuss the applicability of interferometric single particle tracking (iSPT) microscopy to investigate the minutia in the motion of a protein through measurements visualizing the mobility of the epidermal growth factor receptor in various biological scenarios on the live cell.

Transition Path Dynamics of a Dielectric Particle in a Bistable Optical Trap

Many processes in chemistry, physics, and biology involve rare events in which the system escapes from a metastable state by surmounting an activation barrier. Examples range from chemical reactions, protein folding, and nucleation events to the catastrophic failure of bridges. A challenge in understanding the underlying mechanisms is that the most interesting information is contained within the rare transition paths, the exceedingly short periods when the barrier is crossed. To establish a model process that enables access to all relevant timescales, although highly disparate, we probe the dynamics of single dielectric particles in a bistable optical trap in solution. Precise localization by high-speed tracking enables us to resolve the transition paths and relate them to the detailed properties of the 3D potential within which the particle diffuses. By varying the barrier height and shape, the experiments provide a stringent benchmark of current theories of transition path dynamics.

Time-correlated single molecule localization microscopy enhances resolution and fidelity

Single-molecule-localization-microscopy (SMLM) enables superresolution imaging of biological samples down to ~ 10–20 nm and in single molecule detail. However, common SMLM reconstruction largely disregards information embedded in the entire intensity trajectories of individual emitters. Here, we develop and demonstrate an approach, termed time-correlated-SMLM (tcSMLM), that uses such information for enhancing SMLM reconstruction. Specifically, tcSMLM is shown to increase the spatial resolution and fidelity of SMLM reconstruction of both simulated and experimental data; esp. upon acquisition under stringent conditions of low SNR, high acquisition rate and high density of emitters. We further provide detailed guidelines and optimization procedures for effectively applying tcSMLM to data of choice. Importantly, our approach can be readily added in tandem to multiple SMLM and related superresolution reconstruction algorithms. Thus, we expect that our approach will become an effective and readily accessible tool for enhancing SMLM and superresolution imaging.

Mechanical Responses of Breast Cancer Cells to Substrates of Varying Stiffness Revealed by Single-Cell Measurements

How cancer cells respond to different mechanical environments remains elusive. Here, we investigated the tension in single focal adhesions of MDA-MB-231 (metastatic breast cancer cells) and MCF-10A (normal human breast cells) cells on substrates of varying stiffness using single-cell measurements. Tension measurements in single focal adhesions using an improved FRET-based tension sensor showed that the tension in focal adhesions of MDA-MB-231 cells increased on stiffer substrates while the tension in MCF-10A cells exhibited no apparent change against the substrate stiffness. Viscoelasticity measurements using magnetic tweezers showed that the power-law exponent of MDA-MB-231 cells decreased on stiffer substrates whereas MCF-10A cells had similar exponents throughout the whole stiffness, indicating that MDA-MB-231 cells change their viscoelasticity on stiffer substrates. Such changes in tension in focal adhesions and viscoelasticity against the substrate stiffness represent an adaptability of cancer cells in mechanical environments, which can facilitate the metastasis of cancer cells to different tissues.

Gaining insight into cellular cardiac physiology using single particle tracking

Single particle tracking (SPT) is a robust technique to monitor single-molecule behaviors in living cells directly. By this approach, we can uncover the potential biological significance of particle dynamics by statistically characterizing individual molecular behaviors. SPT provides valuable information at the single-molecule level, that could be obscured by simple averaging that is inherent to conventional ensemble measurements. Here, we give a brief introduction to SPT including the commonly used optical implementations, fluorescence labeling strategies, and data analysis methods. We then focus on how SPT has been harnessed to decipher myocardial function. In this context, SPT has provided novel insight into the lateral diffusion of signal receptors and ion channels, the dynamic organization of cardiac nanodomains, subunit composition and stoichiometry of cardiac ion channels, myosin movement along actin filaments, the kinetic features of transcription factors involved in cardiac remodeling, and the intercellular communication by nanotubes. Finally, we speculate on the prospects and challenges of applying SPT to future questions regarding cellular cardiac physiology using SPT.

