Three-Dimensional Superlocalization Imaging of Gliding Mycoplasma

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Three-Dimensional Superlocalization Imaging of Gliding Mycoplasma mobile by Extraordinary Light Transmission through Arrayed Nanoholes Wonju Lee,† Yoshiaki Kinosita,‡ Youngjin Oh,† Nagisa Mikami,‡ Heejin Yang,† Makoto Miyata,§ Takayuki Nishizaka,‡ and Donghyun Kim*,† †

School of Electrical and Electronic Engineering, Yonsei University, Seoul 120-749, Republic of Korea, ‡Department of Physics, Gakushuin University, Tokyo 171-8588, Japan, and §Department of Biology, Graduate School of Science, Osaka City University, Osaka 558-8585, Japan

ABSTRACT In this paper, we describe super-resolved sampling of live

bacteria based on extraordinary optical transmission (EOT) of light. EOT is produced by surface plasmon confinement and coupling with nanostructures. Bacterial fluorescence is excited by the localized fields for subdiffraction-limited sampling. The concept was applied to elucidating bacterial dynamics of gliding Mycoplasma mobile (M. mobile). The results analyzed with multiple M. mobile bacteria show individual characters and reveal that M. mobile undergoes a significant axial variation at 94 nm. The sampling error of the method is estimated to be much smaller than 1/10 of the diffraction limit both in the lateral and depth axis. The method provides a powerful tool for investigation of biomolecular dynamics at subwavelength precision. KEYWORDS: super-resolution . far-field nanoscopy . extraordinary optical transmission . nanoscale sampling . nanoaperture arrays . molecular tracking . bacterial motility . Mycoplasma mobile

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irect nanoscale analyses of biological objects such as viruses and bacteria have been extremely important to investigate many types whose internal morphology and exact nature in the way that they move, behave, and interact with external environments still remain largely unknown. For three-dimensional tracking of nanoscale objects, time-resolved spectroscopy,1 two-photon microscopy,2,3 or optical trapping4
6 have evolved to monitor and provide molecular positions in various environments. Many of the 3D tracking techniques, however, have been attempted on a scale such that understanding the nature of behaviors has been relatively limited in terms of resolution. In addition to conventional fluorescence microscopy used historically,7,8 various imaging approaches have emerged, e.g., super-resolution microscopy techniques,9
11 to enable observation of molecular objects from diverse aspects, despite often sacrificing temporal resolution, small field of view insufficient to catch overall biological motility and the difficulty LEE ET AL.

associated with scanning to create an image. As an example, intracellular imaging of Caulobacter crescentus has recently been explored by super-resolution microscopy, which provides only anatomical details without presenting real-time behaviors.12,13 In this paper, we describe super-resolved sampling with nanoscale resolution that is used to analyze the motility of a single bacterium. The sampling is based on locally amplified electromagnetic waves and the localization takes place in the near-field by extraordinary optical transmission (EOT) of light through arrayed nanoapertures. It is well-known that subwavelength nanoapertures fabricated in a thick metal film can significantly enhance the intensity of transmitted light fields based on surface plasmon-coupling effects.14 In other words, incident light on a nanoaperture in a metallic surface is diffracted from the edge of an aperture and can produce surface plasmon polariton (SPP) localized in the lateral plane.15,16 This gives rise to high confinement of SPP waves as well as plasmonic VOL. 9

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* Address correspondence to [email protected]. Received for review June 27, 2015 and accepted October 15, 2015. Published online October 15, 2015 10.1021/acsnano.5b03934 C 2015 American Chemical Society

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Compared to better known E. coli in Enterobacteriaceae family, less is known about the characteristics of M. mobile: the way M. mobile glides across the surface remains to be a topic that is heavily investigated in addition to flagella swimming,33
35 and parameters such as axial movement and associated fluctuation in the course of the gliding remain elusive, although recent results add insights for understanding its overall motion characteristics.36,37 For complete understanding of M. mobile gliding, therefore, it is critical to acquire axial as well as lateral movements of the bacteria, which is often overlooked in many superresolution techniques. For this purpose, super-resolved axial sampling is addressed by mapping fluctuations of bacterial fluorescence to axial light field distribution, while lateral sampling based on localization of electromagnetic waves is performed simultaneously. The present study is the first attempt to measure M. mobile walking on the surface of metallic nanostructures, where we explore the feasibility of sampling bacterial motility with sub-100 nm resolution based on fieldenhanced nanoaperture arrays.

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coupling when the nanoaperture size is smaller than light wavelength, which has proven useful for subdiffraction-limited localization microscopy techniques using various nanoapertures.17
23 Furthermore, these effects lead to near-field enhancement at the metal-dielectric interface24
29 and modulates the penetration depth of transmitted fields, which depends on the aperture size. In general, the aperture size affects the field transmission in the way that a larger nanoaperture allows deeper light penetration and light cannot transmit through an aperture if the size is too small. The size-dependent light penetration was previously used for super-resolved axial imaging of intracellular protein perfusion.30 The use of multiplesized nanoapertures may also facilitate calibration of fluorescent intensity and investigation of patterndependent cell motility. Here, we use light fields of EOT for lateral and axial sampling of live bacteria in motion, which allows scanningless acquisition of subdiffraction-limited information and thus can help reveal the nature of bacterial gliding on the surface. Particular focus has been placed on Mycoplasma mobile (M. mobile) as the bacterium of interest. M. mobile is a wall-less single-celled bacterium in Mollicutes family and is pathogenic. Motility of M. mobile is believed to be correlated to parasitism.31 It is known for the vigorous gliding at a speed as high as 2
4.5 μm/sec, which may be affected by the extracellular conditions such as pH and ionic strength.32

RESULTS AND DISCUSSION Outline of EOT-Based Super-Resolved Sampling. Superresolved sampling that was performed to analyze bacterial movements is illustrated in Figure 1a. Arrayed nanoapertures produce localized near-fields in the lateral and axial dimension by EOT and excite fluorescence of

Figure 1. (a) Schematic illustration of molecular sampling based on EOT and optical setup. (b) Near-field distribution formed by binary nanoapertures. The results are based on experimental nanohole aperture parameters measured from SEM: φ = 310 and 410 nm and Λ/2 = 830 nm. Above, in the xz plane (x and z represent gliding and depth axis). Below, 2D distribution in the xy plane stacked axially (y: lateral axis). At the top, the schematic of nanoapertures and the guide is overlaid. LEE ET AL.

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ARTICLE Figure 2. (a) SEM image of a fabricated binary nanohole aperture sample. (b) Phase contrast and (c) epi-fluorescence image of M. mobile. (d), (e) TEM image of flask-shaped (intact) and spherical M. mobile. (Scale bars: 2 μm).

