This work was supported by the National Institute of General Medical Sciences of the National Institutes of Health under award number R35GM124868 and by Duke University.

1. Setup Layout and Alignment
<ol>
	<li>Installation and collimation of the tracking excitation laser
	<ol>
		<li>Affix the laser to the optical table using a home-built mount. The mount is a simple aluminum plate with mounting holes for the laser head and the optical table. The laser should be firmly attached to a metal mount for stability and heat dissipation. For this work, use a 488 nm solid state laser for illumination (Figure 1), though the wavelength can be selected to suit a particular fluorophore or experiment. A critical factor is that the laser wavelength fit the 2D-EOD working range, which is determined primarily by the wave plate between the two deflectors (Figure 1: W2). The 488 nm laser can effectively excite the green or yellow fluorescent protein (GFP/YFP), which are common fluorescent tags in live cell experiments.</li>
		<li>Adjust the laser beam height and direction using a pair of dielectric mirrors (Figure 1: M). Make sure the laser beam is parallel to the optical table and adjust it to a suitable height. 
		NOTE: The height should be chosen based on the microscope platform. This height should be maintained for all subsequent mirrors used in this protocol, though it will not be explicitly stated.</li>
		<li>Collimate the beam with a pair of lenses (Figure 1: L1 and L2). The focal lengths of lenses should be carefully chosen to avoid the laser spot being clipped by the aperture of the 2D-EOD. Clipping is evident by a change in the laser beam shape after passing through the 2D-EOD. The quality of collimation here is very important because aberrations will be amplified by subsequent lenses and any divergence will deteriorate the performance of the 2D-EOD deflection. Ideally, collimate the beam by focusing the beam to a point at least 20 m away.</li>
	</ol>
	</li>
	<li>Place a pinhole (Figure 1: PH) of appropriate size at the focus of the first collimation lens (Figure 1: L1).
	<ol>
		<li>Choose an appropriately sized pinhole. The pinhole size can be chosen based on the following calculation: 
		<img alt="Equation 1" src="/files/ftp_upload/56711/56711eq1.jpg" /> 
		Where &#955; is the wavelength of laser, f is the focal length of the first lens, and D is the input beam diameter.</li>
		<li>Mount the pinhole on a 3D translation stage so that it can be placed precisely at the focus of the first collimation lens.</li>
		<li>Adjust the position of the pinhole. Place a laser power meter after the pinhole and adjust the pinhole position in XYZ to maximize the power meter readout. If a diffraction ring is observed, block it with an iris placed before the 2D-EOD.</li>
	</ol>
	</li>
	<li>Installation of Glan-Thompson polarizer
	<ol>
		<li>Put the Glan-Thompson polarizer (Figure 1: GP) after the second collimation lens (Figure 1: L2) to clean the polarization of the laser beam. Rotate the polarizer to find maximum transmission with the power meter.</li>
	</ol>
	</li>
	<li>Installation of EODs
	<ol>
		<li>Use 2 EODs (Figure 1: EOD1 &#38; EOD2) to deflect the laser in the X and Y directions. Maximize the laser transmission by adjusting the yaw, pitch, and height of each EOD.</li>
		<li>Align the two EODs with respect to each other using the alignment marker provided by the manufacturer on the side of each deflector.</li>
		<li>Apply a test pattern to the controller of the 2D-EOD to inspect the output of the EOD. This can either be the knight&#39;s tour (Figure 2) via the FPGA described below or a simple sine wave provided by a function generator. For the best performance, the deflection by each deflector should be parallel to either the X or Y direction of the piezo nanopositioner. This direction is dictated by the angular direction of the deflectors about the transmission axis. To rotate the deflection direction without moving the 2D-EOD, place a dove prism after the 2D-EOD to align the deflection axes to the piezo nanopositioner axes.</li>
	</ol>
	</li>
	<li>Installation of half-wave plate
	<ol>
		<li>Place a half-wave plate (Figure 1: W1) between the Glan-Thompson polarizer (Figure 1: GP) and the 2D-EOD to align the incoming laser beam polarization with the deflection axes of the 2D-EOD. Place a long focal lens (300 mm) after the 2D-EOD and place a sCMOS camera at the laser focus. Next, turn on the 2D-EOD to generate the knight&#39;s tour described below (Figure 2). Rotate the half-wave plate until an evenly square laser distribution is observed on the camera.</li>
	</ol>
	</li>
	<li>Installation of a beam expending lens pair and relay lens pair
	<ol>
		<li>Place a pair of lenses (Figure 1: L3 and L4) after the 2D-EOD to expand the beam to fill the back aperture of the objective lens (Figure 1: OL) and another pair of lenses (Figure 1: L5 and L6) to relay the focal plane to the microscope objective. Be sure to leave enough room between these two pairs of lenses as the TAG lens will be installed between them in a later step.</li>
	</ol>
	</li>
	<li>Install the dichroic filter, 10/90 beam splitter, focusing lens, APD, objective lens, and fluorescence emission filter to complete the detection pathway.
	<ol>
		<li>Install the dichroic filter (Figure 1: DC) to reflect the laser towards the objective lens. Align the laser to go straight through the center of the objective lens using two irises on the top and bottom of a long lens tube.</li>
		<li>Install a 10/90 beam splitter (Figure 1: BS) by which 10% of light is reflected for imaging by an sCMOS camera (described below) and 90% of passes through to the APD for tracking.</li>
		<li>Align the APD. Focus the laser onto a coverslip by the objective lens. Use the reflection from the coverslip to align all downstream elements by putting a coverslip at the objective focus and checking the intensity of the APD readout. After the beam splitter, install the APD focusing lens (Figure 1: L7) followed by the APD on a 3D translation stage. Position the lens such that the laser reflection from the objective goes through the center of the lens. The APD position can be optimized by adjusting the 3D position to maximize the intensity from the laser reflection on the coverslip. The APD position is at the optimal position when a move of the detector position in any direction decreases the intensity.</li>
		<li>Install a longpass fluorescence emission filter (Figure 1: F) before the beam splitter to remove the reflected and scattered light.</li>
	</ol>
	</li>
	<li>Installation of the TAG lens
	<ol>
		<li>Place the TAG lens between the two pairs of lenses (between Figure 1: L4 and L5) as mentioned before and shown in Figure 1. Adjust the yaw, pitch, height, and lateral position such that the beam passes perpendicularly through the center of TAG lens.</li>
	</ol>
	</li>
</ol>
2. Sample Preparation.
<ol>
	<li>Fixed particle preparation
	<ol>
		<li>Dilute 190 nm fluorescent beads to ~ 5 &#215; 108 beads/mL in PBS. Add 400 &#181;L beads solution onto a coverslip and mount on the sample holder of the piezoelectric stage (the volume of beads will depend on the sample holder; the diameter of the sample holder chamber used here is 18 mm). For the beads used here, PBS causes the particles to deposit on the coverslip.</li>
