Motile cilia create fluid-mechanical microhabitats for the active recruitment of the host microbiome
- aResearch & Development, Emulate Inc., Boston, MA 02210;
- bGraduate Aeronautical Laboratories and Bioengineering, California Institute of Technology, Pasadena, CA 91125;
- cPacific Biosciences Research Center, University of Hawaii at Manoa, Honolulu, HI 96822;
- dDepartment of Aerospace and Mechanical Engineering, University of Southern California, Los Angeles, CA 90089-1191;
- eThe Department of Molecular and Cell Biology, University of California, Berkeley, CA 94720;
- fUS Department of Agriculture Forest Products Laboratory, Madison, WI 53726;
- gDepartment of Civil and Environmental Engineering, Stanford University, Stanford, CA 94305
See allHide authors and affiliations
Contributed by Margaret McFall-Ngai, July 21, 2017 (sent for review April 26, 2017; reviewed by Christophe Eloy and M. A. R. Koehl)

Significance
Recent findings demonstrate that microbiome communities often reside on mucociliated surfaces. While mucociliary clearance of bacteria from such surfaces has been extensively studied, the process of bacterial recruitment has remained unexplored. Here, using a simple model system, we show that ciliated surfaces, in addition to their clearance function, can create fluid-mechanical microhabitats with distinct transport and mixing properties that facilitate the active recruitment of symbiotic candidates from a background of suspended particles. Although each specific system will have unique properties, because ciliary structure and function are highly conserved, studies of models will contribute to an understanding of rules governing the selective behavior of ciliated surfaces.
Abstract
We show that mucociliary membranes of animal epithelia can create fluid-mechanical microenvironments for the active recruitment of the specific microbiome of the host. In terrestrial vertebrates, these tissues are typically colonized by complex consortia and are inaccessible to observation. Such tissues can be directly examined in aquatic animals, providing valuable opportunities for the analysis of mucociliary activity in relation to bacteria recruitment. Using the squid–vibrio model system, we provide a characterization of the initial engagement of microbial symbionts along ciliated tissues. Specifically, we developed an empirical and theoretical framework to conduct a census of ciliated cell types, create structural maps, and resolve the spatiotemporal flow dynamics. Our multiscale analyses revealed two distinct, highly organized populations of cilia on the host tissues. An array of long cilia (
Many eukaryotic cells feature motile cilia, microtubule-based surface actuators that sense and propel the extracellular fluidic environment (1⇓–3). Whereas cilia and cilia-like structures that sort and capture bacteria or particles are common and well-characterized features of aquatic organisms (4⇓⇓–7), in terrestrial animals such as mammals, the internal location of ciliated surfaces has made them difficult to study. A central challenge in internal ciliated mucus membranes, such as those lining the fallopian tube, the Eustachian tube, and the respiratory system (8), is to reconcile the effective clearance of toxic molecules and undesirable microbes with selective engagement of beneficial symbionts. For example, on airway epithelia, the coordinated beat of motile cilia creates a horizontal flow across their tips (9⇓⇓–12), which clears mucus, microorganisms, and debris (Fig. 1A). Disruption of this mucociliary clearance can lead to chronic infection of the airways (13). However, this simple model is incomplete; ciliated airway epithelia not only serve a clearance function, but also provide a habitat and a gateway for coevolved symbionts that play an essential role in the development of the host immune system and are believed to provide colonization resistance against pathogens (14, 15). The mechanisms by which mucociliary epithelia cilia might facilitate such controlled discrimination, and hence provide a specific barrier function, remain unknown.
Active recruitment of bacteria at mucociliary epithelia. (A, Left) Mucociliary flow with strict clearance function. (A, Right) Newly discovered mucociliary behaviors that can generate distinct flow regimes and micromechanical habitats. (B) E. scolopes inhales V. fischeri (magenta), and suspended material passes the paired internal mucociliary tissues (dotted box). (C) Model of direct interception (DI) of inhaled bacteria at the mucociliary surface (one side of paired organ shown). (C, i) Mantle-driven inhalation carries suspended matter past cilia. (C, ii) Matter is captured from flow by direct interception and transported to pores by mucociliary clearance. (D) Active recruitment mechanism. (D, i) Ciliary flow actively filters bacteria-sized particles into sheltered zone near pores where (C, ii) a structurally and behaviorally different population of cilia (Inset) enhances diffusion of biochemical signals. (E) Active recruitment mechanism was discovered by mapping the relationships between structure, function, and flow in the intact ciliated organ. Function: In vivo aggregation of bacterial symbiont V. fischeri (magenta) between appendages of ciliated organ before colonization. Structure: Scanning electron microscopy (SEM) image of the ciliated organ demarcates organization of two cilia populations. Flow: Black tracer path lines visualize cilia-driven flow with distinct vortical flow patterns below appendages (yellow outline). Blue arrows indicate flow direction.