M. mobile. The dependence of target fluorescence on the lateral and axial position is governed by the distribution of near-fields formed by EOT, from which the position of target molecules can be estimated at super-resolution. The scheme presented in Figure 1a consists of nanohole apertures of different sizes (binary nanoapertures) and employs axially distinct near-field distribution in two ways: i.e., deeper and shallower penetration of transmitted light through a larger and a smaller nanoaperture, respectively, which can provide information on size-dependent behavior of bacteria in the axial direction with improved resolution and ease of calibration. An additional yet significant advantage of using EOT for super-resolved sampling is that the penetration of the fields by EOT tends to be deeper than what is typically observed under total internal reflection (TIR), and thus allows more extensive analysis of axial features of bacterial gliding. Design and Fabrication of Nanoapertures. For the concept to work, understanding the exact nature of nearfields is critical. Although apertures were initially designed with two different sizes of φ = 300 and 400 nm (φ: nanohole diameter), real apertures were fabricated to be slightly larger in diameter as φ = 310 and 410 nm because of proximity effect. Therefore, the near-fields formed by nanohole apertures were obtained using 3D rigorous coupled wave analysis (RCWA) assuming nanoapertures of two different sizes at φ = 310 and 410 nm with a monochromatic light source of λ = 532 nm illuminated at normal incidence. The period between identical nanoapertures was Λ = 1660 nm while neighboring nanoapertures of different sizes are separated by Λ/2 = 830 nm between centers. The separation is larger than the propagation length of plasmon and the coupling of near-fields at the period was thus negligible. The results are shown in Figure 1b and c. For a nanoaperture at φ = 410 nm, LEE ET AL.

highly enhanced EOT fields following a Gaussian profile in the lateral plane are produced. The penetration depth and the full-width-at-half-maximum (fwhm) of the transmitted fields were produced at 500 and 300 nm, respectively. The fwhm in this case was measured at an axial distance of half the penetration depth. In contrast, in the case of nanoholes of φ = 310 nm, EOT-fields are significantly decreased in intensity with shallower depth penetration to 350 nm and fwhm at 240 nm. If we reduce the nanohole size down to 200 nm, EOT-fields at nanoholes were almost suppressed (see Figure S1). A SEM image of the fabricated binary nanohole aperture arrays is presented in Figure 2a, and the overall fabrication protocol is based on two-step electron-beam lithography as described in Methods. Note that nanoguide lines were defined at the binary nanoaperture surface to induce M. mobile to have largely unidirectional and linear gliding motility at nanograting surface between the nanoguide lines (Figure S2 and Movie S1). In other words, use of aligned nanoguides prevents M. mobile from gliding off the EOT-field and thus reduces the lateral uncertainty when it glides on the arrayed nanoapertures. Figure 2b
e show images of M. mobile measured by phase contrast microscopy, epi-fluorescence, and SEM M. mobile has a body of a few hundred nanometers in size (approximately 450 nm in width, 800 nm in length, and 500 nm in waist circumference) with legs between 50 and 100 nm in length.31 Super-Resolved Sampling at a Single Nanoaperture. Timesequential images of wild-type M. mobile gliding over a nanohole aperture are presented in Figure 3. The raw data are included as movies (see Movie S2). Each image is composed of 9  9 pixels with the size of one pixel at 160  160 nm2, i.e., a nanohole aperture of φ = 410 nm is imaged approximately in 3  3 pixels. The center of a nanohole aperture was initially aligned to the center VOL. 9

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ARTICLE Figure 3. M. mobile gliding over a single nanohole aperture of 410 nm diameter. Schematics and CCD images of the gliding of (a) flask-shaped (asymmetric) and (b) spherical (symmetric) intact M. mobile. (c) Fluorescent intensity profiles of (black) asymmetric and (red) spherical M. mobile gliding over a single nanoaperture (φ = 410 nm).

pixel of each image based on time-averaged light transmittance using bright-field microscopy. If M. mobile approaches a nanohole, the fluorescence intensity becomes stronger and reaches a maximum when gliding M. mobile is located near the aperture center. After a while, fluorescence intensity decreases as M. mobile glides out of the nanohole. Over the course of M. mobile gliding across a nanoaperture, if M. mobile maintains a fixed distance from surface, the measured fluorescence intensity would follow the near-field distribution formed by EOT. Note that the effect of shape may be present because an intact M. mobile is highly asymmetric. If the effect of the shape in the acquired fluorescence can be minimized, the fluorescence intensity deviation from the EOT-field distribution would predominantly be associated with axial movement of M. mobile and can be used to find axial distribution. Determination of axial movement from the intensity deviation is thus based on three assumptions: (1) lateral position of M. mobile is known, (2) M. mobile LEE ET AL.

fluorescence may be affected by its shape, therefore the shape needs to be symmetrical in the lateral and the axial plane, preferably in a spherical form, and (3) fluorescence from M. mobile should be significantly stronger than background noise. The validity of these assumptions is discussed in what follows. First, super-resolved lateral positions of M. mobile were estimated below the diffraction limit by Gaussian least-squares fits. The procedure is performed largely by fitting each raw image of the entire image sequence of a gliding bacterium to a 2D Gaussian function.10,25
27,38
40 The details of the fitting procedure are described in Methods. For investigation of shape symmetry, fluorescence images of Cy3-labeled wild-type intact and spherical M. mobile are shown in Figure 3a and b. In Figure 3a, fluorescent intensities of intact M. mobile were measured at the center pixel of each image and were observed to change much more drastically than what may be explained by the intensity variation of VOL. 9

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k

k

Here, k is an index that runs over fluorophores that are excited at the membrane of M. mobile. Ik and rk represent the fluorescence intensity and the vectorial position of fluorophores. In other words, if M. mobile undergoes axial variations in the course of gliding, the up-anddown motions of fluorophores are sampled sequentially as a whole in terms of the center of brightness. Figures 4 and 5 show sampling of a single spherical M. mobile that glides over eight consecutive nanohole LEE ET AL.

