Douglas R Brumley1,2, Nicolas Bruot3,4, Jurij Kotar4, Raymond E Goldstein5, Pietro Cicuta4, Marco Polin6. 1. Ralph M. Parsons Laboratory, Department of Civil and Environmental Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA. 2. Department of Civil, Environmental and Geomatic Engineering, ETH Zürich, 8093 Zürich, Switzerland. 3. Institute of Industrial Science, University of Tokyo, 4-6-1 Komaba, Meguro-ku, Tokyo 153-8505, Japan. 4. Cavendish Laboratory, University of Cambridge, Cambridge CB3 0HE, United Kingdom. 5. Department of Applied Mathematics and Theoretical Physics, University of Cambridge, Centre for Mathematical Sciences, Wilberforce Road, Cambridge CB3 0WA, United Kingdom. 6. Physics Department, University of Warwick, Gibbet Hill Road, Coventry CV4 7AL, United Kingdom.
Abstract
Eukaryotic cilia and flagella are chemo-mechanical oscillators capable of generating long-range coordinated motions known as metachronal waves. Pair synchronization is a fundamental requirement for these collective dynamics, but it is generally not sufficient for collective phase-locking, chiefly due to the effect of long-range interactions. Here we explore experimentally and numerically a minimal model for a ciliated surface: hydrodynamically coupled oscillators rotating above a no-slip plane. Increasing their distance from the wall profoundly affects the global dynamics, due to variations in hydrodynamic interaction range. The array undergoes a transition from a traveling wave to either a steady chevron pattern or one punctuated by periodic phase defects. Within the transition between these regimes the system displays behavior reminiscent of chimera states.
Eukaryotic cilia and flagella are chemo-mechanical oscillators capable of generating long-range coordinated motions known as metachronal waves. Pair synchronization is a fundamental requirement for these collective dynamics, but it is generally not sufficient for collective phase-locking, chiefly due to the effect of long-range interactions. Here we explore experimentally and numerically a minimal model for a ciliated surface: hydrodynamically coupled oscillators rotating above a no-slip plane. Increasing their distance from the wall profoundly affects the global dynamics, due to variations in hydrodynamic interaction range. The array undergoes a transition from a traveling wave to either a steady chevron pattern or one punctuated by periodic phase defects. Within the transition between these regimes the system displays behavior reminiscent of chimera states.
The ability of ensembles of oscillators to achieve collective motions is
fundamental in biological processes ranging from the initiation of heartbeats to the
motility of microorganisms. The emergent properties of coupled oscillators can vary
dramatically depending on the intrinsic properties of the oscillators and the nature of
the coupling between them [1]. Flashing fireflies
equally and instantaneously coupled to one another [2] can support very different behaviors to chemical micro-oscillators, which
are coupled only locally, and subject to time delays [3].Eukaryotic cilia and flagella are chemo-mechanical oscillators that generate a
variety of collective motions, which can be quantified with high-speed imaging in
microfluidic environments [4-6]. The molecular biology of these internally driven
filaments is virtually identical in green algae [5], protists [7], and humans [8], and the flows they generate fulfill crucial
roles in development, motility, sensing, and transport. When close together, the mutual
interaction between their oscillatory flow fields can cause them to beat in synchrony
[9], and larger ensembles of flagella
demonstrate striking collective motions in the form of metachronal waves (MWs) [10-13], akin to the “Mexican wave” propagating around a packed
stadium. Many surrogate models for flagellar dynamics have been proposed [13-24], typically with a set geometry that fixes the range and coupling between
oscillators.Here we relax this condition and study a linear array of colloidal oscillators
[25] driven in circular trajectories at a
controllable height above a no-slip wall. Originally introduced as a mathematically
convenient minimal model for synchronization at low Reynolds numbers [15], colloidal rotors have been experimentally
shown to reproduce the time-dependent flow field associated with a beating flagellum
down to distances comparable to its size (~10 μm) [9,26]. When
generalized to include waveform flexibility [14,27,28] they are also capable of capturing interflagellar synchronization in
bulk [9]. The system of colloidal rotors studied
here can be modified continuously from being primarily coupled through nearest neighbors
to a regime involving significant long-range interactions. As a function of rotor
properties, a traveling wave found at small heights becomes either a chevron pattern or
is punctuated by phase defects at large ones. The transition is not a gradual morphing
between the two profiles, but rather a process involving generation and propagation of
defects along the strip, where phase-locked and non-phase-locked subgroups of
oscillators can coexist. A behavior arising from long-range interactions whose amplitude
is modulated by the distance from the wall [18],
these dynamics are reminiscent of chimera states, in which oscillators split into
phase-locked and desynchronized clusters [29,30].In our experiments, silica colloids of radius a = 1.74
μm (BangsLab, USA) suspended in a water-glycerol solution of
viscosity μ = 6 mPas within a
150-μm-thick sample, are captured and driven by
feedback-controlled time-shared (20 kHz) optical tweezers (OTs) based on acousto-optical
deflection of a 1064-nm-wavelength diode-pumped solid-state laser (CrystaLaser
IRCL-2W-1064) as previously described [31,32]. The OTs describe a planar array of circular
trajectories [Fig. 1(a)] of radius
R = 1.59 μm and center-to-center separation
ℓ = 9.19 μm, a distance
h above the sample bottom, with 4.2(4) ⩽ h
⩽ 51.7(4) μm. This configuration, which reflects the
capabilities and limitations of our OT setup, is similar to arrays of nodal cilia, but
differs from another common situation where the ciliary beating plane is perpendicular
to an organism’s surface.