	</ol>
	</li>
	<li>Free moving particle preparation
	<ol>
		<li>Dilute 110 nm fluorescent beads to ~ 5 &#215; 108 beads/mL with DI water. Add 400 &#181;L beads solution onto a coverslip and mount onto the sample holder of the piezoelectric stage.</li>
	</ol>
	</li>
</ol>
3. Optimize Tracking Parameters
<ol>
	<li>Raster scan fixed particles
	<ol>
		<li>Put a fixed particle sample on the microscope.</li>
		<li>Turn on the laser, micropositioner controller, piezo nanopositioner controller, TAG lens controller, and EOD controller. Note that the order is not critical. Run the piezo nanopositioner in closed loop.</li>
		<li>Raster scan the sample in XYZ using a custom scanning software program (Figure S3, software available upon request from the authors), which drives the 2D-EOD in a knight&#39;s tour (Figure 2), collects counts from the APD, drives the piezo nanopositioner, and performs position calculation (Figure S2). The step size is 40 nm and the scanning range is 2 &#181;m.
		<ol>
			<li>To place the coverslip at the focus of the objective, remove the fluorescence emission filter and use the reflection of the laser from the coverslip to maximize the signal intensity as a function of the Z position of the micropositioner. After placing the sample at the focal plane, place back the fluorescence emission filter.</li>
			<li>Open the scanning program. Set the scanning range and step size by typing the number in the &#39;start&#39;, &#39;finish&#39;, and &#39;step&#39;. First set a large scanning range and step size to locate a particle (e.g., 10 x 10 &#181;m range with 200 nm step size). After finding the particle, shrink the scanning range and decrease step size (e.g., 2 x 2 &#181;m range with 100 nm step size). Click the &#39;scan&#39; button to perform a 3D raster scan to find the fluorescent focus.</li>
		</ol>
		</li>
	</ol>
	</li>
	<li>TAG lens settings (see also Figure 3)
	<ol>
		<li>Click on the TAG lens control software. Click &#39;connect&#39;, &#39;power on&#39; sequentially.</li>
		<li>To change the output phase of the trigger signals, it is necessary to change the output trigger mode. First change the mode from &#39;RGB&#39; to &#39;Multiplane&#39; and then change it back. Now the phase can be changed (Figure 3b).</li>
		<li>Set the output phase to be 0 &#176;, 90 &#176;, and 270 &#176;. While any three phases which cover the phase space can be used, these three are found to work well empirically (Figure 3c).</li>
		<li>Select the 68,500 Hz frequency setting.</li>
		<li>To find the optimal frequency it is often necessary to change the frequency search range. Click &#39;advanced&#39;, &#39;setting&#39;. Change the &#39;Max. Freq(Hz)&#39; of column 0 from 70,000 Hz to 71,500 Hz. This can be adjusted to whatever frequency range is appropriate. Click &#39;Save Calibration&#39;, &#39;Exit Calibration&#39; (Figure 3d).</li>
		<li>To make the new calibration effective, switch the resonance to another frequency (for example, 189,150 Hz) and then switched back to the 68,500 Hz frequency setting (Figure 3e).</li>
		<li>Change the amplitude gradually to 35%. Click &#39;Lock Resonance&#39;. After the frequency is locked, click &#39;Unlock Resonance&#39; (Figure 3e). The TAG lens is ready to use now.</li>
		<li>To calibrate, change the parameters that are used in the estimation to make the estimated position equal to the real position, as shown in Figure 4e, f. Input the scanning range of x, y, and z and then click the &#39;scan&#39; button to scan the sample in XYZ to move the particle through the moving laser spot. The position of the particle as it is scanned through the laser focus should agree with the estimated particle position determined by the position estimation loop (Figure S1). The relationship between the estimated position and real position (Figure 4d) can be extracted from estimated position images (Figure 4f). If the positions do not agree, adjust the values of laser position (ck) used in the position estimation loop (Figure S1).</li>
		<li>Align TAG lens
		<ol>
			<li>When the TAG lens controller is off, the raster scanned particle images (described below) taken before installing TAG lens and after installing TAG lens should look identical. Next, perform fluorescent particle Z stack scanning by moving the objective with the z nanopositioner to tune the position and angle of TAG lens (Figure 4). Tune the position of the TAG lens until there is no drift in the particle images in XY plane along the Z direction, which is achieved when there is no change in the XY position of the particle as a function of the Z position (Figure 4d). The tracking system is ready to use after alignment of the TAG lens.</li>
		</ol>
		</li>
	</ol>
	</li>
	<li>Installation of sCMOS camera for particle monitoring
	<ol>
		<li>Install a sCMOS camera to visualize particles while they are being tracked. Install the sCMOS only after the all the components of the tracking system have been installed and optimized. Load a fixed fluorescent particle sample onto the microscope and run the tracking program to lock one particle in the objective focal volume. Then, install the 100 mm focal length lens (Figure 1: L8) and sCMOS. Adjust the sCMOS position so that the image of the particle is focused to the smallest and brightest spot.</li>
	</ol>
	</li>
</ol>
4. Real-time 3D Tracking of Freely Diffusing Nanoparticles
<ol>
	<li>Put the 110 nm free moving particle sample on the microscope.</li>
	<li>Turn on laser, micro-positioner controller, piezo nanopositioner controller, TAG lens controller, and EOD controller. Run the piezo nanopositioner in open loop. Set the TAG lens software according to step 3.2.</li>
	<li>Open and run the tracking software (available upon request from the authors). Set the position estimation parameters to their optimized values, which were found in Section 3.</li>
	<li>To place the coverslip at the focus of the objective, remove the fluorescence emission filter and use the reflection of the laser from the coverslip to maximize the signal intensity as a function of the Z position of the micropositioner. After finding the coverslip, increase the focus position 15 &#181;m to focus the laser away from the coverslip and into the solution. Place back the fluorescence emission filter.</li>
	<li>Set the integral control constants. The integral control constants can be set starting at a low value and slowly increasing until oscillations can be seen in the particle&#39;s position readouts. Once oscillations are observed, set the integral control constants to 80% of the value causing the oscillations. Typical values will be around 0.012 for the XY &#39;integral gain&#39; and 0.004 for the Z &#39;integral gain&#39;.</li>
	<li>Set the tracking thresholds in &#39;Track Threshold&#39; and &#39;Track Minimum&#39; and start the tracking experiment by clicking &#39;Search&#39; and &#39;Auto Track&#39;. The threshold for terminating tracking is set slightly higher than the background level and the threshold for triggering tracking is about two times higher than the background. Here, the threshold for triggering tracking is 3 kHz and the threshold for ending the trajectory is 1.5 kHz.</li>
</ol>