apertures and also three-dimensional reconstruction of the sampled M. mobile at super-resolution. Figure 4 addresses lateral dynamics of gliding M. mobile, where axial information is implicit and appears as a change in fluorescent intensity. In contrast, axial analysis is discussed in Figure 5 for a single M. mobile (for multiple M. mobiles in Figure 6). The gliding motion was captured with an identical sampling frequency of 33.025 frames/ sec. Figure 4a presents kymograph images captured as M. mobile glides over a row of nanoholes in which those of φ = 410 nm (A, C, E, and G) and 310 nm (B, D, F, and H) alternate. The consecutive nanoholes are spaced five CCD pixels apart from one another in the image plane. The raw kymograph movie is presented in Movie S3. Corresponding fluorescent intensity profiles obtained at each nanohole aperture are presented as solid lines in Figure 4b. The intensity variation in the profile including the intensity drop observed at the center of A, B, E, F, and G are linked to changes in the axial position of the bacterium, which can be explained by movements of M. mobile in the lateral and axial plane. Due to the lateral guiding, M. mobile may glide along the axis that connects the nanohole centers which we define as the gliding axis (x-axis). Because near-field distribution produced by EOT through a nanohole aperture follows a Gaussian profile shown in Figure 1b and c, if M. mobile glides in a straight line along the x-axis and at a fixed axial distance from the surface, the fluorescent intensity should also follow a Gaussian profile. Even though the gliding motion of M. mobile was restrained by lateral guiding, finite lateral displacement from the x-axis exists along the orthogonal lateral direction (displacement axis or y-axis). The lateral displacement is estimated to be within one image pixel. Even if M. mobile does not glide across the center due to the lateral displacement, the intensity profile should remain Gaussian due to the symmetry of the EOT field in the lateral plane. This is easily confirmed in the intensity profiles of Figure 4b, suggesting that the intensity profiles should represent the convolution of Gaussian near-fields and fluorescence distribution under linear imaging theory and the non-Gaussian variation may be associated with axial movement of M. mobile. The effect of lateral displacement can be compensated by first finding lateral coordinates within a pixel for lateral projection to the aperture center along the gliding axis and then linear interpolation following the protocol described in the Methods. Figure 4c presents the raw image at CCD and describes the lateral movement of M. mobile at each of the nanoholes A
H, in which x and y coordinates represent the center of brightness of M. mobile c(r) projected onto the lateral plane (x
y) that is determined by the least-squares fitting of 2-D Gaussian function. The lateral positions over each of the nanoholes are overlaid in the CCD image (left) and plotted in VOL. 9

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near-fields formed by EOT. The sequential intensity pattern at the center pixel is also presented as a black line in Figure 3c. It is noted that the frame marked under the black arrow shows particularly bright fluorescence emission that is much higher than any other case. The intensity variation is primarily due to an asymmetrical shape of intact M. mobile. Asymmetry in the bacterial shape can therefore contribute significantly to the nonuniformity in the measured fluorescence. To understand the effect of bacterial shape by comparison, we have conducted an experiment in which fluorescence images of spherical M. mobile gliding over a nanohole aperture were measured in a similar manner to the case of intact M. mobile. The possibility of controlling the shape of M. mobile into a spherical shape by shrinking has been reported previously in ref 36. Spherical M. mobile has a globular cell body with its cell size (both width and length) less than 1 μm as shown in Figure 2e, which is enabled by Tris buffer treatments to control extracellular pH-change of medium or osmotic shock. M. mobile, whether it is intact without such treatment or spherical, is wild-type without genetic modification. Time-lapse fluorescence images of M. mobile gliding over a nanohole shown in Figure 3b (and as a red line in Figure 3c) are in stark contrast to what was presented in Figure 3a for intact M. mobile, i.e., the fluorescence intensity changes much less. For intact M. mobile, lateral precision tends to worsen in general, while axial precision also increases, due to the shape effects. To avoid shape-dependent artifacts in the results, we have used spherical M. mobile for super-resolved sampling described hereafter, in which case intensity variation can dominantly be associated with the movement of M. mobile gliding. Additional intensity fluctuation may be caused by various noise factors such as dark current and electron shot noise, which can be suppressed by employing a cooled electron multiplying CCD with high quantum efficiency. Control experiments were performed to ensure that the background noise would not affect the conclusion (Figure S3). Gliding M. mobile Sampled at Super-Resolution over Consecutive Nanoaperture Arrays. For the convenience of representing bacterial positions, we have employed the concept of the center of brightness c(r), which we define as the center position of fluorescently excited volume. c(r) can be expressed as c(r) ¼ ∑Ik rk = ∑Ik .

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ARTICLE Figure 4. Lateral dynamics of M. mobile over eight consecutive nanoaperture arrays (A
H: φ = 410 nm for A, C, E, G and φ = 310 nm for B, D, F, H). (a) Kymograph images of M. mobile, where x and y axis represent gliding and lateral displacement axis. (b) Fluorescent intensity profiles of M. mobile over each nanoaperture. (c) Lateral positions of M. mobile over each of the eight the nanoapertures (A
H). Each of the eight sets consists of the raw CCD image overlaid with lateral movement (left), a 2D plot in the lateral plane (center) and a 3D scatter plot which shows the intensity I in the xy plane (right). The arrows represent the overall movement direction of M. mobile and the time t denotes the start and the end of image acquisition. Lateral displacement was estimated to be less than half a pixel. (d) Standard deviations (in terms of error bars) that accompany fluorescence intensity in the gliding direction (x-axis) and lateral displacement axis (y-axis). Also shown in the inset (top left) are the schematics of nanoholes of φ = 300 and 400 nm (blue circles). The square in dark solid line represents a 240  240 nm2 region in the lateral plane under observation, which includes a single pixel (160  160 nm2) at the center (yellow shaded). For convenience, the pixel and nanoholes are illustrated to be concentric in the inset.

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ARTICLE Figure 5. Super-resolved axial dynamics of M. mobile over eight consecutive nanohole aperture arrays. (a) Schematics of M. mobile gliding on a nanohole aperture from left to right. Initially, its front tip is excited, followed by the membrane of the cell body and then the rear tip. (b) 3D representation of axial movements of gliding M. mobile. Circular diameter at each position denotes the associated axial deviation. Color scale bar represents the axial variation between 0 (surface) and 800 nm. The arrow marks nanohole G, the movement at which is analyzed in (c). (c) Extraction of axial variation of M. mobile movement gliding at nanohole G: lateral displacement compensation by projection and interpolation (left) and axial mapping of the compensated intensity to the EOT field (right). (d) Axial dynamics of M. mobile over the nanoholes along the gliding direction (x-axis) after displacement compensation. (e) Illustration of the effects that may cause fluorescent intensity variation after lateral compensation: (top) pattern dependence, and (bottom) axial motion of gliding M. mobile. (f) Axial movement of M. mobile in the course of gliding without pattern dependence. The inset shows 50 nm differential of axial positions between neighboring holes (G and H). LEE ET AL.

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ARTICLE Figure 6. Axial characteristics of a group of M. mobile bacteria that glide over more than six consecutive nanohole apertures. (a) Histograms of axial positions representing axial dynamics of an individual M. mobile. Each class represented by the tick mark in the x axis has an interval of 200 nm and the leftmost tick mark corresponds to the surface reference. (b) Overall axial positions of the whole group reveal an average variation of Δz = 94 nm. Each class represented by the tick mark in the y axis has an interval of 100 nm and the lowest tick mark corresponds to the surface reference. (c) 3D scatter plot presents axial deviation in color at each 3D position. A smaller deviation is clear at lower position, i.e., at higher fluorescence intensity.