Fig. 1
Experimental setup and results. (a) Microspheres of radius a =
1.74 μm, situated at a distance h above
a no-slip boundary are driven by time-sharing optical tweezers in circular
trajectories of radius R = 1.59 μm and
center-to-center separation ℓ = 9.19
μm. (b) Average phase drift
for a rotor pair vs detuning D
for h = 4.2 (),
6.7 (), 11.7 (),
16.7 (), 31.7 (),
51.7 () μm. (c) Phase
diagram showing experimental regions of synchrony (blue) and drift (red), the
boundary from hydrodynamic simulations (dashed), and theory from Eq. (2) (solid).
The oscillators are imaged using a Nikon inverted Eclipse Ti-E with a 60×
Nikon Plan Apo VC water immersion objective (NA = 1.20), and recorded for up to 1200 s
using an AVT Marlin F131B CMOS camera set at 229 fps. The rotor positions are measured
using an algorithm that correlates the image intensity I (x,
y) with a rotationally symmetric kernel image K(x,
y) constructed from a real colloid. By fitting the two-dimensional (2D)
cross-correlation function
C(x0,y0) =
∑(
I (x,y) × K(x
− x0, y −
y0) with a 2D parabola and maximizing this function, the
rotor positions (x0, y0) are
extracted with subpixel resolution and used to track their phases
{ϕ(t)} over time [Fig. 1(a)].The rapid feedback loop between colloid and trap positions facilitates the
arbitrary placement of the OTs with respect to the colloidal particles. The trap
positions are maintained at a constant radius R and fixed angular
distance ahead of the colloids. Consequently, a colloidal particle on the
ith trajectory (i ∈ {0, …,
N − 1}) experiences a radial harmonic potential with spring
constant λ = 2.06 ± 0.06 pN/μm
resisting excursions from the prescribed radius, and a constant tangential force of
magnitude F =
FdrD
leading to rotation. The period of rotation is therefore not fixed, and it is this
degree of freedom that permits synchronization of interacting particles. The choice of
λ reflects estimates of the bending rigidity of flagella,
κ ~ 4 × 10−22 N
m2, and their length, L. From λ
= κ/L3 [14],
and for typical values of L, values of should represent typical flagella. Unavoidable delays in the OT’s
feedback response introduce a mismatch between the parameters used in experiments and
simulations, which is corrected by increasing the simulation value of
λ by a constant factor γ relative to
the experimental one. The previously reported value of γ = 2.21
[32] is adopted throughout this paper, which
results in quantitative agreement of simulations with the present experiments [see Fig. 1(c)].Isolated oscillators rotate with a height-dependent angular velocity
ω =
F0ζ,
where ζ0 = 6π μa is
the sphere’s bulk drag coefficient, and accounts for the presence of the wall [33]. Experimental results are compared with
deterministic hydrodynamic simulations in which colloids are treated as point-like
particles above a no-slip boundary, and therefore coupled through the so-called
“Blake tensor” [11,34]. Before each experiment we calibrate
Fdr ≃ 2.23 pN (see Supplemental Material [35]; typical variation ±2%).
