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* Rowland Institute at Harvard, Cambridge, Massachusetts 02142; and
Division of Engineering, Brown University, Providence, Rhode Island 02192
Correspondence: Address reprint requests to Howard C. Berg, E-mail: hberg{at}biosun.harvard.edu.
| ABSTRACT |
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| INTRODUCTION |
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The flagellum is a propulsive organelle that includes a reversible rotary motor embedded in the cell wall, and a filament that extends into the external medium (Berg, 2003
). The filament is a long (
10 µm), thin (
20 nm) helix (2.5 µm pitch, 0.5 µm diameter) that turns at speeds of
100 Hz. Motile bacteria differ in their styles of flagellation (Leifson, 1960
). One such style is peritrichous flagellation, such as in Escherichia coli, Salmonella typhimurium, and Serratia marcescens. The flagella of these cells are distributed randomly over the cell surface, and each flagellar motor rotates independently of the others. Hydrodynamic interactions among flagella cause them to coordinate, coalescing and "bundling" behind the cell during swimming. These bacteria have more than one lifestyle: they can live individually as freely swimming single cells in fluids, or cooperatively as swarms of cells on surfaces (for a review, see Fraser and Hughes (1999)
). Swarms develop when cells are grown in a rich medium on a soft agar surface. The cells lengthen, produce more flagella, and move in groups that are packed side by side in dense layers, one or several cells thick (Harshey, 1994
; Henrichsen, 1972
). We exploit swarmer cells of S. marcescens (Alberti and Harshey, 1990
) as a ready source of microscopic low Reynolds number pumps.
Bacteria are equipped with exquisitely sensitive detectors of physical or chemical sensory stimuli that modulate the direction of rotation of their flagellar motors (Falke et al., 1997
). These detectors can be selected, or even designed, to respond to (for example) light of specific wavelengths (Jung et al., 2001
) or to specific chemical substances (Looger et al., 2003
). Bacteria have some advantages over conventional micro- or nanofabricated devices. They can live on small amounts of simple nutrients, e.g., sugars, so no external power source is needed. They self replicate, so no multistep lithographic fabrication is required. Thus, it may eventually be possible to combine a biological sensor and fluid actuator in a single small, cheap, self-replicating package. This study was designed to learn how well the flagella of groups of bacteria might move fluid in a microscopic environment.
| METHODS |
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Carpet assessment
Cell attachment was evaluated using a Nikon (Tokyo, Japan) Optiphot microscope equipped with a 40x phase objective (Fig. 2, A and B). Bacterial filaments were visualized by creating a carpet of labeled and unlabeled bacteria: S. marcescens were washed from a swarm plate, labeled (Turner et al., 2000
) using Cy3 dye (PA23001, Amersham Biosciences, Piscataway, NJ), added back to the swarm, incubated 15 min at 30°C, and then blotted. The flagellar filaments were imaged (Turner et al., 2000
) with the coverslip as part of a flow cell (see below, "Fluid-flow assays", and Fig. 2, C and D). Filament rotation rates were determined from a frame-by-frame analysis of high-speed video from a 500-Hz low-light-level camera (HSC-500 x2, JC Labs, Mountain View, CA) (L.T. and H.C.B., unpublished).
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For motion assays, a 1:50 dilution of 1 µm nominal diameter red fluorescing beads (R0100, Duke Scientific, Palo Alto, CA) was added through the flow-cell input and imaged in epifluorescence mode using mercury arc excitation (TRITC fluorescence cube No. 31002, Chroma Technologies, Brattleboro, VT) and a CCD camera (model 1070, Marshall Electronics, Culver City, CA). Images were recorded (Sony GV-D1000, Sony, Montvale, NJ) and played back for analysis to a Macintosh G3 computer (Apple Computer, Cupertino CA) equipped with an LG3 video board and Scion Image software (both from Scion, Frederick, MD).