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C., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Deep+and+high-resolution+three-dimensional+tracking+of+single+particles+using+nonlinear+and+multiplexed+illumination.">Deep and high-resolution three-dimensional tracking of single particles using nonlinear and multiplexed illumination.</a> Nat Commun. 6, (2015).</li><li>Hou, S., Lang, X., Welsher, K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Robust+real-time+3D+single-particle+tracking+using+a+dynamically+moving+laser+spot.">Robust real-time 3D single-particle tracking using a dynamically moving laser spot.</a> Opt. Lett. 42 (12), 2390-2393 (2017).</li><li>Chenouard, N., Smal, I., de Chaumont, F., Maska, M., Sbalzarini, I. F., Gong, Y., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Objective+comparison+of+particle+tracking+methods.">Objective comparison of particle tracking methods.</a> Nat Meth. 11 (3), 281-289 (2014).</li><li>Shechtman, Y., Weiss, L. E., Backer, A. S., Sahl, S. J., Moerner, W. E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Precise+3D+scan-free+multiple-particle+tracking+over+large+axial+ranges+with+Tetrapod+point+spread+functions.">Precise 3D scan-free multiple-particle tracking over large axial ranges with Tetrapod point spread functions.</a> Nano Lett. 15 (6), 4194-4199 (2015).</li><li>Lee, H. -. l. D., Sahl, S. J., Lew, M. D., Moerner, W. E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+double-helix+microscope+super-resolves+extended+biological+structures+by+localizing+single+blinking+molecules+in+three+dimensions+with+nanoscale+precision.">The double-helix microscope super-resolves extended biological structures by localizing single blinking molecules in three dimensions with nanoscale precision.</a> Appl. Phys. Lett. 100 (15), 153701 (2012).</li><li>Pavani, S. R. P., Thompson, M. A., Biteen, J. S., Lord, S. J., Liu, N., Twieg, R. J., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Three-dimensional,+single-molecule+fluorescence+imaging+beyond+the+diffraction+limit+by+using+a+double-helix+point+spread+function.">Three-dimensional, single-molecule fluorescence imaging beyond the diffraction limit by using a double-helix point spread function.</a> Proc. Natl. Acad. Sci. U.S.A. 106 (9), 2995-2999 (2009).</li><li>Sancataldo, G., Scipioni, L., Ravasenga, T., Lanzan&#242;, L., Diaspro, A., Barberis, A., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Three-dimensional+multiple-particle+tracking+with+nanometric+precision+over+tunable+axial+ranges.">Three-dimensional multiple-particle tracking with nanometric precision over tunable axial ranges.</a> Optica. 4 (3), 367-373 (2017).</li><li>Balzarotti, F., Eilers, Y., Gwosch, K. C., Gynn&#229;, A. H., Westphal, V., Stefani, F. D., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Nanometer+resolution+imaging+and+tracking+of+fluorescent+molecules+with+minimal+photon+fluxes.">Nanometer resolution imaging and tracking of fluorescent molecules with minimal photon fluxes.</a> Science. 355 (6325), 606 (2017).</li><li>Duocastella, M., Theriault, C., Arnold, C. B. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Three-dimensional+particle+tracking+via+tunable+color-encoded+multiplexing.">Three-dimensional particle tracking via tunable color-encoded multiplexing.</a> Opt. Lett. 41 (5), 863-866 (2016).</li><li>Duocastella, M., Sun, B., Arnold, C. B. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Simultaneous+imaging+of+multiple+focal+planes+for+three-dimensional+microscopy+using+ultra-high-speed+adaptive+optics.">Simultaneous imaging of multiple focal planes for three-dimensional microscopy using ultra-high-speed adaptive optics.</a> BIOMEDO. 17 (5), (2012).</li><li>Mermillod-Blondin, A., McLeod, E., Arnold, C. B. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=High-speed+varifocal+imaging+with+a+tunable+acoustic+gradient+index+of+refraction+lens.">High-speed varifocal imaging with a tunable acoustic gradient index of refraction lens.</a> Opt. Lett. 33 (18), 2146-2148 (2008).</li><li>Wang, Q., Moerner, W. 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The authors declare no competing financial interests.

Although many varieties of 3D single particle tracking methods have emerged in recent years, robust real-time tracking of high speed 3D diffusion at low photon count rates with a simple setup is still a challenge, which limits its application to important biological problems. The 3D-DyPLoT method described in this protocol addresses these challenges in a several ways. First, the excitation and detection pathways are simplified greatly compared to other implementations making alignment simple and robust. Secondly, the mov...