D ≠ 1 is used to break left-right symmetry along the chain
and induce a stable traveling wave for small h [11]. For the detuning adopted here, D = 1.01, the
period of individual oscillators varies between τ ~ 0.5 s
and ~1 s across the explored range of h.Consider first two rotors separated by a distance ℓ. For
rotors with instantaneous positions {} and
velocities {}, the hydrodynamic drag on the
ith rotor is given by where is the net external force acting on the
jth sphere and
G(,)
is the Green’s function in the presence of the no-slip wall. For identical rotors
(detuning D = 1), hydrodynamic coupling eventually leads to synchrony
provided λ < ∞, by perturbing the angular
velocities of the two rotors so that the leading and lagging rotors become slower and
faster respectively [13,14]. The timescale for synchronization is proportional to the
spring constant λ [see Eq. (1)] and also depends on the strength of hydrodynamic interactions
between rotors, which is a function of height h and spacing
ℓ. The dynamics become richer if a discrepancy between the
rotor’s intrinsic frequencies is introduced (D ≠ 1), for
then the coupling must be sufficiently strong to overcome the natural tendency for the
rotor’s phase difference χ =
ϕ1 − ϕ0
to drift.Bifurcation plots in Fig. 1(b) show, for
different h, the average phase drift between two oscillators as a
function of D. The behavior is typical of a saddle-node bifurcation:
the oscillators phase-lock until D reaches a critical value
D*(h) and then drift with a monotonically
increasing speed. D*(h) increases with
h, reflecting the strengthening of inter-rotor hydrodynamic
coupling with increasing distance from the wall. The phase-locking behavior is
summarized in Fig. 1(c), where the experimental
synchronization boundary is based on a threshold of five slips in the whole experiment
The results of individual experiments are classified
based on this threshold, and are represented as either red (drift) or blue
(synchronized) points in Fig. 1(c). As
h is increased, the rotor pair moves deeper into the synchronized
region: the coupling between the two strengthens due to lower hydrodynamic screening
from the wall, leading to an enhanced stability of the synchronized state. This is
reproduced by simulations [Fig. 1(c)] up to small
shift in D, which could come from the finite value of
a/h and experimental noise. In the limit a,R
≪ ℓ, the evolution of the phase difference
χ = ϕ1 −
ϕ0 can be derived by a generalization of previous
arguments [14,35]. As phase-locking is slow compared to the rotation period, we average
over this fast timescale and find where From Eq.
(1), the average phase drift for non-phase-locked states reads Given the functional form of the frequency detuning,
F =
FdrD,
Eq. (2) can be solved explicitly to
yield the critical detuning D*(h) [solid line in Fig. 1(c)]. The theoretical and numerical solutions
for the boundary in Fig. 1(c) slightly under- and
overestimate the data, respectively, owing to neglect of temporal variations in the
interparticle spacing and the finite size of the beads, respectively. Both also neglect
thermal fluctuations.We now turn to the dynamics of a linear array of six rotors, with the
ith rotor centered at =
(il,0,h). This is the longest controllable chain
with our active-feedback-based OTs. Linear arrays of colloidal oscillators have been
shown to capture the dynamics of two-dimensional arrays [13], so this simplified geometry will be the focus here. The dynamics are
studied experimentally as a function of h, but numerical simulations
allow wider exploration of parameters, including changes in the radial stiffness
λ, which governs the coupling strength [9,11,13,14,32] as in Eq. (1). In both experiments and simulations we introduce a mild frequency
bias D = 1.01, typical also of Volvox colonies [13], which breaks the translational symmetry and
induces a MW for h ≲ 10 μm. At all
heights studied, this value of D is deep within the synchronized region
of parameter space for two rotors.Figure 2(a) shows that at
h = 6.7(4) μm the rotors phase-lock in a
stable MW whose direction is set by the frequency bias. With increasing
h, defects (phase slips) emerge, giving rise to a net drift in the
cumulative phase difference between rotors at opposite ends of the chain. Phase defects
always propagate in the direction of the fastest oscillator. At these intermediate
heights, the phase profile also displays “wobbles,” perturbations to the
MW that are not accompanied by a phase defect. Numerical results shown in Fig. 2(b) capture the traveling wave at
h = 5 μm, the presence of defects and their
propagation direction, and wobbles at larger heights. At the largest height,
h = 50 μm, defects no longer propagate
through the chain, and rotors 3–5 remain phase-locked.