Multispectral Nanoparticle Tracking Analysis for the Real-Time and Label-Free Characterization of Amyloid-β Self-Assembly In Vitro

The deposition of amyloid β (Aβ) plaques and fibrils in the brain parenchyma is a hallmark of Alzheimer's disease (AD), but a mechanistic understanding of the role Aβ plays in AD has remained unclear. One important reason could be the limitations of current tools to size and count Aβ fibrils in real time. Conventional techniques from molecular biology largely use ensemble averaging; some microscopy analyses have been reported but suffer from low throughput. Nanoparticle tracking analysis is an alternative approach developed in the past decade for sizing and counting particles according to their Brownian motion; however, it is limited in sensitivity to polydisperse solutions because it uses only one laser. More recently, multispectral nanoparticle tracking analysis (MNTA) was introduced to address this limitation; it uses three visible wavelengths to quantitate heterogeneous particle distributions. Here, we used MNTA as a label-free technique to characterize the in vitro kinetics of Aβ1-42 aggregation by measuring the size distributions of aggregates during self-assembly. Our results show that this technology can monitor the aggregation of 106-108 particles/mL with a temporal resolution between 15 and 30 min. We corroborated this method with the fluorescent Thioflavin-T assay and transmission electron microscopy (TEM), showing good agreement between the techniques (Pearson's r = 0.821, P < 0.0001). We also used fluorescent gating to examine the effect of ThT on the aggregate size distribution. Finally, the biological relevance was demonstrated via fibril modulation in the presence of a polyphenolic Aβ disruptor. In summary, this approach measures Aβ assembly similar to ensemble-type measurements but with per-fibril resolution.

Point spread function in interferometric scattering microscopy (iSCAT). Part I: aberrations in defocusing and axial localization

Interferometric scattering (iSCAT) microscopy is an emerging label-free technique optimized for the sensitive detection of nano-matter. Previous iSCAT studies have approximated the point spread function in iSCAT by a Gaussian intensity distribution. However, recent efforts to track the mobility of nanoparticles in challenging speckle environments and over extended axial ranges has necessitated a quantitative description of the interferometric point spread function (iPSF). We present a robust vectorial diffraction model for the iPSF in tandem with experimental measurements and rigorous FDTD simulations. We examine the iPSF under various imaging scenarios to understand how aberrations due to the experimental configuration encode information about the nanoparticle. We show that the lateral shape of the iPSF can be used to achieve nanometric three-dimensional localization over an extended axial range on the order of 10 µm either by means of a fit to an analytical model or calibration-free unsupervised machine learning. Our results have immediate implications for three-dimensional single particle tracking in complex scattering media.

Fluorolabeling of the PPTase-Related Chemical Tags: Comparative Study of Different Membrane Receptors and Different Fluorophores in the Labeling Reactions

The set-up of an advanced imaging experiment requires a careful selection of suitable labeling strategies and fluorophores for the tagging of the molecules of interest. Here we provide an experimental workflow to allow evaluation of fluorolabeling performance of the chemical tags target of phosphopantetheinyl transferase enzymes (PPTases), once inserted in the sequence of different proteins of interest. First, S6 peptide tag was fused to three different single-pass transmembrane proteins (the tyrosine receptor kinases TrkA and VEGFR2 and the tumor necrosis factor receptor p75NTR), providing evidence that all of them can be conveniently albeit differently labeled. Moreover, we chose the S6-tagged TrkA construct to test eight different organic fluorophores for the PPTase labeling of membrane receptors in living cells. We systematically compared their non-specific internalization when added to a S6-tag negative cell culture, the percentage of S6-TrkA expressing cells effectively labeled and the relative mean fluorescence intensity, their photostability upon conjugation, and ratio of specific (cellular) versus background (glass-adhered) signal. This allowed to identify which fluorophores are actually recommended for these labeling reactions. Finally, we compared the PPTase labeling of a purified, YBBR-tagged Nerve Growth Factor with two differently charged organic dyes. We detected some batch-to-batch variability in the labeling yield, regardless of the fluorophore used. However, upon purification of the fluorescent species and incubation with living primary DRG neurons, no significant difference could be appreciated in both internalization and axonal transport of the labeled neurotrophins.

Phenotypic Parallelism during Experimental Adaptation of a Free-Living Bacterium to the Zebrafish Gut

Although animals encounter many bacterial species throughout their lives, only a subset colonize vertebrate digestive tracts, and these bacteria can profoundly influence the health and development of their animal hosts. We used experimental evolution to study a free-living bacterium as it adapts to a novel vertebrate host by serially passaging replicate populations of Shewanella oneidensis through the intestines of larval zebrafish (Danio rerio). Our results demonstrate that adaptation to the zebrafish gut is complex, with multiple evolutionary pathways capable of improving colonization, but that motility plays an important role during the onset of host association.