Here, based on a detailed empirical and computational case study, we describe a set of previously unrecognized mucociliary behaviors involved in selective bacterial recruitment. We propose that mucociliary epithelia are not restricted to homogeneous organization, but that cilia populations can vary in morphology, kinematics, and spatial distribution, giving rise to distinct fluid-mechanical microhabitats with transport functions that extend well beyond the cilia tips (Fig. 1A). In particular, we present an example of an internal mucociliary epithelium that facilitates recruitment of symbiotic bacteria by creating two well-defined flow fields: one that actively filters bacteria-sized particles from the ambient flow into a sheltered zone and another that provides the sheltered zone with enhanced diffusion, such that biochemical signaling between bacterial candidates and host epithelial cells may be facilitated.
We conducted our case study using the symbiosis between the squid Euprymna scolopes and the bioluminescent bacterium Vibrio fischeri, which is an established invertebrate model for investigating interactions between bacterial partners and their host epithelia (for review see ref. 16). Newly hatched E. scolopes recruit V. fischeri to the surface of their nascent light-emitting organ from inhaled seawater. The seawater, which contains a diverse background of other bacterial species and suspended abiotic particles, is drawn into the mantle cavity for the animal’s respiratory flow and passes across the light organ. During embryogenesis, the light organ surface develops two complex, juvenile-specific ciliated fields—each featuring two appendages—that are lost after colonization by symbiotic bacteria, which indicates a possible role of the cilia in promoting symbiont recruitment (Fig. 1B). During initiation of symbiosis, V. fischeri cells become competitively dominant in bacterial aggregates located above the entry pores on the ciliated surface. They reside in these aggregates for a few hours, a time during which they become physiologically prepared or “primed” for their eventual migration through the pores and into the light organ (16). The strict timeline, well-defined localization, and exclusiveness of the squid–vibrio partnership, which occurs in an experimentally accessible, yet intact, internal organ, have revealed highly conserved biochemical mechanisms that also govern specific bacteria–host associations in mammals (16). Here, we used the squid–vibrio symbiosis to investigate the general question of how ciliary activity aids in the transport and selection of a bacterial partner to its target tissue. Specifically, we asked whether ciliary flow facilitates the recruitment of free-living V. fischeri cells from inhaled seawater and facilitates their engagement with the surface pores.
In the current model (17, 18), ciliary activity forms a conveyor belt of adhesive mucus, which directly intercepts particulates from the inhaled stream of seawater and moves them closer to the light organ’s entry pores (Fig. 1C). Instead, we found that one population of cilia generated an outer, vortical flow zone extending far beyond the surface (
We discovered these mechanisms by following an integrated experimental and computational approach for dissecting the multiscale structure–function relationships that link the initiation of a bacteria–host association to both the cilia-generated flows and the structure of the ciliated tissues (Fig. 1E).
Results
Evidence for a Cilia-Mediated Bacteria–Host Association.
Like the respiratory airways, the light organ is continuously exposed to inhaled particulate matter of a wide range of composition and size (20). In the early stages of symbiosis, wild-type V. fischeri, as well as nonmotile mutants of V. fischeri, nonsymbiont bacteria, and bacteria-sized synthetic particles, all accumulate at the light-organ surface (Fig. 1E), after which further selection takes place (17). These findings indicate that neither a specific bacteria shape nor a specific behavior is necessary for the first stage of association. This result poses two questions: (i) Does the respiratory flow directly deliver bacteria-sized particles to the ciliated surface? And (ii) how is larger particulate matter excluded from this surface?