2D (center). The arrows represent the overall gliding direction and the time t denotes the start and the end of image acquisition of gliding M. mobile. Neighboring points were acquired from continuous image frames that are 0.03 s apart. From the 2-D Gaussian fit, M. mobile was estimated to glide along the x-axis with lateral displacement smaller than half a pixel (the largest displacement for this particular M. mobile was determined to be 72.7 nm). Note that the body of M. mobile is nearly twice as large as a nanoaperture and the size of the EOT field. Fluorescent Cy3-label is assumed to be uniformly distributed. Figure 4c also presents a 3D scatter plot of fluorescence intensity in the lateral (x, y) coordinates (right). Note that the intensity profiles are narrower than what is observed in the raw data shown in Figure 4b, i.e., if M. mobile moves along the orthogonal axis by lateral displacement, gliding distance measured along the x-axis becomes shorter and makes the intensity profile significantly narrower. The standard deviation associated with the process of determining the lateral position is also important. This is provided as horizontal error bars for the measured points in Figure 4d along the gliding direction (x-axis) and the direction orthogonal to the gliding direction (displacement axis, y-axis). In Figure 4d, the range in the horizontal axis from
80 to 80 nm LEE ET AL.

represents the extent of one pixel in the gliding (x) and the displacement (y) axis. Also shown in the inset (top left) are the schematics of nanoholes of φ = 300 and 400 nm (blue circles) with a square in dark solid line for the lateral region of observation (240  240 nm2). The deviation is governed by the precision of the 2-D Gaussian fits and correlates with the lateral resolution. The number of sample pixel images (N) improves the √ fitting precision in proportion to Npixel (Npixel = 81), which decreases the deviation. On the other hand, the deviation was observed to decrease if more photons are acquired, i.e., with higher SNR, as shown in Figure S4, where the relation between normalized intensity and the standard deviation of the lateral positions in the gliding (x) and the displacement (y) axis is presented as scatter plots. The results confirm an earlier report that √ the estimated error should be in proportion to 1/ N (N: photon number).41 The result implies that slower gliding may allow more frames to be captured per unit time. This increases the effective number of captured photons, thereby can reduce the deviation. Also shown in Figure S4 are two histograms of the deviation in the lateral plane. It is revealed that the lateral deviation in the displacement direction is smaller than in the gliding direction, which is due to the effect of nanoguide lines. In this case, lateral sampling error (δx, δy) as a measure of image resolution can be derived from the deviation VOL. 9

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intra-aperture and interaperture velocity are in good agreement with literature.31 Figure 5d describes axial dynamics of M. mobile gliding over the eight nanoholes along the gliding direction (x-axis). It is found in all the profiles that the center of brightness is initially lowered before it increases. The result suggests three major factors that may be responsible for the obtained axial variation. First, the variation measured of all the nanoapertures follows that of membrane surface that takes a broad parabolic shape around the minimum, which may be an artifact associated with finite membrane curvature of M. mobile in the course of lateral gliding. As M. mobile glides into and out of a nanoaperture, the center of brightness is slightly shifted in the axial direction within half a body size, leading to the membrane curvature artifact (illustrated in Figure 5a). Second, the results show pattern-dependent axial variation (top in Figure 5e) which is much stronger by as much as the body size. Although a nanohole can be a sizable barrier for a mycoplasma cell, the patterndependence of the gliding appeared largely when M. mobile glides into and out of a hole. Interestingly, M. mobile moves differently with respect the size of nanoholes, i.e., the pattern dependence was more prominent at larger nanoholes, indicating that smaller apertures at φ = 310 nm may be little affecting the bacterial gliding. This may be the result of relative size of gliding machinery and/or nonuniform coating of sialylated oligosaccharides which M. mobile needs to bind for gliding. Finally, there are variations associated with the axial dynamics of gliding M. mobile, as presented in the bottom of Figure 5e. The variations can have a strong relationship with the walking hypothesis of M. mobile at surface, which is explained in Figure 5f. The axial movement, which appears as local fluctuation near minimum, was measured to be Δz = 76 nm for this particular M. mobile (st.d., n = 5 for each of the eight nanoholes) excluding curvature artifact and patterndependence. One assumption was that the effect of curvature artifact and pattern-dependence was reflected in c(x, y0, z) near the first and last sampling point on each nanohole. For improved visualization of the axial trajectory of M. mobile gliding, the size of bacterial membrane and the separation between neighboring holes are downscaled to half and one-tenth, respectively. Axial variations (Δz) in the M. mobile movements were determined based on zero reference position (z = 0) along the y-axis with 50 nm grids. Once the middle of the membrane bottom coincides with the center of EOT field, which occurs near minimum c(x, y0, z), gliding movement of M. mobile was observed to fluctuate up and down in the axial direction. This axial movement is modeled in Figure 5f which describes the changes of body positions of M. mobile on the eight nanoholes. For example, the inset shows 50 nm differential of axial positions between neighboring holes (G and H). VOL. 9

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and determined to be δx = 24 nm and δy = 15 nm in the gliding and displacement direction, respectively (see Figure S5 for the definition of sampling error in contrast to precision and accuracy of the measurement). For more details of the lateral sampling error, overall gliding events of M. mobile were analyzed in Figure S6. Once lateral positions and corresponding fluorescence intensities were determined, the effect of lateral displacements along the y-axis has been compensated so that the movement of M. mobile was translated into the motion along the gliding x-axis (y = 0). The lateral displacement compensation was performed by lateral projection of measured light intensity to that of the gliding axis which is followed by linear interpolation along the EOT intensity profile, as elaborated in Methods. After the lateral compensation, axial positions of M. mobile can be determined in the xz-plane by mapping compensated fluorescent intensity of M. mobile to the three-dimensional EOT-based field distribution. The overall procedure of lateral compensation and extraction of axial information by intensity mapping is described as a flowchart in Figure S7. As illustrated in Figure 5a, gliding M. mobile has its fluorescence localized at membrane surface of the body, which is excited by extraordinary light transmission produced by the nanoaperture. As it glides into EOT fields, the front tip of M. mobile is initially exposed, corresponding to the first sampling point in Figure 5b
d, and while M. mobile moves from left to right, it is the cell body and then the rear tip that is excited. The measured axial variations over all eight nanoapertures are presented in 3D in Figure 5b, where axial profiles of M. mobile are shown with a schematic of scaled eight consecutive nanohole apertures (animated version of Figure 5b provided in Movie S4). Color scale bar represents the axial variation between 0 (surface, red) and 800 nm (blue). If we focus on a specific nanohole, e.g., G marked with an arrow in Figure 5b, the axial variation can be extracted by performing the mapping of intensity data (shown on the left of Figure 5c) to the EOT field as shown on the right. The graphic illustration of the axial mapping steps, including lateral compensation, for the case of nanohole G is provided in Figure S8. The intensity reference in the axial mapping process (vertical error bar) was obtained from inactive M. mobiles, the membrane of which was bound to the surface while fluorescing and is shown along with that of lateral displacement (horizontal error bar). Gliding behaviors of M. mobile can be deduced at each nanoaperture by following the trajectory of sampled positions during the sampling times. For example, intra-aperture velocity along the axial direction and in the xz plane was measured to be vz = 1.94 ( 0.51 μm/sec (st.d., n = 106) and vxz = 2.02 ( 0.49 μm/sec (st.d., n = 106). Also, interaperture velocity along the gliding axis was vx = 2.27 ( 0.72 μm/sec (st.d., n = 7). These results of

