Reflection phase microscopy using spatio-temporal coherence of light

Many disease states are associated with cellular biomechanical changes as markers. Label-free phase microscopes are used to quantify thermally driven interface fluctuations, which allow the deduction of important cellular rheological properties. Here, the spatio-temporal coherence of light was used to implement a high-speed reflection phase microscope with superior depth selectivity and higher phase sensitivity. Nanometric scale motion of cytoplasmic structures can be visualized with fine details and three-dimensional resolution. Specifically, the spontaneous fluctuation occurring on the nuclear membrane of a living cell was observed at video rate. By converting the reflection phase into displacement, the sensitivity in quantifying nuclear membrane fluctuation was found to be about one nanometer. A reflection phase microscope can potentially elucidate biomechanical mechanisms of pathological and physiological processes.Korea Health Industry Development Institute. Korea Health Technology R&D Project (H114C3477)National Research Foundation of Korea (1R01HL121386-01A1)National Research Foundation of Korea (4R44EB012415)National Research Foundation of Korea (5R01NS051320)National Research Foundation of Korea (9P41EB015871-26A1)National Science Foundation (U.S.) (CBET-0939511)Hamamatsu CorporationSingapore-MIT Alliance. BioSystems and Micromechanics (BioSyM) Inter-Disciplinary Research GroupKorea University (Future Research Grant

Zigzag Turning Preference of Freely Crawling Cells

The coordinated motion of a cell is fundamental to many important biological processes such as development, wound healing, and phagocytosis. For eukaryotic cells, such as amoebae or animal cells, the cell motility is based on crawling and involves a complex set of internal biochemical events. A recent study reported very interesting crawling behavior of single cell amoeba: in the absence of an external cue, free amoebae move randomly with a noisy, yet, discernible sequence of ‘run-and-turns’ analogous to the ‘run-and-tumbles’ of swimming bacteria. Interestingly, amoeboid trajectories favor zigzag turns. In other words, the cells bias their crawling by making a turn in the opposite direction to a previous turn. This property enhances the long range directional persistence of the moving trajectories. This study proposes that such a zigzag crawling behavior can be a general property of any crawling cells by demonstrating that 1) microglia, which are the immune cells of the brain, and 2) a simple rule-based model cell, which incorporates the actual biochemistry and mechanics behind cell crawling, both exhibit similar type of crawling behavior. Almost all legged animals walk by alternating their feet. Similarly, all crawling cells appear to move forward by alternating the direction of their movement, even though the regularity and degree of zigzag preference vary from one type to the other

Enhancement of Chemotactic Cell Aggregation by Haptotactic Cell-To-Cell Interaction.

The crawling of biological cell is a complex phenomenon involving various biochemical and mechanical processes. Some of these processes are intrinsic to individual cells, while others pertain to cell-to-cell interactions and to their responses to extrinsically imposed cues. Here, we report an interesting aggregation dynamics of mathematical model cells, when they perform chemotaxis in response to an externally imposed global chemical gradient while they influence each other through a haptotaxis-mediated social interaction, which confers intriguing trail patterns. In the absence of the cell-to-cell interaction, the equilibrium population density profile fits well to that of a simple Keller-Segal population dynamic model, in which a chemotactic current density [Formula: see text] competes with a normal diffusive current density [Formula: see text], where p and ρ refer to the concentration of chemoattractant and population density, respectively. We find that the cell-to-cell interaction confers a far more compact aggregation resulting in a much higher peak equilibrium cell density. The mathematical model system is applicable to many biological systems such as swarming microglia and neutrophils or accumulating ants towards a localized food source

Directional persistence of a mathematical model cell.

<p>(a) Two sample traces of crawling model cells. (b) Mean squared displacement for seven different values of control parameter <i>K</i>_<i>decay</i>. (c) Auto-correlation functions of the instantaneous direction of crawling. (d) Directional persistent time <i>τ</i>₂ and superdiffusiveness exponent <i>γ</i> vs. <i>K</i>_<i>decay</i>. The insets in (a) show two representative snapshot images of the model cells. The blue (red) dashed line in (b) has a slope of 2 (1). The large (small) scale bar is 250 (20) <i>μm</i>. The variations in <i>τ</i>₂ and <i>γ</i> brought about by a different initial condition (positions and random seed number) are less than 0.5% (n = 5).</p

Three-dimensional imaging of macroscopic objects hidden behind scattering media using time-gated aperture synthesis

Precision measurement of the morphology of macroscopic objects has played an important role in many areas including the manufacturing, navigation, and safety fields. In some applications, objects of interest are often masked by scattering and/or applying turbid layers such that they remain invisible for existing methodologies. Here, we present a high depth-resolution three-dimensional (3D) macroscopy working through a scattering layer. In this implementation, we combined time-gated detection with synthetic aperture imaging to enhance single-scattered waves containing the object information above the background level set by the multiple scattering. We demonstrated the 3D mapping of the macroscopic object through a 13-scattering-mean-free-path thick scattering layer, where conventional digital holographic imaging failed to work, with the depth resolution of 400 μm and view field of 30 ×× 30 mm2. Our work is expected to broaden the range of applications covered by 3D macroscopy. © 2017 Optical Society of America under the terms of the OSA Open Access Publishing Agreemen

Chemotaxing model cell population.