Data analysis
Videos of bead motion were divided into 10- or 30-s segments and imported into MATLAB (The MathWorks, Natick, MA) for tracking. Each set of images was thresholded, generally 57 standard deviations above the black background. MATLAB's built-in particle locating routines assigned all contiguous above-threshold pixels to the same "particle", and labeled each disjoint "particle" with a unique index. The centroid of every particle (with area >3 pixels) was tracked frame to frame. A 1 µm bead was assumed to move <2 µm between frames (1/30 s). In any ambiguous situation, the algorithm terminated the existing bead track and started afresh. This technique frequently chopped a single long track into several short tracks (for instance, when a bead dipped below threshold for a single frame), reducing the total number of long tracks available for subsequent analysis. As a result, the statistics for long tracking times are poor, so bead-tracking analysis was stopped at a practical upper limit of 3 s. The 2 µm search radius was chosen just large enough to accept all the observed single-frame displacements, and adjusted when necessary for different bead sizes and data rates.
Alignment parameters
To evaluate the correlation of a vector field (see Fig. 6), we constructed an alignment parameter
and normalized it so that
The average is over all pairs of vectors measured at relative distances
and relative times
. Since cell bodies have a head/tail ambiguity, measures of cell alignment used a variation
where
is a unit vector parallel to the major axis of the cell body. Both of these parameters are constructed so that
= 1 for a fully aligned field and
= 0 for a completely random field.
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800 x g) and concentrated in motility medium (about fivefold) and pipetted onto the leading edge of a swarm. This region was pipetted from the plate into 1 ml of motility medium. A sample was sealed between coverslip and slide with a grease ring and observed in both fluorescence (Texas Red cube No. 31004, Chroma Technologies) and phase contrast with a 40x dry objective. Auto-mobile bead motion was recorded and the centroid tracked, as above. To extract rotational information, individual bacteria on the bead's surface were identified by eye and tracked frame to frame. These markers were rotated into alignment between successive frames, giving the change in bead body angle. Auto-mobile chips were fabricated from Dow Corning Sylgard 184 (PDMS), which was spread between two microscope slides by sliding the edge of one across the surface of the other. This created a very thin PDMS layer that was cured by holding the slide in a propane flame until red hot. As the microscope slide cooled to room temperature, the PDMS slowly fractured. The fractured PDMS was blotted onto S. marcescens as described above, and pieces were scraped off the slide under buffer using a razor blade. This produced small fragments of bacterial-carpet-coated PDMS, which were imaged in phase-contrast with a 10x objective.
| RESULTS |
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Carpets made from the leading edge of the swarm (Fig. 2 A) contained long cells (0.70 ± 0.07 µm wide by 2.7 ± 0.7 µm long) that were seldom up-ended. Carpets made farther behind the leading edge contained shorter cells (0.62 ± 0.01 µm wide by 1.7 ± 0.3 µm long) of mixed attachment style. The longest bacteria (6.6 ± 1.9 µm), found at the leading edge of the swarm, were missing from our bacterial carpets.
We mixed fluorescently labeled bacteria with unlabeled swarming bacteria to create a heterogeneous carpet. Labeled flagella rotated just above the carpet surface (Fig. 2, C and D). An applied flow of 10 µm/s (measured 10 µm above the carpet surface) caused these filaments to orient in the direction of flow, where they bundled and unbundled. The rotation rate of the flagella was 140 ± 30 Hz, comparable to the rotation rate of E. coli flagella when cells are stuck to glass (L.T. and H.C.B, unpublished). When swarming S. marcescens were suspended in motility medium at room temperature, their swimming speed was 47 ± 16 µm/s.
Bead dynamics
Fig. 3 shows the paths traced by 1 µm beads over a 10 s interval, in the bulk fluid (A) and immediately above the surface (B). Beads near the surface moved much more rapidly, and over much larger distances, than beads in the bulk fluid. Since all bead motions were, on average, uncorrelated with each other, we describe their motion statistically and develop an analogy with ordinary diffusion.