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DISCUSSION Several points in this work are worth discussion, in particular, about sampling error, bacterial walking model that may be implied from the results, and the effects of nanoguiding. First of all, the EOT-sampling method that we have explored for three-dimensional analysis of gliding M. mobile reveals that M. mobile gliding on patterned surface undergoes axial movement with an average variation Δz = 94 nm from surface. Some error may be introduced into the axial dimension because of the disparity in the actual and calculated field profile, which may arise from, e.g., imperfect nanoholes and local refractive index change due to the presence of a bacterium. Analysis based on simple modeling shows that the disparity in intensity is less than 5% and its influence is still limited (Figure S10). The sampling error as a measure of tracking resolution was estimated to be LEE ET AL.

(δx = 24, δy = 15, δz = 57 nm). This is much smaller than the diffraction limit, approximately less than one tenth of what is estimated by Rayleigh criterion both in the lateral plane and in the depth axis. Such a resolution requires sufficient certainty in the near-field. Near-field scanning optical microscopy can be used to confirm the numerical field distribution produced by the binary nanohole aperture within the measurement accuracy. Regarding the bacterial walking mechanism, the axial data extracted of gliding M. mobile may be used to add a tilt in the axial dimension to an existing walking model of M. mobile based on pivoting movement in the lateral plane.35 In this tilt model, axial tilt motion can be analyzed by mapping the intensity variation to a specific tilt angle in the axial plane with respect to the central axis of the body, although additional measurements need to be conducted for conclusive results. Furthermore, because of the large size of the protein, Gli349, that anchors the membrane to the substrate, it has been hypothesized that the protein works as a “leg” by binding to and releasing from the substrate. This simple view is now modified with the assumption in which an additional movement of other proteins, such as Gli521, is possibly involved so as to generate regular steps in an extreme condition.36 If these structural changes directly drive the continuous gliding of a single bacterium, the axial position of the center of the cell body should show fluctuation with relation to the stochastic change of the number of working motor units in the general condition. We infer that the axial movement observed in Figure 6 possibly originates from the above structural dynamics, counting that the size of protein complex, several hundred nanometers, coincides well with the Δz, (94 nm. Finally, we emphasize that nanoguides allow the possibility of controlling the gliding motion of multiple bacterial cells that on glass surface would glide in random directions without guides. While M. mobile was previously found to glide in unidirectional circling motions along the wall of lithographically defined microtracks,42 nanoguides enable periodic spots of EOT to act effectively as an arrayed scanning optical microscope by aligning biomolecules under investigation to probe arrays that are fixed spatially. Equally important is the possibility that the nanoguides in the long run can be used to implement massive cargo transport with bacteria as directed transporters. More than the nanoguiding, the power of 3D superlocalization by the EOT sampling can be extended to the analysis of more general biomolecular dynamics. Compared to conventional tracking techniques, our approach takes advantage of multiplexing capability of arrayed nanoapertures for simultaneous tracking and sampling of multiple gliding M. mobiles. It also allows molecular tracking at a precision significantly smaller than diffraction limit and thus much more precise lateral and axial sectioning for three-dimensional VOL. 9

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Axial Movement Characteristics of M. mobile. For more general understanding of M. mobile gliding behavior, multiple M. mobile bacteria are now analyzed in Figure 6. Figure 6a presents histograms of axial movement of six different M. mobile bacteria which glide over more than six consecutive nanoapertures. Obviously, distinct axial characteristics are observed with each bacterium. Excluding curvature artifact and pattern dependence, axial variation was found to range from 6 to 100 nm. The variation in the dynamicity of M. mobile may be explained by differences in motility parameters such as gliding speed as well as in anatomical characteristics. Overall distribution of the axial variation of the six M. mobiles is presented in Figure 6b. The axial movement of M. mobile was statistically fitted to a normal distribution. The fwhm correlates with the range of average axial movements of M. mobile. On the basis of this distribution, it is suggested that the range of axial characteristics of M. mobile is fairly broad, i.e., the axial distance from surface out of its axial movements was measured to be 217 ( 94 nm (st.d., n = 185), i.e., the axial variance ratio, which is defined as the ratio of axial variance to average Δz/z ≈ 94/217 = 0.43. In other words, M. mobile undergoes significant axial movement in the course of the lateral gliding. For comparison, we performed threedimensional tracking microscopy of the axial gliding of M. mobile, which was in excellent agreement with our results based on the EOT sampling method (Figure S9). A 3D scatter plot in Figure 6c presents axial deviation extracted from the overall axial distance distribution of Figure 6b and shows that the error with which axial positions can be determined decreases with the depth due to a smaller number of photons that can be acquired in the evanescent field. This is in line with what we observed in the process of determining lateral positions. From the axial positions of gliding M. mobile, the sampling error along the depth axis was estimated to be δz = 57 nm.

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CONCLUSION In summary, we report super-resolved sampling of gliding M. mobile. The sampling was performed by

METHODS Numerical Method. Electromagnetic field distribution produced by gold nanohole aperture arrays with nanoguide lines was numerically calculated using 3D RCWA with a grid spacing of 1 nm and 15  15 spatial harmonic orders. RCWA has been successfully employed for numerical calculations of periodic nanostructures.45 Refractive index of gold and BK7 glass was 0.467 þ 2.4075i and 1.51947 at λ = 532 nm.46 Light source was assumed to be p-polarized with normal incidence. Fabrication of Guided Nanoaperture Arrays and Nanoguides. For fabrication of binary nanoapertures, chrome and gold adhesion layers, each of which is 2 nm thick, were initially deposited by e-beam evaporation on a BK7 cover glass substrate. Circular nanohole apertures were then patterned at a period Λ = 1.6 μm using electron beam lithography on a ARN-7520N (Allresist Inc., Strausberg, Germany) negative resist layer which was for 1 min at 5000 rpm and then the sample was soft-baked for 5 min at 85 °C. The aperture pattern on the resist was transferred to a layer of 50 nm gold, followed by removal of the resist in a lift-off process. Second electron-beam lithography was conducted with positive e-beam resist (Poly(methyl methacrylate) AR-P 630, Allregist) after spin-coating the sample for 1 min at 6000 rpm and soft-baking for 5 min at 175 °C. Nanoguide patterns were then defined by electron-beam after alignment based on stage positioning and angular tilts with e-beam markers. The nanoguides were formed by development and subsequent evaporation with 1 nm chrome, 100 nm silver, and finally 1 nm chrome for lift-off. The topmost chrome layer was intended for improvement of biocompatibility.19 Optical Setup. Optical setup illustrated in Figure 1a employs light illumination from a 532 nm laser (COMPASS 215M-50, Coherent Inc., Dieburg, Germany) normally incident at the sample through a high numerical aperture objective lens (Apo TIRF 100, NA 1.49, Nikon, Tokyo, Japan) to excite Cy3-labeled M. mobile. The light output power at 50 mW was reduced through a neutral density filter to 1.4 mW when light is incident upon the nanoaperture array. Fluorescent images were captured by an EM-CCD (iXon 860 and 897, Andor Technology, Belfast, Ireland) through a dichroic mirror (Q550DRLPXT, Chroma, Bellow Falls, VT, USA) and an emission filter (NF03
532  10
25, Semrock, Rochester, NY, USA). Preparation of M. mobile. A mutant strain of M. mobile, P476R Gli521 mutant, which was mutated at the 476 residue of Gli521 in wild-type, was grown as described earlier.47,48 The strain of M. mobile was cultured in the Aluotto medium at 25 °C. The M. mobile cells were cultured in the Aluotto medium at 25 °C.47 The strain of M. mobile, P476R Gli521 mutant, was used in this study. This mutant was isolated previously, as a spontaneous mutant, which was resistant to the inhibitory effects of a monoclonal antibody against Gli349, and featured by better binding in gliding than the wild-type strain.48 The genome DNA sequencing of the 30-kb region coding the gliding proteins revealed