The emergence of advanced imaging techniques has opened a window to see ever more detailed structure of cellular phenomena, all the way down to the molecular level. Methods such as stochastic optical reconstruction microscopy (STORM)1,2,3, photo-activated localization microscopy (PALM)4,5,6,7, structured illumination microscopy (SIM)8,9,10,11, and stimulated emission depletion microscopy (STED)12,13,14 have gone far beyond the diffraction limit to deliver unprecedented detail into the structure and function of live cells. However, full understanding of how these systems behave requires dynamic information as well as structural information. The super-resolution methods listed above involve a trade-off between spatial resolution and temporal resolution, limiting the temporal precision with which dynamic processes can be probed. A method which provides both high spatial precision and temporal resolution is RT-3D-SPT15,16,17,18,19,20,21,22,23,24,25,26,27,28,29. Here, we draw a distinction between traditional 3D-SPT30 and RT-3D-SPT. Traditional 3D-SPT simply requires a time series of three-dimensional image data (which can be acquired either using a confocal microscope or an epifluorescence microscope given the right configuration). In traditional 3D-SPT, the coordinates of the particle are determined after data collection by locating the particle in each image stack and concatenating the locations in successive volumes to create a trajectory. For these methods, the ultimate temporal resolution is determined by the volumetric imaging rate. For confocal microscopes, this is easily on the scale of seconds to tens of seconds. For epifluorescence methods, wherein the optical path is manipulated so that the axial location information can be extracted, the temporal resolution is limited by the camera exposure or readout time. These epifluorescent methods are limited in the range over which axial information can be collected, though recent progress in Fourier plane phase masks design and adaptive optics is extending these ranges to 10 &#181;m or more31,32,33,34.
In contrast, RT-3D-SPT does not rely on acquiring a 3D image stack and finding particles after the fact. Instead, real-time location information is extracted via single point detectors and feedback is applied to effectively &#34;lock&#34; the particle in the focal volume of the objective lens through the use of a highspeed piezoelectric stage. This allows continuous measurement of the particle&#39;s position limited only by how many photons can be collected. Moreover, this method enables spectral interrogation of the particle as it moves over long ranges. RT-3D-SPT in effect works akin to a force-free optical trap for nanoscale objects, wherein the particle is continuously probed and measured in real-time without the need for large laser powers or optical forces. Given that RT-3D-SPT provides a means for continuous interrogation of fast diffusive objects (up to 20 &#181;m2/s)25,29 in three dimensions at low photon count rates20,29,35, it should provide a window into fast or transient biological processes such as intracellular cargo transport, ligand-receptor binding, and the extracellular dynamics of single virions. However, to this point, the application of RT-3D-SPT has been limited to the handful of groups working to advance this technology.
One barrier is the complexity of the optical layout required by RT-3D-SPT methods, which are varied. For most methods, the optical feedback is provided by a piezoelectric stage. As the particle makes small movements in X, Y, or Z, readouts from single point detectors are converted to error functions and fed at high-speed to a piezoelectric nanopositioner, which in turn moves the sample to counteract the particle&#39;s motion, effectively locking it in place relative to the objective lens. To measure small positional movements in X, Y, and Z, either multiple detectors (4 or 5 depending on the implementation)15,18,21 or multiple excitation spots (2 - 4, the lower of which can be applied if a lock-in amplifier is used to extract X and Y position using a rotating laser spot)25,28 are applied. The overlap of these multiple detection and emission spots make the systems difficult to align and maintain.
Herein, we present a high-speed target-locked 3D-SPT method with a simplified optical design called 3D-DyPLoT29. 3D-DyPLoT uses a 2D-EOD and a TAG lens36,37,38 to dynamically move a focused laser spot through the objective focal volume at a high rate (50 kHz XY, 70 kHz Z). Combining the laser focus position and the photon arrival time enables the particle&#39;s 3D position to be rapidly obtained even at low photon count rates. The 2D-EOD drives the laser focus in a knight&#39;s tour pattern39 with a square size of 1 x 1 &#181;m in the X-Y plane and the TAG lens moves the laser focus in axial direction with a range of 2 - 4 &#181;m. The 3D particle position is obtained with an optimized position estimation algorithm29,40 in 3D. The control of the 3D dynamically moving laser spot, photon counting from the avalanche photodiode (APD), real-time particle position calculation, piezoelectric stage feedback, and data recording are performed on a field programmable gate array (FPGA). In this protocol, we describe how to build a 3D-DyPLoT microscope step-by-step, including optical alignment, calibration with fixed particles, and finally free particle tracking. As a demonstration, 110 nm fluorescent beads were tracked continuously in water for minutes at a time.
The method described herein is an ideal choice for any application where it is desired to continuously monitor a fast-moving fluorescent probe at low light levels, including viruses, nanoparticles, and vesicles such as endosomes. In contrast to previous methods, there is only a single excitation and single detection pathway, making alignment and maintenance straightforward. Furthermore, the large detection area enables this microscope to easily pick up quickly diffusing particles, while the ability to track at low signal levels (down to 10 kHz) makes this method ideal for low-light applications29.