Fig. 2
Results for the linear array of driven colloidal oscillators, shown schematically
in grey (not to scale). (a) Kymographs showing sin
ϕ at three heights above the wall. With
increasing h, the traveling wave becomes frustrated, with the
introduction of wobbles (arrows) and phase defects (circles). (b) Numerical
results from model. (c) Fraction of total coupling corresponding to interacting
with different neighbors, as a function of h. The shaded red
region represents the experimental parameter regime.
The phase dynamics of wobbles and defects are shown in Fig. 3(a) for h = 11.7(4)
μm. The first 25 seconds of the time series show fluctuations in
ϕ −
ϕ0 (wobbles), even while the system is frequency
locked. Fluctuations start at the first oscillator pair and travel unidirectionally
along the chain [Fig. 3(b)] with a preserved,
soliton-like signature [36]. Occasionally, they
terminate within the chain with a slip [Fig. 3(a)];
these are the phase defects observed in kymographs. Both wobbles and defects are
characterized by initial excursions of amplitude W and recurrence time
τ [Fig. 3(c)], which
depend on h [Figs. 3(d) and 3(e)].
The typical time τ ~ 10
〈T〉 (where 〈T〉 ≃ 1
s is the average period) depends less strongly on h than does
W, which shows a pronounced growth [Fig. 3(d)], mirroring the increased probability that a wobble will terminate
in a slip within the chain, causing a defect [Fig.
3(f)]. Although their position can vary, defects tend to cluster, in this
case at the middle of the chain (position i = 2), as seen also in
simulations of longer chains [35].
Fig. 3
Experimental phase dynamics. (a),(b) Phase difference relative to the first
rotor, ϕ −
ϕ0, at h = 11.7
μm. (c) Wobbles are characterized by their magnitude
W (radians) and timescale
τ/〈T〉 (normalized by
rotor period), shown as a function of h in panels (d) and (e).
(f) Probability that a propagating wobble ends at rotor i,
resulting in a slip.
The hydrodynamic coupling between two rotors increases monotonically with
h; for an isolated pair, this manifests in more robust
synchronization at larger heights. For a chain of rotors, increasing h
has the reverse effect, disrupting the stable MW with wobbles and punctuating it with
periodic phase defects (Fig. 2). The hydrodynamic
coupling between every pair of rotors in the chain grows as h is
increased. For just two rotors, Eq. (1)
shows that equivalent changes to the hydrodynamic coupling can be achieved through
modification of the mean interparticle separation l. For the chain of
six rotors, in which longer range hydrodynamic interactions also occur, changes to
h and l are no longer equivalent.The peculiar dynamics observed arise from a change in the relative contributions
of interactions with different neighbors. The no-slip wall has the effect of screening
the hydrodynamic interactions in a way that qualitatively changes as a function of
β = 2h/ℓ. This is an important
determinant of MW stability, as observed also in simulations of colloidal
“rowers” [18]. Figure 2(c) shows the magnitude of the coupling of a given
oscillator with its nth nearest neighbor, estimated with Eq. (1), normalized by the total
interaction strength with the first five neighbors. Although all pairwise couplings grow
monotonically with h, the relative magnitude of the nearest neighbor
interactions actually diminishes. Conversely, the relative importance of all others
increases with h. Hydrodynamic disturbances parallel to the wall decay
as u ~ r−
where j = 1 and 3 represent the far (β ≫
1) and near (β ≪ 1) asymptotic limits [18]. For the end rotor the magnitude of the
coupling with the nth nearest neighbor, normalized by the total
coupling strength, is For β ≪ 1 the
interactions are dominated by nearest neighbor, with S(1) = 0.84, while
for β ≫ 1, S(1) = 0.44 [see the black
curve in Fig. 2(c)]. We test the hypothesis that
the breakdown of the traveling wave is due to long-range hydrodynamic interactions
through simulations in which interactions are truncated at nearest neighbors, and find
the abundance of defects is significantly reduced. Importantly, the dynamics are nearly
insensitive to h, with a maximum relative variation in end-to-end drift
speed of just 3% between h = 5 μm and 1000
μm (Fig. 4) [35].