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fluorescent excitation and localization based on EOT of light through periodic binary nanohole aperture arrays. The results revealed dynamics of M. mobile with nanoscale precision regarding the way that it glides, i.e., it glides with a fairly large axial variation Δz = 94 nm with an axial variance ratio at 43%. The sampling error achieved in this work is estimated to correspond to a resolution smaller than one tenth of the diffraction limit and thus significantly improves the conventional imaging resolution. The EOT-based localization sampling can provide an analytical tool to enlighten biomolecular dynamics with super-resolution in the threedimensional space.

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microscopy. Another strength of the approach is that the penetration of EOT is far deeper than under conventional TIR environment. Deeper penetration implies a longer dynamic range, which provides an added freedom when super-resolved sampling method is applied directly to intracellular phenomena that take place inside a cell. The trend of axial flexibility agrees well with recently emerging super-resolution approaches such as light sheet microscopy.43,44

that the features of this strain were caused by a single substitution from Proline to Arginine at the 476th amino acid residue in the Gli521 protein. For bacterial resuspension, nanoaperture surface was coated using sialylated oligosaccharides (SO) included in horse serum. As a result of mutation, its gliding speed was reduced, as the binding activity to glass treated by medium containing SO increased. The shape of M. mobile can be controlled into a spherical shape by suspending into Tris-based buffer for extracellular pH-change of medium or osmotic shock.35 Fluorescent labeling of M. mobile followed the procedure described in ref 36. M. mobile was cultured in an Aluotto medium including 2.1% (wt/vol) heart infusion broth, 0.56% yeast extract, 10% (v/v) horse serum, 0.025% thallium acetate, and 0.005% ampicillin, which was kept at 25 °C until 0.06 to 0.10 absorbance at 600 nm. 1 mL-volume cultured bacterial cells were centrifuged at 12 000g for 4 min, resuspended and incubated in the Aluotto medium for 30 min. Cy3-NHS ester (GE Healthcare) in a buffer of 75 mM sodium phosphate and 68.4 mM NaCl with 50 mM glucose at pH 7.4 was used for Cy3-labeling of M. mobile, which was incubated for 2 h at room temperature and cleaned by two times of centrifugation after suspensions using 500 and 200 μL of the buffer. Photobleaching. A control experiment was conducted to ensure the effect of photobleaching over the course of M. mobile gliding over arrays of nanoapertures (Figure S11). The results suggest that the intensity change due to photobleaching should be negligible. Image Analysis and Postprocessing. Image processing to extract axial information on gliding M. mobile in motion is initiated with calculation of electromagnetic field distribution (see Figure S7 for flowchart that describes the procedure): (1) stacked EOT field distribution in the lateral plane (xy plane) along the depth axis up to 1 μm (z = 1 μm) from surface (z = 0) at 20 nm interval, i.e., |E(x,y)|2zm=0,20,40,∼,960,980,1000nm (m = 0, 1, 2, ∼ , 49, 50) and (2) EOT field distribution in the axial plane (xz plane, y = 0), |E(x,z)|2y = 0. Sampling of M. mobile on EOT was performed in three steps: first, the center of brightness of M. mobile, c(r), was determined from each raw image in the entire image sequences (n) while a single bacterium glides on consecutive nanoholes using leastsquares fitting based on 2D Gaussian function, i.e., c(r)∼c(x, y, I). Gaussian nature of the incident light was taken into account by adjusting overall fluorescence intensity of the images acquired by EM-CCD based on the following equation: intensity, IL(x, y) = IL0exp{
[(x
x0)2 þ (y
y0)2]/2w2G}, where wG of the Gaussian beam was measured to be ∼53 pixels. (x0, y0) represents the pixel coordinate for the center of region of interest. Second, the effect of lateral displacement in the y-axis was compensated by lateral projection and linear interpolation. For lateral projection to the aperture center along the gliding x-axis, an axial index (m) corresponding to In(x, y), which represents a raw image sequence between I(x, y, zm) and I(x, y, zmþ1), was determined for each image. I(x, y, zm) and I(x, y, zmþ1) were then projected to the aperture center, i.e., I(x, y0, zm) and I(x, y0, zmþ1).

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Conflict of Interest: The authors declare no competing financial interest. Acknowledgment. This work was sponsored by the National Research Foundation (NRF) grants funded by the Korean Government (2011-0017500 and NRF-2012R1A4A1029061). This work is supported in part by Grant-in-Aid for Scientific Research on Innovative Areas (No. 26103527 “Fluctuation & Structure” to T. N.; No. 87003306 “Cilia & Centrosomes to T. N.; No. 24117002 “Motility Machinery” to T. N.) from the Ministry of Education, Culture, Sports, Science, and Technology of Japan. W. L. designed binary nanoholes, measured M. mobile gliding, performed analysis, and wrote the manuscript. Y. K. prepared M. mobile and helped measure the gliding. Y. O. and H. Y. fabricated nanoholes. N. M. helped set up optics for measurement. M. M. provided M. mobile and helped analyze the gliding. T. N. helped measure and analyze the gliding and wrote the manuscript. D. K. analyzed the data and wrote the manuscript. All authors reviewed the manuscript. Supporting Information Available: The Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/acsnano.5b03934. Figures S1
S12. (PDF) Movie S1. (AVI) Movie S2. (AVI) Movie S3. (AVI) Movie S4. (AVI)