<table border="0" cellpadding="0" cellspacing="0" width="1075">
	<tbody>
		<tr height="21">
			<td height="21" style="height:21px;width:229px;">2D Electro-optic Deflector&#160;</td>
			<td style="width:145px;">ConOptics</td>
			<td style="width:160px;">M310A</td>
			<td style="width:541px;">2 required</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:229px;">Power supply for EOD</td>
			<td style="width:145px;">ConOptics</td>
			<td style="width:160px;">412</td>
			<td>Converts FPGA ouput to high voltage for EOD</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:229px;">TAG&#160; Lens</td>
			<td style="width:145px;">TAG Optics</td>
			<td style="width:160px;">TAG 2.0</td>
			<td>Used to deflect laser along axial direction</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:229px;">XY piezoelectric nanopositioner</td>
			<td style="width:145px;">MadCity Labs</td>
			<td style="width:160px;">Nano-PDQ275HS</td>
			<td>Used for moving the sample to lock the particle in the objective focal volume in&#160;</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:229px;">Z piezoelectric nanoposiitoner</td>
			<td style="width:145px;">MadCity Labs</td>
			<td style="width:160px;">Nano-OP65HS</td>
			<td>Used to move the objective lens to follow the diffusing particle</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:229px;">Micropositioner</td>
			<td style="width:145px;">MadCity Labs</td>
			<td style="width:160px;">MicroDrive</td>
			<td>Used to coarsely position sample and evaluate</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:229px;">Objective Lens</td>
			<td style="width:145px;">Zeiss</td>
			<td style="width:160px;">PlanApo</td>
			<td>High numerical aperture required for best sensitivity. 100X, 1.49 NA, M27, Zeiss</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:229px;">sCMOS camera</td>
			<td style="width:145px;">PCO</td>
			<td style="width:160px;">pco.edge 4.2</td>
			<td>Used to monitor the particle&#39;s position</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:229px;">APD</td>
			<td style="width:145px;">Excelitas</td>
			<td style="width:160px;">SPCM-ARQH-15</td>
			<td>Lower dark counts beneficial</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:229px;">Field programmable gate array</td>
			<td style="width:145px;">National Instruments</td>
			<td style="width:160px;">NI-7852r</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:229px;">Software</td>
			<td style="width:145px;">National Instruments</td>
			<td style="width:160px;">LabVIEW</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:229px;">Tracking excitation laser</td>
			<td style="width:145px;">JDSU</td>
			<td style="width:160px;">FCD488-30</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:229px;">Lens</td>
			<td style="width:145px;">ThorLabs</td>
			<td style="width:160px;">AC254-150-A-ML</td>
			<td>L1</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:229px;">Lens</td>
			<td style="width:145px;">ThorLabs</td>
			<td style="width:160px;">AC254-200-A-ML</td>
			<td>L2</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:229px;">Pinhole</td>
			<td style="width:145px;">ThorLabs</td>
			<td style="width:160px;">P75S</td>
			<td>PH</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:229px;">Glan-Thompson Polarizer</td>
			<td style="width:145px;">ThorLabs</td>
			<td style="width:160px;">GTH5-A</td>
			<td>GT</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:229px;">Half-wave plate</td>
			<td style="width:145px;">ThorLabs</td>
			<td style="width:160px;">WPH05M-488</td>
			<td>WP</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:229px;">Lens</td>
			<td style="width:145px;">ThorLabs</td>
			<td style="width:160px;">AC254-75-A-ML</td>
			<td>L3</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:229px;">Lens</td>
			<td style="width:145px;">ThorLabs</td>
			<td style="width:160px;">AC254-250-A-ML</td>
			<td>L4</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:229px;">Lens</td>
			<td style="width:145px;">ThorLabs</td>
			<td style="width:160px;">AC254-200-A-ML</td>
			<td>L5</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:229px;">Lens</td>
			<td style="width:145px;">ThorLabs</td>
			<td style="width:160px;">AC254-200-A-ML</td>
			<td>L6</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:229px;">Dichroic Mirror</td>
			<td style="width:145px;">Chroma</td>
			<td style="width:160px;">ZT405/488/561/640rpc</td>
			<td>DC</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:229px;">Fluorescence Emission Filter</td>
			<td style="width:145px;">Chroma</td>
			<td style="width:160px;">D535/40m</td>
			<td>F</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:229px;">10/90 beamsplitter</td>
			<td style="width:145px;">Chroma</td>
			<td style="width:160px;">21012</td>
			<td>BS</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">PBS</td>
			<td>Sigma</td>
			<td>D8537</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">190 nm fluorescent nanoparticles</td>
			<td>Bangs laboratories</td>
			<td>FC02F/9942</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">110 nm fluorescent nanoparticles</td>
			<td>Bangs laboratories</td>
			<td>FC02F/10617</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">Coverslip</td>
			<td>Fisher Scientific</td>
			<td>12-545A</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:229px;">Powermeter</td>
			<td style="width:145px;">Thorlabs</td>
			<td style="width:160px;">PM100D</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:229px;">CMOS</td>
			<td style="width:145px;">Thorlabs</td>
			<td style="width:160px;">DCC1545M</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:229px;">Iris</td>
			<td style="width:145px;">Thorlabs</td>
			<td style="width:160px;">SM1D12D</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">Microscope</td>
			<td style="width:145px;">Mad City Labs</td>
			<td style="width:160px;">RM21</td>
			<td></td>
		</tr>
	</tbody>
</table>

a protocol for real-time 3d single particle tracking

Real-time three-dimensional single particle tracking (RT-3D-SPT) has the potential to shed light on fast, 3D processes in cellular systems. Although various RT-3D-SPT methods have been put forward in recent years, tracking high speed 3D diffusing particles at low photon count rates remains a challenge. Moreover, RT-3D-SPT setups are generally complex and difficult to implement, limiting their widespread application to biological problems. This protocol presents a RT-3D-SPT system named 3D Dynamic Photon Localization Tracking (3D-DyPLoT), which can track particles with high diffusive speed (up to 20 &#181;m2/s) at low photon count rates (down to 10 kHz). 3D-DyPLoT employs a 2D electro-optic deflector (2D-EOD) and a tunable acoustic gradient (TAG) lens to drive a single focused laser spot dynamically in 3D. Combined with an optimized position estimation algorithm, 3D-DyPLoT can lock onto single particles with high tracking speed and high localization precision. Owing to the single excitation and single detection path layout, 3D-DyPLoT is robust and easy to set up. This protocol discusses how to build 3D-DyPLoT step by step. First, the optical layout is described. Next, the system is calibrated and optimized by raster scanning a 190 nm fluorescent bead with the piezoelectric nanopositioner. Finally, to demonstrate real-time 3D tracking ability, 110 nm fluorescent beads are tracked in water.

Fixed particle scanning (Figure 4) and freely diffusing 110 nm fluorescent particle tracking (Figure 5) were performed following the protocol above. The particle scanning was performed by moving the piezoelectric nanopositioner and bin photons while simultaneously calculating the particle&#39;s estimated position at each point in the scan. The scanning image shows a square of even intensity (Figure 4a</strong...

Watch this Scientific Journal Video about A Protocol for Real-time 3D Single Particle Tracking at JoVE.com

A Protocol for Real-time 3D Single Particle Tracking

This protocol details the construction and operation of a real-time 3D single particle tracking microscope capable of tracking nanoscale fluorescent probes at high diffusive speeds and low photon count rates.