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should be invariant under the similarity transform
and
with distance r, time t, and an arbitrary scale factor
. Indeed, far from the surface the distribution is unchanged if we increase the time interval by a factor of
and compress the distance scale by a corresponding factor of
(compare Fig. 4, A and B). For diffusion in two dimensions, we expect this distribution to follow
with diffusion coefficient
(according to the Stokes-Einstein equation with temperature T, viscosity
, and particle radius a). This functional form is superimposed in Fig. 4 B (dotted line), and agrees with the observed distribution; we conclude that all influence of the active carpet surface has already dissipated at a distance of 80 µm from that surface.
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scaling law of the similarity transform.
The simplest plausible correlation function allows an exponentially decaying memory of velocity:
This is mathematically equivalent to a Rayleigh particle, which is designed to describe the diffusion of a physically reasonable particle (albeit on time scales
105 times smaller than ours (van Kampen, 1992
)). The mean-square displacement in two dimensions is given by
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, and rms speed
are related via
For small t this becomes ballistic motion
; for large t it becomes Brownian motion
.
Fig. 5 A shows the mean-square displacements as a function of time. In the bulk fluid far from the surface (open circles), the mean-square displacement
increases linearly with t at a very slow rate that is consistent with the small diffusion coefficient of the large tracer beads. At the surface (open squares),
begins as ballistic motion, but soon changes over to Brownian motion. The initial curvature (inset) occurs because bead motion is correlated over
0.25 s.
Averaging over 13 separate areas of 6 carpets gave Dsurface = 19 ± 5 µm2/s and Dbulk = 0.52 ± 0.18 µm2/s. From the ratio of these two numbers, the agitation of bacterial flagella increased the surface "active" diffusion coefficient almost 40 times relative to the bulk "passive" diffusion of 1 µm beads. Individual measurements of Dsurface spanned ±40% of the mean value, even within different areas of a single carpet preparation. Presumably, this variability stems from differences in the number, length, and coordination of the cells' free flagella. We found no significant correlation between Dsurface and style of cell attachment.
The average correlation times are
surface = 0.09 ± 0.03 s and
bulk = 0.02 ± 0.03 s. The relatively large error associated with the latter measurement occurs because
is sensitive to small amounts of drift in the bulk fluid, so
is generally a less precise and robust measure than D.
The bulk fit parameters are consistent with the Stokes-Einstein predictions of
bulk = 50 ns and of Dbulk = 0.45 ± 0.02 µm2/s for a 0.97 ± 0.05 µm diameter sphere in water (Reif, 1965
). We verified that bead motion in the bulk fluid was similar to motion over a bare surface or over a surface of deactivated bacteria.
The effective diffusion coefficient drops smoothly as a function of height above the surface (Fig. 5 B). At distances of more than 50 µm from the surface, it is indistinguishable from its bulk value.
Surface flows
The vector plot of Fig. 6 A gives a snapshot of flow over a small portion of the surface. In some regions of this snapshot, the fluid seemed quiescent, whereas in others bead after bead moved across the surface. These local variations can be qualitatively classified into "whirlpools" (a) and "rivers" (b). "Whirlpools" produced an almost perfectly circular flow, whereas "rivers" transported beads in an almost straight line. Many rivers seemed to be constructed from several suitably spaced co- and counter-rotating whirlpools. These features generally lasted several minutes before dissipating, with the hardiest rivers and whirlpools lasting more than 10 min. After 10 min, the amount of activity is undiminished (as measured by the rms speed of the flow, for example), but almost none of the originally identifiable centers of activity remain. Most rivers and whirlpools have shifted, merged, or dissipated in that time.
To quantify these observations, we examined the correlations between measured surface fluid velocities as a function of the distance and time between them. Fig. 6 B shows the average, normalized correlation between velocities (solid line, defined as the alignment parameter
in "Methods"). The peak between 10 and 25 µm is a consistent feature of all our carpets. It is caused by the anticorrelation between velocities on opposite sides of whirlpools. The distance between the flanking minima corresponds to the whirlpool diameter, which ranged from 10 to 15 µm. The average interwhirlpool distance was
30 µm.
Choosing a particular distance (
µm) and examining the alignment
as it decays in time, we see a gradual decline over many minutes (data not shown). After 5 min, the correlation was reduced to
25% of its original value, but it was still far from zero. As noted above, some locations maintained stable patterns for more than 10 min.