REFERENCES AND NOTES 1. Wells, N. P.; Lessard, G. A.; Goodwin, P. M.; Phipps, M. E.; Cutler, P. J.; Lidke, D. S.; Wilson, B. S.; Werner, J. H. TimeResolved Three-Dimensional Molecular Tracking in Live Cells. Nano Lett. 2010, 10, 4732–4737. 2. Levi, V.; Ruan, Q.; Gratton, E. 3-D Particle Tracking in a TwoPhoton Microscope: Application to the Study of Molecular Dynamics in Cells. Biophys. J. 2005, 88, 2919–2928. 3. van den Broek, B.; Ashcroft, B.; Oosterkamp, T. H.; van Noort, J. Parallel Nanometric 3D Tracking of Intracellular Gold Nanorods Using Multifocal Two-Photon Microscopy. Nano Lett. 2013, 13, 980–986. 4. Pralle, A.; Prummer, M.; Florin, E.-L.; Stelzer, E. H. K.; Horber, J. K. H. Three-Dimensional High-Resolution Particle Tracking for Optical Tweezers by Forward Scattered Light. Microsc. Res. Tech. 1999, 44, 378–386. 5. Krishnan, M.; Mojarad, N.; Kukura, P.; Sandoghdar, V. Geometry-Induced Electrostatic Trapping of Nanometric Objects in a Fluid. Nature 2010, 467, 692–695. 6. Mojarad, N.; Krishnan, M. Measuring the Size and Charge of Single Nanoscale Objects in Solution Using an Electrostatic Fluidic Trap. Nat. Nanotechnol. 2012, 7, 448–452. 7. Belton, C. M.; Izutsu, K. T.; Goodwin, P. C.; Park, Y.; Lamont, R. J. Fluorescence Image Analysis of the Association between Porphyromonas Gingivalis and Gingival Epithelial Cells. Cell. Microbiol. 1999, 1, 215–223. 8. Turner, L.; Ryu, W. S.; Berg, H. C. Real-Time Imaging of Fluorescent Flagellar Filaments. J. Bacteriol. 2000, 182, 2793–2801.

LEE ET AL.

9. Pavani, S. R. P.; Thompson, M. A.; Biteen, J. S.; Lord, S. J.; Liu, N.; Twieg, R. J.; Piestun, R.; Moerner, W. E. ThreeDimensional, Single-Molecule Fluorescence Imaging beyond the Diffraction Limit by Using a Double-Helix Point Spread Function. Proc. Natl. Acad. Sci. U. S. A. 2009, 106, 2995–2999. 10. Liu, S.-L.; Li, J.; Zhang, Z.-L.; Wang, Z.-G.; Tian, Z.-Q.; Wang, G.-P.; Pang, D.-W. Fast and High-Accuracy Localization for Three-Dimensional Single-Particle Tracking. Sci. Rep. 2013, 3, 2462. 11. Juette, M. F.; Gould, T. J.; Lessard, M. D.; Mlodzianoski, M. J.; Nagpure, B. S.; Bennett, B. T.; Hess, S. T.; Bewersdorf, J. Three-Dimensional Sub
100 nm Resolution Fluorescence Microscopy of Thick Samples. Nat. Methods 2008, 5, 527–529. 12. Biteen, J. S.; Thompson, M. A.; Tselentis, N. K.; Bowman, G. R.; Shapiro, L.; Moerner, W. E. Super-Resolution Imaging in Live Caulobacter Crescentus Cells Using Photoswitchable EYFP. Nat. Methods 2008, 5, 947–949. 13. Gahlmann, A.; Ptacin, J. L.; Grover, G.; Quirin, S.; von Diezmann, A. R. S.; Lee, M. K.; Backlund, M. P.; Shapiro, L.; Piestun, R.; Moerner, W. E. Quantitative Multicolor Subdiffraction Imaging of Bacterial Protein Ultrastructures in Three Dimensions. Nano Lett. 2013, 13, 987–993. 14. Ebbesen, T. W.; Lezec, H. J.; Ghaemi, H. F.; Thio, T.; Wolff, P. A. Extraordinary Optical Transmission through SubWavelength Hole Arrays. Nature 1998, 391, 667–669. 15. Lalanne, P.; Rodier, J. C.; Hugonin, J. Surface Plasmons of Metallic Surfaces Perforated by Nanohole Arrays. J. Opt. A: Pure Appl. Opt. 2005, 7, 422–426. 16. Rindzevicius, T.; Alaverdyan, Y.; Sepulveda, B.; Pakizeh, T.; Käll, M.; Hillenbrand, R.; Aizpurua, J.; García de Abajo, F. J. Nanohole Plasmons in Optically Thin Gold Films. J. Phys. Chem. C 2007, 111, 1207–1212. 17. Kim, K.; Yajima, J.; Oh, Y.; Lee, W.; Oowada, S.; Nishizaka, T.; Kim, D. Nanoscale Localization Sampling Based on Nanoantenna Arrays for Super-Resolution Imaging of Fluorescent Monomers on Sliding Microtubules. Small 2012, 8, 892–900. 18. Balzarotti, F.; Stefani, F. D. Plasmonics Meets Far-Field Optical Nanoscopy. ACS Nano 2012, 6, 4580–4584. 19. Kim, K.; Choi, J.-W.; Ma, K.; Lee, R.; Yoo, K.-H.; Yun, C.-O.; Kim, D. Nanoislands-Based Random Activation of Fluorescence for Visualizing Endocytotic Internalization of Adenovirus. Small 2010, 6, 1293–1299. 20. Johnson, T. W.; Lapin, Z. J.; Beams, R.; Lindquist, N. C.; Rodrigo, S. G.; Novotny, L.; Oh, S.-H. Article Previous Article Next Article Table of Contents Highly Reproducible NearField Optical Imaging with Sub-20-nm Resolution Based on Template-Stripped Gold Pyramids. ACS Nano 2012, 6, 9168–9174. 21. Oh, Y.; Son, T.; Kim, S. Y.; Lee, W.; Yang, H.; Choi, J.; Shin, J.-S.; Kim, D. Surface Plasmon-Enhanced Nanoscopy of Intracellular Cytoskeletal Actin Filaments Using Random Nanodot Arrays. Opt. Express 2014, 22, 27695–27706. 22. Wertz, E.; Isaacoff, B. P.; Flynn, J. D.; Biteen, J. S. SingleMolecule Super-Resolution Microscopy Reveals How Light Couples to a Plasmonic Nanoantenna on the Nanometer Scale. Nano Lett. 2015, 15, 2662–2670. 23. Son, T.; Lee, W.; Kim, D. Localization-Based Full-Field Microscopy: How to Attain Super-Resolved Images. Sci. Rep. 2015, 5, 12365. 24. Shankar, S. S.; Rizzello, L.; Cingolani, R.; Rinaldi, R.; Pompa, P. P. Micro/Nanoscale Patterning of Nanostructured Metal Substrates for Plasmonic Applications. ACS Nano 2009, 3, 893–900. 25. Stranahan, S. M.; Willets, K. A. Super-Resolution Optical Imaging of Single-Molecule SERS Hot Spots. Nano Lett. 2010, 10, 3777–3784. 26. Weber, M. L.; Litz, J. P.; Masiello, D. J.; Willets, K. A. SuperResolution Imaging Reveals a Difference between SERS and Luminescence Centroids. ACS Nano 2012, 6, 1839–1848. 27. Lee, W.; Kim, K.; Kim, D. Electromagnetic Near-field Nanoantennas for Subdiffraction-Limited Surface PlasmonEnhanced Light Microscopy. IEEE J. Sel. Top. Quantum Electron. 2012, 18, 1684–1691.