Real-time three-dimensional single particle tracking (RT-3D-SPT) has the potential to shed light on fast, 3D processes in cellular systems. Although ...

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Bioengineering

14.8K Views.  Duke University. This protocol details the construction and operation of a real-time 3D single particle tracking microscope capable of tracking nanoscale fluorescent probes at high diffusive speeds and low photon count rates.

Video: A Protocol for Real-time 3D Single Particle Tracking

A Simple Hanging Drop Cell Culture Protocol for Generation of 3D Spheroids

Studies of cell-cell cohesion and cell-substratum adhesion have historically been performed on monolayer cultures adherent to rigid substrates. Cells within a tissue, however, are typically encased within a closely packed tissue mass in which cells establish intimate connections with many near-neighbors and with extracellular matrix components. Accordingly, the chemical milieu and physical forces experienced by cells within a 3D tissue are fundamentally different than those experienced by cells grown in monolayer culture. This has been shown to markedly impact cellular morphology and signaling. Several methods have been devised to generate 3D cell cultures including encapsulation of cells in collagen gels1or in biomaterial scaffolds2. Such methods, while useful, do not recapitulate the intimate direct cell-cell adhesion architecture found in normal tissues. Rather, they more closely approximate culture systems in which single cells are loosely dispersed within a 3D meshwork of ECM products. Here, we describe a simple method in which cells are placed in hanging drop culture and incubated under physiological conditions until they form true 3D spheroids in which cells are in direct contact with each other and with extracellular matrix components. The method requires no specialized equipment and can be adapted to include addition of any biological agent in very small quantities that may be of interest in elucidating effects on cell-cell or cell-ECM interaction. The method can also be used to co-culture two (or more) different cell populations so as to elucidate the role of cell-cell or cell-ECM interactions in specifying spatial relationships between cells. Cell-cell cohesion and cell-ECM adhesion are the cornerstones of studies of embryonic development, tumor-stromal cell interaction in malignant invasion, wound healing, and for applications to tissue engineering. This simple method will provide a means of generating tissue-like cellular aggregates for measurement of biomechanical properties or for molecular and biochemical analysis in a physiologically relevant model.

We describe a simple, rapid method of generating 3D tissue-like spheroids and their potential application to quantify differences in cell-cell interactions.

Studies of cell-cell cohesion and cell-substratum adhesion have historically been performed on monolayer cultures adherent to rigid substrates. Cells ...

Longitudinal Measurement of Extracellular Matrix Rigidity in 3D Tumor Models Using Particle-tracking Microrheology

The mechanical microenvironment has been shown to act as a crucial regulator of tumor growth behavior and signaling, which is itself remodeled and modified as part of a set of complex, two-way mechanosensitive interactions. While the development of biologically-relevant 3D tumor models have facilitated mechanistic studies on the impact of matrix rheology on tumor growth, the inverse problem of mapping changes in the mechanical environment induced by tumors remains challenging. Here, we describe the implementation of particle-tracking microrheology (PTM) in conjunction with 3D models of pancreatic cancer as part of a robust and viable approach for longitudinally monitoring physical changes in the tumor microenvironment, in situ. The methodology described here integrates a system of preparing in vitro 3D models embedded in a model extracellular matrix (ECM) scaffold of Type I collagen with fluorescently labeled probes uniformly distributed for position- and time-dependent microrheology measurements throughout the specimen. In vitro tumors are plated and probed in parallel conditions using multiwell imaging plates. Drawing on established methods, videos of tracer probe movements are transformed via the Generalized Stokes Einstein Relation (GSER) to report the complex frequency-dependent viscoelastic shear modulus, G*(&#969;). Because this approach is imaging-based, mechanical characterization is also mapped onto large transmitted-light spatial fields to simultaneously report qualitative changes in 3D tumor size and phenotype. Representative results showing contrasting mechanical response in sub-regions associated with localized invasion-induced matrix degradation as well as system calibration, validation data are presented. Undesirable outcomes from common experimental errors and troubleshooting of these issues are also presented. The 96-well 3D culture plating format implemented in this protocol is conducive to correlation of microrheology measurements with therapeutic screening assays or molecular imaging to gain new insights into impact of treatments or biochemical stimuli on the mechanical microenvironment.

Particle-tracking microrheology can be used to non-destructively quantify and spatially map changes in extracellular matrix mechanical properties in 3D tumor models.

The mechanical microenvironment has been shown to act as a crucial regulator of tumor growth behavior and signaling, which is itself remodeled and ...

3D Orbital Tracking in a Modified Two-photon Microscope: An Application to the Tracking of Intracellular Vesicles

The objective of this video protocol is to discuss how to perform and analyze a three-dimensional fluorescent orbital particle tracking experiment using a modified two-photon microscope1. As opposed to conventional approaches (raster scan or wide field based on a stack of frames), the 3D orbital tracking allows to localize and follow with a high spatial (10 nm accuracy) and temporal resolution (50 Hz frequency response) the 3D displacement of a moving fluorescent particle on length-scales of hundreds of microns2. The method is based on a feedback algorithm that controls the hardware of a two-photon laser scanning microscope in order to perform a circular orbit around the object to be tracked: the feedback mechanism will maintain the fluorescent object in the center by controlling the displacement of the scanning beam3-5. To demonstrate the advantages of this technique, we followed a fast moving organelle, the lysosome, within a living cell6,7. Cells were plated according to standard protocols, and stained using a commercially lysosome dye. We discuss briefly the hardware configuration and in more detail the control software, to perform a 3D orbital tracking experiment inside living cells. We discuss in detail the parameters required in order to control the scanning microscope and enable the motion of the beam in a closed orbit around the particle. We conclude by demonstrating how this method can be effectively used to track the fast motion of a labeled lysosome along microtubules in 3D within a live cell. Lysosomes can move with speeds in the range of 0.4-0.5 &#181;m/sec, typically displaying a directed motion along the microtubule network8.

In this video protocol we track - at high speed and in three dimensions - fluorescently labeled lysosomes within living cells, using the orbital tracking method in a modified two-photon microscope.

The objective of this video protocol is to discuss how to perform and analyze a three-dimensional fluorescent orbital particle tracking experiment using a ...