Using video microscopy and particle tracking, we observed two counterrotating fluid vortices near the appendages of the light organ (Fig. 1E). These vortices occur in vivo as well as in excised light organs, indicating little contribution of the mantle geometry in directing particle trajectories at this scale. Further, during respiration at rest, the mantle pulsates at a much lower frequency (
The DI model fails to explain bacterial capture at the ciliated epithelium. (A) In vivo aggregation of bacteria-sized microbeads (1
Flow fields of the system associated with bacterial-cell capture. Mantle-driven, inhaled flow in E. scolopes at rest is laminar and passes by the ciliated epithelium. (A) Ventral view of juvenile E. scolopes. (B) Trajectories of microparticles reveal the flow regime of seawater that enters the mantle during normal inhalation and exits through the funnel during exhalation. Notably, the flow passes closely by the light organ where environmental, bacteria-sized particles are captured. (C) Velocity measurements of microparticles show that respiration-driven flow near the light organ reaches ca. 50–100
To test experimentally whether DI could be a major mode of particle capture, we exposed the animals to a suspension containing both V. fischeri-sized (1
Ciliary activity tightly controls adhesion of suspended materials to the surface. (A) In light organs with healthy ciliary beat, suspended microparticles (red;
Structural and Kinematic Characterization of the Ciliated Epithelium.
We used a rapid-fixation protocol, which “freezes” ciliary motion, followed by scanning electron microscopy (Fig. S3) to generate a snapshot image of ciliary activity on the light organ (28). We identified two distinct populations of cilia: long cilia beating in a metachronal wave along the outside of the appendages and short cilia with no detectable coordination covering the region around the pores and along the medial side of the appendages. High-speed video recordings (Movie S2) and confocal imaging, followed by kymograph analyses, ciliary beat frequency analysis, and kinematic analyses (Fig. 3 A–J), confirmed structural and kinematic differences between the two ciliary populations and enabled us to derive a tissue-wide map of spatiotemporal cilia organization and activity (Fig. 3K). The long cilia are 25
Structural and kinematic characterization of the ciliated epithelium. (A) Live confocal imaging of a ciliated appendage. (B) Top view of appendage showing metachronal waves of the long cilia. (C) Cross-section of an appendage and metachronal waves. Arrows indicate direction of ciliary beating along the perimeter. (D) Close-up of short cilia. (E) Sagittal section of an appendage showing short (
Dimensions and morphology of the ciliated surface. (A) Location of the ciliated light organ (white square) in the mantle cavity of a juvenile E. scolopes. (B) SEM of a light organ showing the position of the two pairs of ciliated appendages. The left pair is a diagram showing the types and distributions of cilia, and the right pair is shown in detail in C, where
Long Cilia Help Select and Focus Bacteria-Sized Particles.
Particle tracking and velocimetry in excised light organs revealed that the two populations of cilia generate two distinct flow compartments (Fig. 4 A and B, Fig. S4, and Movie S3): a vortical flow region consisting of two counterrotating vortices above the long cilia of the appendages and a sheltered zone near the pores above the short cilia. Both passive particles and motile V. fischeri cells that were caught in the vortices followed curved trajectories converging near the ciliated surface, where flow velocities reached up to 600
Isolation of bacteria-sized particles by ciliary flow. (A) Ciliary flow velocities derived from particle-tracking velocimetry. (B) Streamlines computed from average flow velocity field, showing, like a traffic map, the path along which the fluid will flow at each location. (C) Cross-sectional flow around an appendage. (D) Side view of flow around appendage. (E) Computational flow field and streamlines generated by 2D model of ciliated appendages with diameter
Flow visualizations in ex vivo ciliated surfaces confirm transport patterns of microparticles and bacteria. (A) Dye streaklines reveal the oscillatory flow generated by the long cilia. (B–E) The excised light organ is illuminated with a laser sheet. Fluorescent microparticles or bacteria suspended in the bath reveal the cilia-generated flow. (B) Pathlines and (C) velocities of particle tracers reveal the front-sectional flow pattern around appendages. (D) Path lines and (E) velocities of GFP-fluorescent V. fischeri suggest that these motile bacteria follow a similar flow pattern around the ciliated organ as passive microparticles.