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In(x, y0) after lateral displacement compensation was obtained from I(x, y0, zm) and I(x, y0, zmþ1) based on linear interpolation. Finally, each axial position c(x, y0, z) corresponding to In(x, y0) was determined from spatial field analysis of EOT. Axial movements (e.g., variations from the zero reference position, z = 0) were extracted for overall image sequences by sequential direct mapping of compensated intensity In(x, y0) to EOT field distribution |En(x, y0, z)|2z=0
1μm in the xz-plane within estimated error in the zero reference. The relation between axial displacement and intensity In is in general nonlinear and depends on lateral coordinate (x, y0). At an aperture center (x = 0, y0 = 0), as an example, an intensity decrease by 10% was accompanied by an increase of axial displacement by 96 nm for φ = 310 and 70 nm for φ = 410 nm over the linear range that encompasses the average axial displacement of M. mobile (Figure S12). The overall graphic illustration of the axial mapping process applied to the case of nanohole G in Figure 5 is provided in Figure S8.

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28. Titus, E. J.; Willets, K. A. Superlocalization SurfaceEnhanced Raman Scattering Microscopy: Comparing Point Spread Function Models in the Ensemble and SingleMolecule Limits. ACS Nano 2013, 7, 8284–8294. 29. Khatua, S.; Paulo, P. M. R.; Yuan, H.; Gupta, A.; Zijlstra, P.; Orrit, M. Resonant Plasmonic Enhancement of SingleMolecule Fluorescence by Individual Gold Nanorods. ACS Nano 2014, 8, 4440–4449. 30. Choi, J.; Kim, K.; Oh, Y.; Kim, A. L.; Kim, S. Y.; Shin, J.-S.; Kim, D. Extraordinary Transmission Based Plasmonic Nanoarrays for Axially Super-Resolved Cell Imaging. Adv. Opt. Mater. 2014, 2, 48–55. 31. Miyata, M.; Petersen, J. D. Spike Structure at the Interface between Gliding Mycoplasma Mobile Cells and Glass Surfaces Visualized by Rapid-Freeze-and-Fracture Electron Microscopy. J. Bacteriol. 2004, 186, 4382–4386. 32. Miyata, M. Molecular Mechanism of Mycoplasma Gliding;a Novel Cell Motility System. In Cell Motility; Lenz, P., Ed.; Springer: New York, 2007; pp 137
175. 33. Charon, N. W. Mycoplasma Takes a Walk. Proc. Natl. Acad. Sci. U. S. A. 2005, 102, 13713–13714. 34. Hiratsuka, Y.; Miyata, M.; Tada, T.; Uyeda, T. Q. P. A Microrotary Motor Powered by Bacteria. Proc. Natl. Acad. Sci. U. S. A. 2006, 103, 13618–13623. 35. Kasai, T.; Nakane, D.; Ishida, H.; Ando, H.; Kiso, M.; Miyata, M. Role of Binding in Mycoplasma Mobile and Mycoplasma Pneumoniae Gliding Analyzed Through Inhibition by Synthesized Sialylated Compounds. J. Bacteriol. 2013, 195, 429–435. 36. Nakane, D.; Miyata, M. Mycoplasma Mobile Cells Elongated by Detergent and Their Pivoting Movements in Gliding. J. Bacteriol. 2012, 194, 122–130. 37. Kinosita, Y.; Nakane, D.; Sugawa, M.; Masaike, T.; Mizutani, K.; Miyata, M.; Nishizaka, T. Unitary Step of Gliding Machinery in Mycoplasma Mobile. Proc. Natl. Acad. Sci. U. S. A. 2014, 111, 8601–8606. 38. Cheezum, M. K.; Walker, W. F.; Guilford, W. H. Quantitative Comparison of Algorithms for Tracking Single Fluorescent Particles. Biophys. J. 2001, 81, 2378–2388. 39. Toprak, E.; Balci, H.; Blehm, B. H.; Selvin, P. R. ThreeDimensional Particle Tracking via Bifocal Imaging. Nano Lett. 2007, 7, 2043–2045. 40. Weigel, A. V.; Simon, B.; Tamkun, M. M.; Krapf, D. Ergodic and Nonergodic Processes Coexist in the Plasma Membrane as Observed by Single-Molecule Tracking. Proc. Natl. Acad. Sci. U. S. A. 2011, 108, 6438–6443. 41. Thompson, R. E.; Larson, D. R.; Webb, W. W. Precise Nanometer Localization Analysis for Individual Fluorescent Probes. Biophys. J. 2002, 82, 2775–2783. 42. Hiratsuka, Y.; Miyata, M.; Uyeda, T. Q. P. Living Microtransporter by Uni-Directional Gliding of Mycoplasma along Microtracks. Biochem. Biophys. Res. Commun. 2005, 331, 318–324. 43. Tokunaga, M.; Imamoto, N.; Sakata-Sogawa, K. Highly inclined thin illumination enables clear single-molecule imaging in cells. Nat. Methods 2008, 5, 159–161. 44. Galland, R.; Grenci, G.; Aravind, A.; Viasnoff, V.; Studer, V.; Sibarita, J.-B. 3D high- and superresolution imaging using single-objective SPIM. Nat. Methods 2015, 12, 641–644. 45. Moharam, M. G.; Gaylord, T. K. Rigorous Coupled-Wave Analysis of Metallic Surface-Relief Gratings. J. Opt. Soc. Am. A 1986, 3, 1780–1787. 46. Edwards, D. F. Silicon (Si). In Handbook of Optical Constants of Solids; Palik, E. D., Ed.; Academic Press: Orlando, 1985; pp 547
569. 47. Miyata, M.; Yamamoto, H.; Shimizua, T.; Uenoyama, A.; Citti, C.; Rosengarten, R. Gliding Mutants of Mycoplasma Mobile: Relationships between Motility and Cell Morphology, Cell Adhesion and Microcolony Formation. Microbiology 2000, 146, 1311–1320. 48. Uenoyama, A.; Miyata, M. Gliding Ghosts of Mycoplasma Mobile. Proc. Natl. Acad. Sci. U. S. A. 2005, 102, 12754– 12758.

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