Fig. 4
(a) Average phase drift per beat between end oscillators (measured in beats) as a
function of height above the wall and radial spring stiffness. Shown also are
four representative kymographs. (b) Time-averaged amplitude
Ā and (c) angle of the complex order parameter
Z =
Ae. The axes are the
same as in (a). (d) Same as (a) but with hydrodynamic interactions truncated to
nearest neighbor. Parameters used include a = 1.74
μm, ℓ = 9.19
μm, R = 1.59
μm, and viscosity μ = 6
mPas. Simulations correspond to 0 ≤ t ≤ 2000 s.
The dashed white line shows the value of λ corresponding
to Fig. 2. Note the different color scales
used throughout.
Additional numerical simulations permit the wider exploration of parameter
space. The range of λ values studied here corresponds to the
estimated values λ = κ/L3
based upon ciliary lengths of L ~ 4−10
μm [14]. Figure 4(a) shows the average end-to-end phase drift
per beat as a function of λ and h, and enables
analysis of many numerical simulations without looking at the individual kymographs. The
area of solid blue corresponds to specific parameter combinations for which complete
phase-locking occurs. However, from the drift alone, one cannot distinguish between a
linear traveling wave ③ and a chevron phase profile ①. For this we compute
the complex order parameter where χ =
ϕ −
ϕ [18,37]. Note the use of the pairwise
phase differences, not the individual rotor phases. Looking at the mean value of
[see Fig. 4(c)],
the region of parameter space corresponding to complete phase-locking can be decomposed
into chevron and MW regions. Using the average values
Ā and for t > 200 s [Figs. 4(b) and 4(c)], we see that as
h is increased at the experimental value of
λ (white dotted line), the stable traveling wave at small
h shifts to a profile with defects and wobbles, initially along the
whole chain, and then localized to one-half of the chain with the remaining three
oscillators constantly phase-locked.At values of λ smaller than the experimental one,
however, we observe qualitatively different dynamics. For λ
≲ 2.5 pN/μm, the pattern morphs continuously between
different types of complete synchronization as h is increased, going
from a MW ③ to a chevron-like pattern ①. These transitions happen without
the emergence of defects [11]. For 2.5 <
λ < 3 pN/μm the system shows
reentrant behavior with defects only at intermediate heights, separating a MW region
from a chevron-like region. The order parameter angle [Fig. 4(c)]
identifies clearly the stable MW (yellow/orange) and chevron (dark blue) regions of
parameter space. For a fixed h ≳ 50 μm,
increasing λ results in a monotonic decrease in
Ā owing to the reduced rotor compliance. Conversely, the
end-to-end phase drift exhibits a strong peak around λ = 4.5
pN/μm, where the rotors slip approximately one beat in every
five, despite an intrinsic frequency difference of just 5%. These nontrivial dynamics
emerge due to the combination of phase slips induced by long-range interactions, and
rapid healing of phase defects through orbit compliance. The complete absence of these
features from the simulations with nearest neighbor coupling alone [Fig. 4(d)] highlights the role played by competition between
interactions at different ranges. Changing h is then a simple and
accessible way to modulate their relative strength (see Fig. 2).Large arrays of cilia are synonymous with no-slip boundaries, and in many cases,
the spacing between these organelles is comparable to their length [13], so that effectively
h/ℓ ~ 1 [see Fig. 4(a)]. Our results suggest that flagella of
Volvox may then be balancing the need to extend out into the fluid
enough to generate a vigorous thrust, with the screening of long-rage hydrodynamic
interactions necessary to stabilize MWs on the colony surface. As a result, ensembles of
flagella in Volvox [11] (but see
also numerical simulations [22]) may operate in a
regime naturally prone to the emergence of metachronal phase defects, which are indeed
observed experimentally [13].
Authors: Jurij Kotar; Luke Debono; Nicolas Bruot; Stuart Box; David Phillips; Stephen Simpson; Simon Hanna; Pietro Cicuta Journal: Phys Rev Lett Date: 2013-11-27 Impact factor: 9.161
Authors: Erik Andreas Martens; Shashi Thutupalli; Antoine Fourrière; Oskar Hallatschek Journal: Proc Natl Acad Sci U S A Date: 2013-06-12 Impact factor: 11.205
Authors: Luigi Feriani; Maya Juenet; Cedar J Fowler; Nicolas Bruot; Maurizio Chioccioli; Steven M Holland; Clare E Bryant; Pietro Cicuta Journal: Biophys J Date: 2017-07-11 Impact factor: 4.033