Time-lapse confocal recordings confirm similar trajectories of particles and bacteria in light organs not excised from the mantle cavity. (A) Trajectories of 4-
We used a computational model to probe the role of the long cilia in creating the two flow compartments. Namely, we reconstructed the cross-section of the organ’s appendages by circumscribing the cilia tips, thereby producing two circles. We modeled the collective activity of the cilia by prescribing a tangential velocity around these circles that reflects the observed direction of the ciliary beat (Fig. 4C, Fig. S6 A–F, and Movie S6). This model does not take into account the beat pattern of the individual cilium; it rather accounts for the effective slip velocity caused by the ciliated surface. The resulting flow was obtained by solving Stokes equations for low-Reynolds numbers subject to the prescribed tangential velocities. This flow pattern recapitulates the cilia-driven flow observed empirically, i.e., a pair of counterrotating vortices and a central sheltered zone (Fig. 4E). Although this flow pattern is robust to small perturbations in the tangential velocity profile, it is not necessarily reproducible by profiles corresponding to arbitrary ciliary beat patterns and spatial distributions (e.g., Fig. S6 K–M). This finding indicates that formation of the two distinct flow zones is sensitive to the spatiotemporal organization of ciliary beat.
Computational model of the vortical flow zone. (A) SEM imaging shows that the ciliated appendages form a torus-like ring. (B) Optical cross-section of the two appendages.
Next, to explore whether the flow field constitutes a hydrodynamic sieve, selectively barring entrance of suspended material into the sheltered zone, we seeded the computed flow field with particles of finite diameter
Relative efficiency of possible mechanisms for capturing particles from mantle-driven flow (adapted from ref. 26)
Short Cilia Enhance Molecular Mixing.
We next investigated the role of the short cilia lining the sheltered zones. Tracer trajectories suggested a mix of diffusive transport with crisscrossing directional flow (Fig. 5 A–C and Fig. S7); therefore, we speculated that the combination of symmetric beat kinematics in individual cilia and random stroke phase between neighboring cilia may result in enhanced fluid mixing, but no net transport. To test this hypothesis computationally, we developed a carpet model consisting of discrete cilia, where the beat kinematics of each cilium are adapted from empirical measurements (Fig. 2G and Fig. S8). We considered three modes of phase coordination: synchronous activity with no phase differences (SYNC), metachronal beating with a phase difference of 45° between neighboring cilia (META) (34), and random phase coordination, where each cilium is randomly assigned a phase between 0° and 360° (RAND) (Fig. 5D). Solving for the resulting flow fields, we found three distinct average patterns: specifically, zero net velocity in the SYNC mode, laminar flow in META mode, and vortical flow in RAND mode (Fig. 5E). To investigate the mixing performance of each flow field, we seeded horizontal or vertical strips of nondiffusing particle tracers (Fig. 5F) and let this distribution of particles evolve during multiple cycles of ciliary beat. After 16 cycles, tracer distributions were strikingly different among the three cases: While there is no obvious pattern change in SYNC mode, and limited distortion in META mode, the RAND mode disrupts much of the initial stratification by stretching and folding fluid filaments, a hallmark of so-called chaotic mixing (35). To quantify mixing, we defined a mixing efficiency of
Enhanced molecular mixing in the sheltered zone. (A) SEM of one of the two lateral surfaces of the ciliated organ. Dashed box indicates region where short and long cilia interface, as shown in detail in B. (Scale bar: 80
Particle trajectories in sheltered zone reveal both diffusion-like and directional transport. (A) Particle trajectories in the fast-flowing regions covered by long cilia (Left) and the sheltered zone covered by short cilia (Right, white dashed rectangle). (B) Four particle trajectories recorded in the sheltered zone. Arrows indicate starting point and direction of the trajectories. (C) MSD analysis of the four trajectories shown in B. (D) The initial 100 ms of the four trajectories are used to analyze the contribution of diffusion. (E) The mean MSD (dashed line) of the first 100 ms is approximated by the linear trend MSD
Computation of fluid transport by different cilia stroke kinematics. A–C, Left show asymmetric stroke kinematics of cilia in the rabbit small airway (9) while A–C, Right show symmetric stroke kinematics of the short cilia of the squid. (A) Stroke cycle. (B) Normalized flow velocities at end of the effective stroke (Top) and at end of the recovery stroke (Bottom). (C) Flow rate over one stroke cycle. Note that only the asymmetric stroke cycle (Left) generates a net directional flow. (D) Flow displacement field of an array of short squid cilia with a rigid stroke cycle and in RAND mode showing the divergence of particle trajectories. The colors represent the magnitudes of the displacement per stroke cycle while the arrows denote the directions. Two seeded particles that are initially in close proximity segregate over the course of 16 stroke cycles. This behavior results in overall mixing of the fluid. (E) The average flow field becomes more uniform and the mixing performance decays as we move farther from the cilia (x > 1). (F) the mixing pattern of an initially vertically stratified field after 16 cycles.