Although animals encounter a plethora of bacterial species throughout their lives, only a subset colonize vertebrate digestive tracts, and these bacteria can profoundly influence the health and development of their animal hosts. However, our understanding of how bacteria initiate symbioses with animal hosts remains underexplored, and this process is central to the assembly and function of gut bacterial communities. Therefore, we used experimental evolution to study a free-living bacterium as it adapts to a novel vertebrate host by serially passaging replicate populations of Shewanella oneidensis through the intestines of larval zebrafish (Danio rerio). After approximately 200 bacterial generations, isolates from evolved populations improved their ability to colonize larval zebrafish during competition against their unpassaged ancestor. Genome sequencing revealed unique sets of mutations in the two evolved isolates exhibiting the highest mean competitive fitness. One isolate exhibited increased swimming motility and decreased biofilm formation compared to the ancestor, and we identified a missense mutation in the mannose-sensitive hemagglutinin pilus operon that is sufficient to increase fitness and reproduce these phenotypes. The second isolate exhibited enhanced swimming motility but unchanged biofilm formation, and here the genetic basis for adaptation is less clear. These parallel enhancements in motility and fitness resemble the behavior of a closely related Shewanella strain previously isolated from larval zebrafish and suggest phenotypic convergence with this isolate. Our results demonstrate that adaptation to the zebrafish gut is complex, with multiple evolutionary pathways capable of improving colonization, but that motility plays an important role during the onset of host association.

Integrating engineered point spread functions into the phasor-based single-molecule localization microscopy framework

In single-molecule localization microscopy (SMLM), the use of engineered point spread functions (PSFs) provides access to three-dimensional localization information. The conventional approach of fitting PSFs with a single 2-dimensional Gaussian profile, however, often falls short in analyzing complex PSFs created by placing phase masks, deformable mirrors or spatial light modulators in the optical detection pathway. Here, we describe the integration of PSF modalities known as double-helix, saddle-point or tetra-pod into the phasor-based SMLM (pSMLM) framework enabling fast CPU based localization of single-molecule emitters with sub-pixel accuracy in three dimensions. For the double-helix PSF, pSMLM identifies the two individual lobes and uses their relative rotation for obtaining z-resolved localizations. For the analysis of saddle-point or tetra-pod PSFs, we present a novel phasor-based deconvolution approach entitled circular-tangent pSMLM. Saddle-point PSFs were experimentally realized by placing a deformable mirror in the Fourier plane and modulating the incoming wavefront with specific Zernike modes. Our pSMLM software package delivers similar precision and recall rates to the best-in-class software package (SMAP) at signal-to-noise ratios typical for organic fluorophores and achieves localization rates of up to 15 kHz (double-helix) and 250 kHz (saddle-point/tetra-pod) on a standard CPU. We further integrated pSMLM into an existing software package (SMALL-LABS) suitable for single-particle imaging and tracking in environments with obscuring backgrounds. Taken together, we provide a powerful hardware and software environment for advanced single-molecule studies.

Active particle feedback control with a single-shot detection convolutional neural network

The real-time detection of objects in optical microscopy allows their direct manipulation, which has recently become a new tool for the control, e.g., of active particles. For larger heterogeneous ensembles of particles, detection techniques are required that can localize and classify different objects with strongly inhomogeneous optical contrast at video rate, which is often difficult to achieve with conventional algorithmic approaches. We present a convolutional neural network single-shot detector which is suitable for real-time applications in optical microscopy. The network is capable of localizing and classifying multiple microscopic objects at up to 100 frames per second in images as large as [Formula: see text] pixels, even at very low signal-to-noise ratios. The detection scheme can be easily adapted and extended, e.g., to new particle classes and additional parameters as demonstrated for particle orientation. The developed framework is shown to control self-thermophoretic active particles in a heterogeneous ensemble selectively. Our approach will pave the way for new studies of collective behavior in active matter based on artificial interaction rules.

Potential quality improvement of stochastic optical localization nanoscopy images obtained by frame by frame localization algorithms

A data movie of stochastic optical localization nanoscopy contains spatial and temporal correlations, both providing information of emitter locations. The majority of localization algorithms in the literature estimate emitter locations by frame-by-frame localization (FFL), which exploit only the spatial correlation and leave the temporal correlation into the FFL nanoscopy images. The temporal correlation contained in the FFL images, if exploited, can improve the localization accuracy and the image quality. In this paper, we analyze the properties of the FFL images in terms of root mean square minimum distance (RMSMD) and root mean square error (RMSE). It is shown that RMSMD and RMSE can be potentially reduced by a maximum fold equal to the square root of the average number of activations per emitter. Analyzed and revealed are also several statistical properties of RMSMD and RMSE and their relationship with respect to a large number of data frames, bias and variance of localization errors, small localization errors, sample drift, and the worst FFL image. Numerical examples are taken and the results confirm the prediction of analysis. The ideas about how to develop an algorithm to exploit the temporal correlation of FFL images are also briefly discussed. The results suggest development of two kinds of localization algorithms: the algorithms that can exploit the temporal correlation of FFL images and the unbiased localization algorithms.