<p>(a) 2,000 model cells (green) under a constant radial gradient of chemoattractant <i>p</i> (red). (b) Equilibrium density state for <i>K</i>_<i>decay</i> = 0.04 superimposed with an exemplary trace (blue) of a cell (red: start, black: end). (c) Density distribution at an equilibrium. (d) Chemotactic surface current density vs. surface density; the inset plots the slopes. (e) Diffusive surface current density vs. surface density gradient. (f) Effective diffusion coefficients [blue: estimation from (e), red: estimation from <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0154717#pone.0154717.g001" target="_blank">Fig 1b</a>]. Blue (red) error bars in (f) represent the uncertainty associated with the linear least square fitting of the data in Fig 2e (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0154717#pone.0154717.g001" target="_blank">Fig 1b</a>). The red dashed line in (c) represents an exponential fit of the data. The variations in <i>α</i> and <i>D</i> brought about by a different initial condition are less than 0.5% (n = 5).</p

Shapes and statistical properties of the trail networks for different values of <i>K</i>_<i>decay</i>.

<p>(a) Skeletonized networks of trails (red stars mark the nodes). (b) Probability density function of the distance between two immediately connected neighboring nodes. (c) Mean distance vs. <i>K</i>_<i>decay</i> (error bars represent standard deviations). (d) Skewness vs. <i>K</i>_<i>decay</i>. The standard deviation of the mean distance and and that of the skewness are about 10% with different initial conditions (n = 5).</p

Two distinct actin waves correlated with turns-and-runs of crawling microglia

© 2019 Yang et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.Freely crawling cells are often viewed as randomly moving Brownian particles but they generally exhibit some directional persistence. This property is often related to their zigzag motile behaviors that can be described as a noisy but temporally structured sequence of “runs” and “turns.” However, its underlying biophysical mechanism is largely unexplored. Here, we carefully investigate the collective actin wave dynamics associated with the zigzag-crawling movements of microglia (as primary brain immune cells) employing a number of different quantitative imaging modalities including synthetic aperture microscopy and optical diffraction tomography, as well as conventional fluorescence imaging and scanning electron microscopy. Interestingly, we find that microglia exhibit two distinct types of actin waves working at two quite different time scales and locations, and they seem to serve different purposes. One type of actin waves is fast “peripheral ruffles” arising spontaneously with an oscillating period of about 6 seconds at some portion of the leading edge of crawling microglia, where the vigorously biased peripheral ruffles seem to set the direction of a new turn (in 2-D free space). When the cell turning events are inhibited with a physical confinement (in 1-D track), the peripheral ruffles still exist at the leading edge with no bias but showing phase coherence in the cell crawling direction. The other type is “dorsal actin waves” which also exhibits an oscillatory behavior but with a much longer period of around 2 minutes compared to the fast “peripheral ruffles”. Dorsal actin waves (whether the cell turning events are inhibited or not) initiate in the lamellipodium just behind the leading edge, travelling down toward the core region of the cell and disappear. Such dorsal wave propagations seem to be correlated with migration of the cell. Thus, we may view the dorsal actin waves are connected with the “run” stage of cell body, whereas the fast ruffles at the leading front are involved in the “turn” stag

Reflection Phase Microscopy by Successive Accumulation of Interferograms

Imaging three-dimensional (3-D) structures of biological specimens without exogenous contrast agents is desired in biological and medical science in order not to disturb the physiological status of the living samples. Reflection phase microscopy based on interferometric detection has been useful for the label-free observation of such samples. However, the achievement of optical sectioning has been mainly based on the time gating set by the broad spectra of light sources. Here we propose wide-field reflection phase microscopy using a light source of narrow bandwidth, which is yet capable of achieving the optical sectioning sufficient for 3-D imaging of biological specimens. The depth selectivity is achieved by successive accumulation of interferograms (SAI) produced by synchronous angular scanning of a plane wave on both the sample and reference planes. This intensity-based cumulative process eventually results in a coherent addition of object fields that quickly attenuates the out-of-focus information along the axial direction. We theoretically investigated and numerically verified the generation of the depth selectivity by SAI. We also implemented a reflection phase microscope working with this principle and then demonstrated high-resolution 3-D imaging of living cells and small worms in a label-free manner. © 2019 American Chemical Societ