We then measured fluid transport in terms of volumetric flow rate
Taken together, these results suggest that a symmetric ciliary beat with a randomized phase achieves chaotic mixing that accelerates molecular transport without generating net fluid transport and effectively doubles the rate of diffusion of biochemical molecules in the kilodalton mass range (37). Such “enhanced” diffusion accelerates the formation of concentration gradients emanating from chemical signal sources, a mechanism exploited in microfluidic devices (40). Specifically, the characteristic time
Mixing without transport has not been previously described in common ciliary arrangements (34), demonstrating the importance of considering individual ciliary beat together with collective organization. In our analyses, it was first important to implement the symmetric stroke cycle, which by itself does not create any net flow because of the time reversibility in low-Reynolds number regimes (38) (Fig. S8). Second, because any flow-generating asymmetry must therefore arise from the activity of multiple cilia, it was necessary to recapitulate random-phase coordination among neighboring cilia. For the squid–vibrio system specifically, these findings add a fluid-mechanical dimension to the symbiont–host dialogue (Fig. S9), and they refute the longstanding assumption that flow generated by ciliary beat would necessarily compromise the formation of biochemical gradients for bacteria–host signaling (31). Taken together, our study has revealed a class of motile cilia with structural and kinematic adaptations that support fluid mixing in a stagnant zone and, hence, extend the known spectrum of ciliary functions.
Discussion
Our finding of different functional modalities of distinct cilia populations on mucus epithelia opens vistas for the understanding of these important subcellular structures in animal biology. It showcases how the impact of ciliated-tissue patterning extends well beyond the tissue surface, where it controls the formation of distinct fluid-mechanical environments. The combinatorial powers of ciliary parameters described in our study, such as beat direction, kinematics, and coordination, suggest a richness of potential scenarios for shaping the extracellular fluid environment at multiple scales to drive tissue homeostasis and remodeling, much as described for other tissue-organizing mechanical forces (44). Indeed, new imaging techniques have recently mapped both structurally distinct populations of cilia and spatiotemporally varying ciliary flow dynamics, in the ventricles of the mouse brain (45, 46). Multiscale analyses of ciliated tissues not only reveal new tissue-level phenomena, but also enable a quantification of their functional roles in different tissue environments. Such analyses require the integration of empirical and computational approaches for studying cilia function, like those developed in this study, as well as for investigating the particular fluid environment, including air and mucus (47).
In addition, our findings provide a mechanism by which ciliated epithelia generate a landscape of different fluid-mechanical microenvironments that support the formation of distinct “biogeographic” sites for the microbiota. Such a spatial series of ecological niches has previously been demonstrated along other epithelia, such as the mammalian gut lining, where tissue morphology and mucus interact to shape discrete microniches, each selecting for characteristic microbial communities important for gut function (48, 49). Furthermore, this study suggests how a microbial pathogen might alter ciliary movement to foster tissue colonization. These pathogens often misappropriate the mechanisms by which a host interacts with its beneficial bacteria, such as using the bacterial surface molecules lipopolysaccharide and peptidoglycan to signal the host (50). Here we have identified a distinct cilia-generated flow that creates a highly localized sheltered zone whose mechanical properties differ markedly from adjacent regions and in which bacterial cells accumulate. While the features of such biomechanical environments may have evolved to foster interaction with the beneficial microbiota, they may also be conscripted, or created de novo, by pathogens. For example, the human airway pathogen Bordetella spp. releases ciliostatic compounds, locally reducing ciliary beat and creating a micromechanical niche that favors pathogen attachment (51).
In conclusion, this study demonstrates that internalized ciliated epithelia can perform diverse and intricate fluid-transport tasks rivaling those of the externally ciliated surfaces of aquatic animals (7, 22, 52). Importantly, we have developed a theoretical and empirical framework for investigating the functional complexity of mucociliary epithelia. This framework will inform efforts to identify novel roles for cilia-generated flow and mechanical landscapes in human tissues and increase our appreciation of the functional scope of these important subcellular structures in animal biology.