If flagella were to form bundles that are aligned with the cell body (as occurs during swimming), these bundles would produce a local flow that is itself aligned with the cell body. Fig. 6 B includes a plot of cell-cell alignment as a function of cell-cell separation (dotted line, defined as
in "Methods"). It does not match the flow-flow alignment curve particularly well. The cell-cell correlation length (79 µm) seems too short to explain the observed whirlpool sizes. As a direct test, we examined the alignment between flow direction and cell orientation (dashed line). Over short distances, the cell-flow alignment is consistently positive, but extremely weak: at 2 µm separation, flow-flow alignment is high (better than 60%) and cell-cell alignment is moderate (
30%), but they are not aligned with each other (cell-flow alignment is <0.5%). The connector between the flagellum and the cell body (the "hook") is very flexible. This enables the filaments to change their orientation (Berg and Anderson, 1973
) and thus, in a carpet, to decouple the direction of local flow from any order present among the cell bodies themselves.
Auto-mobile beads and chips
We attached S. marcescens to fluorescent 10 µm diameter beads (Fig. 7 A, inset) to make them auto-mobile. Fig. 7, A and B, show two trajectories of such a bead. The
50 bacteria attached correspond to a surface density of
1 bacterium/6 µm2,
3 times smaller than the density achieved by blotting flat PDMS surfaces. A substantial number of the attached bacteria must be active, since contaminants drifting near the bead are suddenly spurted away from many different points on the bead's surface.
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To reduce rotation, we created larger, flat fragments of bacterial carpets: "auto-mobile chips." These flat objects appeared to skate in the buffer just above the surface of the microscope slide, moving in two dimensions. Fig. 8, A, shows a trapezoidal auto-mobile chip moving at
5 µm/s. The slight clockwise rotation reversed sharply 2 min later. The bacterial carpet, which coats the top side of the chip (Fig. 8, C), shows both styles of attachment. The wedge-shaped chip of Fig. 8, B, rotated at
6 rpm for more than 10 min. Since its axis of rotation meandered slightly during this time, the wedge's corner probably was dragging on the surface rather than being tethered. Other triangular chips also rotated rapidly, and almost all clockwise (viewed from above). Square chips, or irregularly shaped chips with aspect ratios closer to 1, tended to rotate about an axis closer to their centers.
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| DISCUSSION |
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50 µm. The carpets were made by blotting PDMS-coated glass onto a petri plate of swarming S. marcescens. Both swarms and carpets were robust and easy to prepare, and the blot-transfer process consistently gave dense, uniform carpets. Carpets formed from suspensions of such cells were less dense (data not shown), suggesting that bacterial wastes in the buffer compete for available PDMS binding sites. Surprisingly, the surfactants produced by swarming S. marcescens (Matsuyama et al., 1992
The bulk diffusion coefficient (Dbulk = 0.52 µm2/s) is a property of the 1 µm spheres used as tracer particles, whereas the surface diffusion coefficient (Dsurface = 19 µm2/s) is a property of the carpet itself. Since diffusion coefficients for small molecules are
1000 µm2/s, this active surface is not competitive with passive diffusion for salts, amino acids, or sugars, but it is potentially useful with macromolecules. Any object larger than 10 nm could benefit from the active mixing of such a carpet. Since the variation in D over different areas of the same carpet was quite large and comparable to the variation among carpets, we could not identify any differences in surface activity due to the position of carpet fabrication on the swarm plate or to the style of cell attachment. The total depth of fluid affected by the carpet is
50 µm, with a half-depth of 10 µm. This is reasonably consistent with either flagellar length or whirlpool size, which are the two length scales that could influence the height dependence of the flow field.