Super-resolution localization microscopy: Toward high throughput, high quality, and low cost

After nearly 15 years since its initial debut, super-resolution localization microscopy that surpasses the diffraction-limited resolution barrier of optical microscopy has rapidly gotten out of the ivory tower and entered a new phase to address various challenging biomedical questions. Recent advances in this technology greatly increased the imaging throughput, improved the imaging quality, simplified the sample preparation, and reduced the system cost, making this technology suitable for routine biomedical research. We will provide our perspective on the recent technical advances and their implications in serving the community of biomedical research.

Diffusion behavior of peptide amphiphiles containing different numbers of alkyl tails at a hydrophobic solid-liquid interface: single molecule tracking investigation

Using the single molecule tracking technique, the diffusion behavior of peptide amphiphiles (PAs) with different numbers of alkyl tails at a hydrophobic solid-liquid interface has been investigated. The effect of the number of alkyl tails of PAs on molecular trajectories at the hydrophobic solid-liquid interface has been systematically studied. PA molecules display an intermittent motion consisting of immobilization and hopping processes, which has been well simulated by the continuous time random walk (CTRW) model. The results reveal that the hydrophobic interaction between the PAs and hydrophobic surface plays an important role in the diffusion behavior of PAs. Increasing the number of alkyl tails in PAs systematically reduces the mobility of PAs on the hydrophobic surface. Moreover, the diffusion behavior of PAs at the hydrophobic interface also shows pH dependence. A decrease in pH is beneficial to the motion of all PAs on the hydrophobic surface, which can be ascribed to the protonation of PAs in acidic solutions. Therefore, the hydrophobic interaction is crucial to the transport of peptide amphiphiles at hydrophobic interfaces which would be important for the design of peptides in biological applications.

Imaging Switchable Protein Interactions with an Active Porous Polymer Support

Mechanistic details about how local physicochemistry of porous interfaces drives protein transport mechanisms are necessary to optimize biomaterial applications. Cross-linked hydrogels made of stimuli-responsive polymers have potential for active protein capture and release through tunable steric and chemical transformations. Simultaneous monitoring of dynamic changes in both protein transport and interfacial polymer structure is an experimental challenge. We use single-particle tracking (SPT) and fluorescence correlation spectroscopy Super-resolution Optical Fluctuation Imaging (fcsSOFI) to relate the switchable changes in size and structure of a pH-responsive hydrogel to the interfacial transport properties of a model protein, lysozyme. SPT analysis reveals the reversible switching of protein transport dynamics in and at the hydrogel polymer in response to pH changes. fcsSOFI allows us to relate tunable heterogeneity of the hydrogels and pores to reversible changes in the distribution of confined diffusion and adsorption/desorption. We find that physicochemical heterogeneity of the hydrogels dictates protein confinement and desorption dynamics, particularly at pH conditions in which the hydrogels are swollen.

Swimming motility of a gut bacterial symbiont promotes resistance to intestinal expulsion and enhances inflammation

Some of the densest microbial ecosystems in nature thrive within the intestines of humans and other animals. To protect mucosal tissues and maintain immune tolerance, animal hosts actively sequester bacteria within the intestinal lumen. In response, numerous bacterial pathogens and pathobionts have evolved strategies to subvert spatial restrictions, thereby undermining immune homeostasis. However, in many cases, it is unclear how escaping host spatial control benefits gut bacteria and how changes in intestinal biogeography are connected to inflammation. A better understanding of these processes could uncover new targets for treating microbiome-mediated inflammatory diseases. To this end, we investigated the spatial organization and dynamics of bacterial populations within the intestine using larval zebrafish and live imaging. We discovered that a proinflammatory Vibrio symbiont native to zebrafish governs its own spatial organization using swimming motility and chemotaxis. Surprisingly, we found that Vibrio’s motile behavior does not enhance its growth rate but rather promotes its persistence by enabling it to counter intestinal flow. In contrast, Vibrio mutants lacking motility traits surrender to host spatial control, becoming aggregated and entrapped within the lumen. Consequently, nonmotile and nonchemotactic mutants are susceptible to intestinal expulsion and experience large fluctuations in absolute abundance. Further, we found that motile Vibrio cells induce expression of the proinflammatory cytokine tumor necrosis factor alpha (TNFα) in gut-associated macrophages and the liver. Using inducible genetic switches, we demonstrate that swimming motility can be manipulated in situ to modulate the spatial organization, persistence, and inflammatory activity of gut bacterial populations. Together, our findings suggest that host spatial control over resident microbiota plays a broader role in regulating the abundance and persistence of gut bacteria than simply protecting mucosal tissues. Moreover, we show that intestinal flow and bacterial motility are potential targets for therapeutically managing bacterial spatial organization and inflammatory activity within the gut.

The use of live imaging and bacteria engineered to carry inducible genetic switches reveals how a gut symbiont uses swimming motility to escape the host's spatial control and persist within the physically dynamic confines of the intestine.