Detailed methods and raw video recordings are available in Supporting Information.
Animal Husbandry.
Juvenile E. scolopes were obtained immediately after hatching from breeding colonies maintained in artificial seawater (ASW), as described previously (53). Between hatching and the start of experimental procedures, the hatchling squid were kept individually in 5 mL of filter-sterilized ASW.
Bacterial Culture.
GFP or RFP plasmid carrying V. fischeri wild-type strain ES114 was grown at 25 °C in tryptone-enriched ASW medium to the midlogarithmic phase to ensure bacterial motility. Cell density was estimated using optical density (OD) at 600 nm.
Particle and Bacteria Capture at the Ciliated Surface.
Squid were placed individually in 5 mL of filter-sterilized ASW previously exposed to adult, colonized animals and hence containing mucus-release–stimulating bacterial peptidoglycan (PGN) (27) but no bacteria. V. fischeri and fluorescent polystyrene beads with 1-
Statistical Analysis of Particle Capture.
Capture data of particles were tested for the null hypothesis that the datasets were drawn from continuous distributions with equal medians, against the alternative hypothesis that there was an increase in the median capture rate for smaller particles. We conducted a one-sided, nonparametric statistical test (Wilcoxon rank sum test) at a
Confocal Imaging.
For preparation, the animals were rinsed in ASW and incubated for 10 min with 10
Flow Visualization and Analysis.
Unless indicated otherwise, for quantitative flow analysis, yellow-green fluorescent polystyrene microbeads (ex/em 505/515 nm; 1
For flow visualization, we used a portable laser with 473-nm wavelength (Aquarius Pro; Laserglow Technologies) diverged into a plane through a plano-concave cylindrical lens (focal length f = −4; Thorlabs). The laser was used to illuminate an
For ex vivo visualization and analysis of the ciliary currents, the light organ was excised and placed in ASW with suspended bacteria or microbeads. Video recordings of V. fischeri were taken at lower magnification than for particles because the GFP-fluorescent bacteria emit less light than light-scattering particles, hence limiting spatial resolution and accuracy of the tracked trajectories. For qualitative analysis of the flow, the ink sac embedded in the light organ was pierced using a microinjection needle, allowing the escaped ink to form a streakline that visualizes the oscillating nature of the flow field generated by metachronal ciliary beat (34) (Fig. 4A). Particle motions in the sheltered compartment were analyzed using mean-square displacement (MSD) analysis of the particle trajectories in 2D with the Matlab-class msdanalyzer (58).
For in vivo visualization and analysis of the ciliary currents, the animals were prepared and imaged with confocal microscopy as described above. Fluorescent particles or bacteria were added to the preparation at a final concentration of
For measuring in vivo inhalation flow, the intact and nonanesthetized animals were placed ventral side up in a plastic dish containing ASW with
Model of Particle Capture by Direct Interception.
We first assessed which of the common mechanisms underlying the capture of nonmoving particles at filter feeding structures would be most effective for the capture of microparticles at the squid appendages. These mechanisms include direct interception, inertial impaction, diffusion, and gravitational deposition of particles, and their relative importance in a given system can be assessed by computing previously described nondimensional indexes (5). Using these indexes, we estimated the relative contribution of each mechanism to the capture of relevant particle types from the mantle-driven flow (26). Here, we assume the following conditions: Temperature T = 20 °C, density of seawater
Based on these results, we focused on estimating the effect of direct interception and ignored the other previously described capture mechanisms. The theoretical capture rate of particles by direct interception from the mantle-driven flow at the ciliated appendage was estimated by adapting a computational fluid dynamic (CFD) model for aquatic filter feeders (25). Briefly, the model predicts the capture rate of suspended particles by a cylindrical structure in a uniform flow. This model is valid for low to intermediate Reynolds numbers at the cylindrical structure, i.e.,
SEM.
For SEM, animals were first anesthetized in 2% (vol/vol) ethanol in ASW. Before fixation, the mantle was cut open near the light organ to expose the light organ to the fixative agent. Then, the animals were rapidly fixed in 1% (wt/vol) osmium tetroxide in marine PBS (mPBS) (50 mm sodium phosphate, 0.45 M sodium chloride, pH 7.4). After 30 min of incubation, this was followed by fixation in 4% paraformaldehyde in mPBS. Fixation was allowed to proceed for 12–14 h at room temperature. Animals were then washed twice for 10 min in mPBS and dehydrated through an ethanol series (53). The samples were dried and gold sputter coated (Tousimis Samdri 780 critical point drier; SeeVac Auto conductavac IV), mounted on stubs, and viewed with a Hitachi S-570 LaB6 scanning electron microscope. In the digitized images, light-organ dimensions were measured using ImageJ.