The measured correlation time is
surface = 0.09 s. From the relation
, the rms speed of fluid just above the carpet is
15 µm/s, which compares favorably with the S. marcescens swimming speed of 47 µm/s. As this swimming speed is probably the best achievable fluid-pumping speed, improvements in carpet-making technique could increase
by up to a factor of 3 (a factor of 9 in D). There is no such upper limit on the correlation time, so boosting
could increase D much further. We might improve coordination among flagella by increasing the flagellar density, using a S. marcescens strain that spins its flagella exclusively in one direction, adding an attractant to lengthen the period between motor reversals, or reducing the depth of the fluid to be mixed. All of these should increase the typical size of the surface flow patterns, producing a corresponding increase in correlation time.
Fluid flow above the active surface seems to consist of many "whirlpools", rotating both clockwise and counterclockwise, which are typically 1015 µm in diameter. These whirlpools are not correlated with the pattern of the underlying cell bodies in the carpet. The simplest explanation of whirlpool size is that it is produced by a rotating flagellum (or flagella) sticking straight up into the fluid. The velocity induced by a rotating flagellum should decrease with radial distance r as
, where
µm is the radius of the flagellar helix (Higdon, 1979
). The peak speed of
occurs at
, where
Hz is the flagellum rotation rate. At a distance of 3 µm, this idealized flagellum would create a flow of
µm/s. At the same distance, a real whirlpool produces a flow of 9 µm/s that does fall off reasonably like
(data not shown). This suggests that a whirlpool could be created by a small number of coordinated flagella aligned predominantly normal to the carpet surface. The 10 µm/s flow field that orients filaments in the carpet is consistent with bacterial locomotion: a swimming speed of just a few µm/s causes randomly oriented flagella to stream behind the cell and rebundle (Turner et al., 2000
). Rivers of flow are often several times the length of any relevant bacterial dimension (including the typical flagellum length of 10 µm). Both rivers and whirlpools persist many times longer than the typical bundle lifetime during normal swimming. All of these observations lead us to suspect that we have achieved coordination among a handful of flagella at a time, although as yet we have no direct evidence of this.
Under our temperature and buffer conditions, S. marcescens swims at
47 µm/s. If we approximate its cell body as a 1 µm diameter sphere, then one bacterium attached end-on should be able to move a 10 µm sphere (our auto-mobile bead) 4.7 µm/s (since the viscous drag on a sphere is proportional to its radius). From Stokes' law, this works out to a thrust of
0.5 pN. One bacterium attached side-on, applying this propulsive force tangentially to the sphere's surface through a 5 µm lever arm, would rotate the bead 41°/s. The observed rms translational and rotational speeds of our auto-mobile bead were 4.7 µm/s and 59°/s, respectively. This can be explained by applying the propulsive force equivalent to one or two free-swimming bacteria (properly oriented).
In reality, a 10 µm bead captures
50 bacteria. If these 50 bacteria are randomly distributed over the surface, each pointing an average of four flagella in random directions, the net force and torque produced would be zero. We actually observe frequent pauses and reversals of motion that are caused by statistical fluctuations among flagella orientations. We expect to see temporary imbalances of 
flagella that transiently produce a net force and torque. This is equivalent to three or four free-swimming bacteria. The estimate of the previous paragraph is slightly lower than this, probably because a bacterium that is stuck to a surface cannot deliver as much thrust as one that is swimming freely. The reduction in propulsive power could be caused by flagella sticking to the bead surface or breaking during fabrication, or by increased drag against the large nearby bead surface. As the latter would be a more fundamental problem with our technique, we are currently working to understand the relevant hydrodynamics.
Until we can coordinate larger numbers of flagella, the propulsive force F generated by N bacteria attached to an object of size L will scale like
; since
, we expect
. Meanwhile, the low Reynolds number drag also scales like L, so the typical speed should be roughly independent of size. Indeed, the auto-mobile chip pictured in Fig. 8, A, is almost 10 times the size of the auto-mobile bead, but moves at the same speed.
| ACKNOWLEDGEMENTS |
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This work was supported by the Defense Advanced Research Projects Agency/Office of Naval Research Biomolecular Motors Program (contract No. N66001-02-C-8029) and by the Rowland Institute at Harvard.
| FOOTNOTES |
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Submitted on July 3, 2003; accepted for publication October 9, 2003.
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