Ordering Single Cells and Single Embryos in 3D Confinement: A New Device for High Content Screening

Biological cells are usually observed on flat (2D) surfaces. This condition is not physiological, and phenotypes and shapes are highly variable. Screening based on cells in such environments have therefore serious limitations: cell organelles show extreme phenotypes, cell morphologies and sizes are heterogeneous and/or specific cell organelles cannot be properly visualized. In addition, cells in vivo are located in a 3D environment; in this situation, cells show different phenotypes mainly because of their interaction with the surrounding extracellular matrix of the tissue. In order to standardize and generate order of single cells in a physiologically-relevant 3D environment for cell-based assays, we report here the microfabrication and applications of a device for in vitro 3D cell culture. This device consists of a 2D array of microcavities (typically 105 cavities/cm2), each filled with single cells or embryos. Cell position, shape, polarity and internal cell organization become then normalized showing a 3D architecture. We used replica molding to pattern an array of microcavities, &#8216;eggcups&#8217;, onto a thin polydimethylsiloxane (PDMS) layer adhered on a coverslip. Cavities were covered with fibronectin to facilitate adhesion. Cells were inserted by centrifugation. Filling percentage was optimized for each system allowing up to 80%. Cells and embryos viability was confirmed. We applied this methodology for the visualization of cellular organelles, such as nucleus and Golgi apparatus, and to study active processes, such as the closure of the cytokinetic ring during cell mitosis. This device allowed the identification of new features, such as periodic accumulations and inhomogeneities of myosin and actin during the cytokinetic ring closure and compacted phenotypes for Golgi and nucleus alignment. We characterized the method for mammalian cells, fission yeast, budding yeast, C. elegans with specific adaptation in each case. Finally, the characteristics of this device make it particularly interesting for drug screening assays and personalized medicine.

We report a device and a new method to study cells and embryos. Single cells are precisely ordered in microcavity arrays. Their 3D confinement is a step towards 3D environments encountered in physiological conditions and allows organelle orientation. By controlling cell shape, this setup minimizes variability reported in standard assays.

Biological cells are usually observed on flat (2D) surfaces. This condition is not physiological, and phenotypes and shapes are highly variable. Screening ...

In Situ Mapping of the Mechanical Properties of Biofilms by Particle-tracking Microrheology

Bacterial cells are able to form surface-attached biofilm communities known as biofilms by encasing themselves in extracellular polymeric substances (EPS). The EPS serves as a physical and protective scaffold that houses the bacterial cells and consists of a variety of materials that includes proteins, exopolysaccharides and DNA. The composition of the EPS may change, which remodels the mechanic properties of the biofilm to further develop or support alternative biofilm structures, such as streamers, as a response to environmental cues. Despite this, there are little quantitative descriptions on how EPS components contribute to the mechanical properties and function of biofilms. Rheology, the study of the flow of matter, is of particular relevance to biofilms as many biofilms grow in flow conditions and are constantly exposed to shear stress. It also provides measurement and insight on the spreading of the biofilm on a surface. Here, particle-tracking microrheology is used to examine the viscoelasticity and effective crosslinking roles of different matrix components in various parts of the biofilm during development. This approach allows researchers to measure mechanic properties of biofilms at the micro-scale, which might provide useful information for controlling and engineering biofilms.

In Situ Mapping of the Mechanical Properties of Biofilms by Particle-tracking Microrheology

Particle-tracking microrheology investigates the viscoelasticity of materials. Here, the technique is used to determine the viscoelasticity, creep compliance and effective crosslinking roles of different matrix components of a bacterial biofilm. The matrix consists of polymeric substances secreted by the bacteria and its components determine biofilm structure and mechanical properties.

Bacterial cells are able to form surface-attached biofilm communities known as biofilms by encasing themselves in extracellular polymeric substances ...

Real Time Monitoring of Intracellular Bile Acid Dynamics Using a Genetically Encoded FRET-based Bile Acid Sensor

F&#246;rster Resonance Energy Transfer (FRET) has become a powerful tool for monitoring protein folding, interaction and localization in single cells. Biosensors relying on the principle of FRET have enabled real-time visualization of subcellular signaling events in live cells with high temporal and spatial resolution. Here, we describe the application of a genetically encoded Bile Acid Sensor (BAS) that consists of two fluorophores fused to the farnesoid X receptor ligand binding domain (FXR-LBD), thereby forming a bile acid sensor that can be activated by a large number of bile acids species and other (synthetic) FXR ligands. This sensor can be targeted to different cellular compartments including the nucleus (NucleoBAS) and cytosol (CytoBAS) to measure bile acid concentrations locally. It allows rapid and simple quantitation of cellular bile acid influx, efflux and subcellular distribution of endogenous bile acids without the need for labeling with fluorescent tags or radionuclei. Furthermore, the BAS FRET sensors can be useful for monitoring FXR ligand binding. Finally, we show that this FRET biosensor can be combined with imaging of other spectrally distinct fluorophores. This allows for combined analysis of intracellular bile acid dynamics and i) localization and/or abundance of proteins of interest, or ii) intracellular signaling in a single cell.

We provide a detailed protocol to study bile acid dynamics in living cells using a genetically encoded BAS FRET sensor. This Bile Acid Sensor represents a unique tool to study (regulation of) bile acid transport and FXR activation in a wide range of cell types.

F&#246;rster Resonance Energy Transfer (FRET) has become a powerful tool for monitoring protein folding, interaction and localization in single cells. ...

Micropatterning and Assembly of 3D Microvessels

In vitro platforms to study endothelial cells and vascular biology are largely limited to 2D endothelial cell culture, flow chambers with polymer or glass based substrates, and hydrogel-based tube formation assays. These assays, while informative, do not recapitulate lumen geometry, proper extracellular matrix, and multi-cellular proximity, which play key roles in modulating vascular function. This manuscript describes an injection molding method to generate engineered vessels with diameters on the order of 100 &#181;m. Microvessels are fabricated by seeding endothelial cells in a microfluidic channel embedded within a native type I collagen hydrogel. By incorporating parenchymal cells within the collagen matrix prior to channel formation, specific tissue microenvironments can be modeled and studied. Additional modulations of hydrodynamic properties and media composition allow for control of complex vascular function within the desired microenvironment. This platform allows for the study of perivascular cell recruitment, blood-endothelium interactions, flow response, and tissue-microvascular interactions. Engineered microvessels offer the ability to isolate the influence from individual components of a vascular niche and precisely control its chemical, mechanical, and biological properties to study vascular biology in both health and disease.