High-Speed Video Recording.
For high-speed imaging of ciliary beat, the animals were first anesthetized in a 2% (vol/vol) solution of ethanol in ASW. Then, the light organ was either imaged inside the animal through a window cut into the mantle (in vivo) or excised (ex vivo). Samples were placed in a plastic dish or depression slide with filtered ASW. For imaging of cilia–particle and cilia–bacteria interactions, microspheres or bacteria were added to a final concentration of
Kinematic Analysis of Ciliary Beat.
Ciliary beat frequency (CBF) was determined from phase-contrast movie recordings of ciliary activity. An automated Matlab-based algorithm we have recently developed for in vitro analysis of ciliary beat (59) was used to detect regions of interest (ROI), i.e., regions where ciliary activity is present. In these ROI, the intensity value of each pixel over time was bandwidth filtered, windowed, and analyzed using fast Fourier transform (FFT). The dominant frequency of the average power spectrum over all pixels in a given ROI corresponds to the CBF.
Kymograph analysis was performed using ImageJ. Beat kinematics of single cilia were determined by manually tracing individual cilia in subsequent frames of high-speed movie recordings of the ciliated surface. The traces were centered and overlaid to visualize the motion of the entire beat cycle.
Computational Model of the Vortical Flow Zone.
We used a 2D continuum model to numerically study the ciliated appendages. Two cylinders of diameter
At zero Reynolds number, the fluid motion is governed by the Stokes equation
To investigate how particles with different sizes move in the flow field generated by the ciliated appendices, we considered the model proposed in ref. 39. In the model, a particle of diameter
Computational Model of the Sheltered Zone.
We considered a cluster of cilia whose base points are rooted on the surface (
To study the mixing effects of the short cilia with different phase coordination, we uniformly seeded the fluid domain near the cilia with passive tracers of two different colors in a 1:1 ratio. We considered two cases of initial seeding: horizontal strips and vertical strips. We computed the displacement field
We considered three different cases of this model: (i) cilia beating in synchrony (SYNC); (ii) cilia beating in metachronal waves, in which case the phase difference between the neighboring cilia in the
For these computations, each cilium was discretized into 20 regularized Stokeslets uniformly distributed along the centerline and the regularization parameter was chosen to be 0.05 to match a typical radius-to-length ratio. We prescribed the motion of each cilium as a rigid bar beating in the
Computational Model of Transport by Single Cilium.
We compared the fluid transport generated by a single cilium with different beating patterns (Fig. S8 A–C). The beating pattern of a single cilium was studied by Eloy and Lauga (62), who found that for optimal transport the cilium exhibited a small curvature during the effective stroke and large curvature during the recovery stroke. Here, we used an asymmetric beating pattern adapted from the rabbit tracheal cilia (9), which exhibits a nearly straight effective stroke and a curly recovery stroke. The symmetric beating pattern was extracted from high-speed video recordings of the short cilia in the squid ciliated organ (Movie S2).
Using the regularized Stokeslet method with image distributions described in the previous section, we derived the flow velocity field for each of the two beating patterns. We further integrated the flow generated by the single cilium over one cycle to evaluate the transport efficacies of different beating patterns quantitatively.
Acknowledgments
We thank B. Boettner, S. Fraser, and M. Kinzel for helpful discussion of the manuscript. Funding was provided by National Institutes of Health grants from The National Institute of Allergy and Infectious Diseases (AI050661) (to M.M.-N.) and Office of Research Infrastructure Programs (RR012294/OD011024) (to E.G.R.), by the Gordon & Betty Moore Foundation (3396) (to E.G.R.), and by a National Science Foundation Integrated NSF Support Promoting Interdisciplinary Research and Education Grant (NSF-MCB1608744) (to M.M.-N., E.G.R., and E. Kanso).
Footnotes
↵1J.C.N. and H.G. contributed equally to this work.
- ↵2To whom correspondence may be addressed. Email: kanso{at}usc.edu or mcfallng{at}hawaii.edu.
This contribution is part of the special series of Inaugural Articles by members of the National Academy of Sciences elected in 2014.
Author contributions: J.C.N., H.G., E.G.R., J.O.D., E. Kanso, and M.M.-N. designed research; J.C.N., H.G., and E. Kanso performed research; J.C.N., H.G., E. Kanso, and M.M.-N. contributed new reagents/analytic tools; J.C.N., E. Koch, E.A.C.H.-H., and J.C.H. conducted biological imaging; J.C.N., H.G., E.G.R., J.O.D., E. Kanso, and M.M.-N. analyzed data; and J.C.N., H.G., E.G.R., E. Kanso, and M.M.-N. wrote the paper.
Reviewers: C.E., Institut de Recherche sur les Phénomènes Hors Equilibre; and M.A.R.K., University of California, Berkeley.
Conflict of interest statement: Coauthor E.A.C.H.-H. and reviewer M.A.R.K. are both affiliated with the University of California, Berkeley, but in different departments.
See Profile on page 9494.
This article contains supporting information online at www.pnas.org/lookup/suppl/doi:10.1073/pnas.1706926114/-/DCSupplemental.
References
- ↵.
- Choksi SP,
- Lauter G,
- Swoboda P,
- Roy S
- ↵.
- Shah AS,
- Ben-Shahar Y,
- Moninger TO,
- Kline JN,
- Welsh MJ
- ↵
- ↵
- ↵
- ↵.
- Riisgard HU,
- Larsen PS
- ↵.
- Shapiro OH, et al.
- ↵
- ↵
- ↵.
- Button B, et al.
- ↵
- ↵
- ↵
- ↵
- ↵.
- Gensollen T,
- Iyer SS,
- Kasper DL,
- Blumberg RS
- ↵
- ↵.
- Nyholm SV,
- Stabb EV,
- Ruby EG,
- McFall-Ngai MJ
- ↵
- ↵
- ↵.
- Reynolds RA,
- Stramski D,
- Wright VM,
- Wožniak SB
- ↵
- ↵.
- Pepper RE,
- Roper M,
- Ryu S,
- Matsudaira P,
- Stone HA
- ↵.
- Riisgård H,
- Larsen P
- ↵
- ↵.
- Humphries S
- ↵.
- Shimeta J, et al.
- ↵.
- Nyholm SV,
- Deplancke B,
- Gaskins HR,
- Apicella MA,
- McFall-Ngai MJ
- ↵
- ↵.
- Nakhleh N, et al.
- ↵.
- Werner ME, et al.
- ↵.
- Mandel MJ, et al.
- ↵
- ↵
- ↵.
- Guo H,
- Nawroth J,
- Ding Y,
- Kanso E
- ↵.
- Jones SW,
- Thomas OM,
- Aref H
- ↵.
- Stone ZB,
- Stone HA
- ↵.
- Ding Y,
- Nawroth J,
- McFall-Ngai M,
- Kanso E
- ↵
- ↵.
- Ding Y,
- Kanso E
- ↵.
- Stroock AD, et al.
- ↵
- ↵.
- Cornforth DM, et al.
- ↵.
- Kim MK,
- Ingremeau F,
- Zhao A,
- Bassler BL,
- Stone HA
- ↵
- ↵.
- Liu T,
- Jin X,
- Prasad RM,
- Sari Y,
- Nauli SM
- ↵.
- Faubel R,
- Westendorf C,
- Bodenschatz E,
- Eichele G
- ↵.
- Vasquez PA,
- Jin Y,
- Palmer E,
- Hill D,
- Forest MG
- ↵.
- Donaldson GP,
- Lee SM,
- Mazmanian SK
- ↵.
- Kim HJ,
- Li H,
- Collins JJ,
- Ingber DE
- ↵
- ↵
- ↵
- ↵
- ↵.
- Tropea C,
- Yarin AL
- ↵
- ↵
- ↵
- ↵.
- Tarantino N, et al.
- ↵.
- Benam KH, et al.
- ↵.
- Cortez R
- ↵
- ↵
- ↵.
- Miller CC
Citation Manager Formats
Article Classifications
- Biological Sciences
- Microbiology
- Physical Sciences
- Biophysics and Computational Biology
See related content:
- Profile of Margaret J. McFall-Ngai- Aug 22, 2017