This manuscript presents an injection molding method to engineer microvessels that recapitulate physiological properties of endothelium. The microfluidic-based process creates patent 3D vascular networks with tailorable conditions, such as flow, cellular composition, geometry, and biochemical gradients. The fabrication process and examples of potential applications are described.

In vitro platforms to study endothelial cells and vascular biology are largely limited to 2D endothelial cell culture, flow chambers with polymer or glass ...

Bioprinting of Cartilage and Skin Tissue Analogs Utilizing a Novel Passive Mixing Unit Technique for Bioink Precellularization

Bioprinting is a powerful technique for the rapid and reproducible fabrication of constructs for tissue engineering applications. In this study, both cartilage and skin analogs were fabricated after bioink pre-cellularization utilizing a novel passive mixing unit technique. This technique was developed with the aim to simplify the steps involved in the mixing of a cell suspension into a highly viscous bioink. The resolution of filaments deposited through bioprinting necessitates the assurance of uniformity in cell distribution prior to printing to avoid the deposition of regions without cells or retention of large cell clumps that can clog the needle. We demonstrate the ability to rapidly blend a cell suspension with a bioink prior to bioprinting of both cartilage and skin analogs. Both tissue analogs could be cultured for up to 4 weeks. Histological analysis demonstrated both cell viability and deposition of tissue specific extracellular matrix (ECM) markers such as glycosaminoglycans (GAGs) and collagen I respectively.

Cartilage and skin analogs were bioprinted using a nanocellulose-alginate based bioink. The bioinks were cellularized prior to printing via a single step passive mixing unit. The constructs were demonstrated to be uniformly cellularized, have high viability, and exhibit favorable markers of differentiation.

Bioprinting is a powerful technique for the rapid and reproducible fabrication of constructs for tissue engineering applications. In this study, both ...

In Situ Microscopy for Real-time Determination of Single-cell Morphology in Bioprocesses

In situ monitoring in microbial bioprocesses is mostly restricted to chemical and physical properties of the medium (e.g.,pH value and the dissolved oxygen concentration). Nevertheless, the morphology of cells can be a suitable indicator for optimal conditions, since it changes with dependence on the growth state, product accumulation and cell stress. Furthermore, the single-cell size distribution provides not only information about the cultivation conditions, but also about the population heterogeneity. To gain such information, a photo-optical in situ microscopy device1 was developed to enable the monitoring of the single-cell size distribution directly in the cell suspension in bioreactors. An automated image analysis is coupled to the microscopy based on a neural network model, which is trained with user-annotated images. Several parameters, which are gained from the captures of the microscope, are correlated to process relevant features of the cells, like their metabolic activity. Until now, the presented in situ microscopy probe series was applied to measure the pellet size in filamentous fungi suspensions. It was used to distinguish the single-cell size in microalgae cultivation and relate it to lipid accumulation. The shape of cellular particles was related to budding in yeast cultures. The microscopy analysis can be generally split into three steps: (i) image acquisition, (ii) particle identification, and (iii) data analysis, respectively. All steps have to be adapted to the organism, and therefore specific annotated information is required in order to achieve reliable results. The ability to monitor changes in cell morphology directly in line or on line (in a by-pass) enables real-time values for monitoring and control, in process development as well as in production scale. If the off line data correlates with the real-time data, the current tedious off line measurements with unknown influences on the cell size become needless.

In Situ Microscopy for Real-time Determination of Single-cell Morphology in Bioprocesses

A photo-optical in situ microscopy device was developed to monitor the size of single cells directly in the cell suspension. The real-time measurement is conducted by coupling the photo-optical sterilizable probe to an automated image analysis. Morphological changes appear with dependence on the growth state and cultivation conditions.

In situ monitoring in microbial bioprocesses is mostly restricted to chemical and physical properties of the medium (e.g.,pH value and the dissolved ...

Manufacturing of a Nafion-coated, Reduced Graphene Oxide/Polyaniline Chemiresistive Sensor to Monitor pH in Real-time During Microbial Fermentation

Here, we report the engineering of a solid-state micro pH sensor based on polyaniline-functionalized, electrochemically reduced graphene oxide (ERGO-PA). Electrochemically reduced graphene oxide acts as the conducting layer and polyaniline acts as a pH-sensitive layer. The pH-dependent conductivity of polyaniline occurs by doping of holes during protonation and by the dedoping of holes during deprotonation. We found that an ERGO-PA solid-state electrode was not functional as such in fermentation processes. The electrochemically active species that the bacteria produce during the fermentation process interfere with the electrode response. We successfully applied Nafion as a proton-conducting layer over ERGO-PA. The Nafion-coated electrodes (ERGO-PA-NA) show a good sensitivity of 1.71 &#937;/pH (pH 4 - 9) for chemiresistive sensor measurements. We tested the ERGO-PA-NA electrode in real-time in the fermentation of Lactococcus lactis. During the growth of L. lactis, the pH of the medium changed from pH 7.2 to pH 4.8 and the resistance of the ERGO-PA-NA solid-state electrode changed from 294.5 &#937; to 288.6 &#937; (5.9 &#937; per 2.4 pH unit). The pH response of the ERGO-PA-NA electrode compared with the response of a conventional glass-based pH electrode shows that reference-less solid-state microsensor arrays operate successfully in a microbiological fermentation.

Here, we report the protocol for the fabrication of a Nafion-coated, polyaniline-functionalized, electrochemically reduced graphene oxide chemiresistive micro pH sensor. This chemiresistor-based, solid-state micro pH sensor can detect pH changes in real-time during a Lactococcus lactis fermentation process.

Here, we report the engineering of a solid-state micro pH sensor based on polyaniline-functionalized, electrochemically reduced graphene oxide (ERGO-PA). ...