Name: a protocol for real-time 3d single particle tracking
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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 partic...

<ol>
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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 ...

The overall goal of this protocol is to implement a real-time, 3D, single particle tracking microscope. The main advantage of this technique is that a single diffusing nano scale object can be monitored continuously with photon limited temporal resolution. This technique can help answer key questions in the field of virology, such as following a single virion through the entire infection process.Prepare the apparatus on an optical table. This setup is ready for calibration. Key components include a 488 nanometer solid state laser, two electro-optic deflectors that are along the beam's path, a tunable acoustic gradient lens, and a sample stage with micro and nano positioners.This schematic of the setup provides additional details. Here is the laser beam path to the sample stage. The electro-optic deflectors and the tunable acoustic lens are along the beam's path.These devices dynamically drive the laser spot at the sample stage. Photons from the sample are counted by an avalanche photo diode. A camera monitors the position of the particle.The position of the sample is set using micro and nano controllers. A field programmable gate array controls the laser spot, real-time particle position calculation, stage feedback, and photon counting. Two samples have to be prepared.The first, requires 190 nanometer fluorescent beads diluted in phosphate buffered saline. Use a cover slip to prepare a fixed particle sample. Place 400 microliters of the bead solution onto the cover slip.Now, produce the free moving particles sample. It requires 110 nanometer fluorescent beads diluted in water. Create a free moving particle sample by placing 400 microliters of the solution onto a cover slip.Take the fixed particle sample to the microscope to mount. The sample is on the XY nano positioner. Turn on the laser, the photo detector, the controllers for the beam line elements, and for the positioners.Run the Piezo nano positioner in a closed loop. Next, remove the fluorescence emission filter from in front of the photo detector. Then, vary the sample's z-position with the micro positioner.As the position varies, use the photo detector to monitor the intensity of the laser's reflection. Maximize the intensity to identify the focal plane of the objective lens. With the sample in the focal plane, replace the fluorescence emission filter.Now, work with the computer control software. Use custom software to raster scan the sample. First, set a large scanning range, the difference between start and finish.Here, the range is 10 micrometers in Y and 10 micrometers in X.Also, set a large step size in each direction. Here, 200 nanometers. Set both Z fields to the previously identified position of the focal plane.Pushing scan will start the Raster scan. Start the scan. The software drives the electro-optic deflectors in a night's tour, collects counts from the photo detector, drives the nano positioner, and performs position calculations.The scan will find a particle that is identifiable in the software through a plata fluorescence. For each site in the scan, the software will also determine estimates of the particle position in X and Y, relative to the center of the electro-object deflector scan. After finding the particle, shrink the scanning range around it to two micrometers in X and Y.Also, decrease the step size for both to 100 nanometers.Add a scan range in the Z direction of two micrometers to bracket the fluorescent focus. Set the Z step size to 200 nanometers. Start the 3D raster scan to find the fluorescent focus.The data produced from the scan show the focal plane before the tunable acoustic gradient lens is powered on. Move on to work with the tunable acoustic lens setting within its control software. First, click connect, then, power on.Go to the pulse and gating control section, change the output trigger mode from RGB to multi-plane. Then, change it back to RGB to allow changing the output phase. Use the sliders to set the output phase between zero degrees, 90 degrees, and 270 degrees.Next, go to the frequency control section. There, select a resonance frequency of 68, 500 hertz. Move to the top of the screen and click advanced.Then, choose the settings tab. On the new screen, find the maximum frequency of the zero column. Adjust it to change the frequency search range.Click, save calibration, then, exit calibration. Return to frequency controls and change the resonance frequency. Immediately change it back to 68, 500 hertz to have the calibration take effect.In the amplitude control section, use the slider to slowly raise the amplitude to 35%After this, click lock resonance. When the frequency is locked, click unlock resonance. Return to the raster scan software.Input two micrometer scanning ranges centered on the particle in X and Y.Use a step size of 100 nanometers. Center the particle in a four micrometer range in Z, with a step size of 200 nanometers. In the scanning image that results the region of illumination representing the particle is about one micrometer wide.Based on this, adjust the XY scale parameter so the estimated positions in X and Y range from negative 0.5 to 0.5 micrometers. After a similar procedure with the Z scale set the nano positioner to the zero position. Turn off the power to the nano positioner before continuing.Replace the fixed particle sample with the freely moving particle sample. Then, make sure all of the equipment is on. Run the Piezo nano positioner in open loop.At the computer, set the tunable acoustic gradient lens software as before. Remove the fluorescence emission filter from the path to the photo detector. Find the focal plane by varying the sample Z position and maximizing the intensity of laser reflection, from the cover slip.After finding the focal plane, increase the focus position 15 micrometers into the solution. Replace the fluorescence emission filter. Open the custom tracking software.Set the position estimation parameters to the values found during optimization. Now, set the integral control constants, which dictate the response speed of the nano positioner. Start with the X constant.Enter a low value and increase it slowly. When oscillations begin in the particle position read-out, note the value of the control constant. Reduce the integral control constant to about 70%of its value at the onset of oscillation.Repeat the steps with the Y and Z control constants. Set he trigger to start tracking the track threshold to three kilohertz. Set track minimum, the trigger to end tracking, at 1.5 kilohertz.Start the experiment by clicking search and then clicking auto track. This movie shows the result of using the three dimensional, dynamic photon localization tracking microscope to track the diffusive motion of a 110 nanometer fluorescent nano particle in water. The particle's position, measured using the position read-out of the nano positioner is shown on the 3D axes.The inset is the read-out of the scientific sea moss camera. It demonstrates that the particle is held, locked in the focal volume, by the tracking system. The particle was tracked and its position recorded for more than two minutes.Once mastered, this technique can be done in under 50 minutes, if the system is properly aligned, and the calibration parameters set. After its development, this technique will help researchers in the field of drug delivery explore the pathways of internalization and transport of cellular cargo. After watching this video, you should have a good understanding of how to operate a zero-time, 3D single particle tracking microscope.

a-protocol-for-real-time-3d-single-particle-tracking

Research

JoVE Journal

Bioengineering

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. ...

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). ...

Uptake of New Lipid-coated Nanoparticles Containing Falcarindiol by Human Mesenchymal Stem Cells

Nanoparticles are the focus of an increased interest in drug delivery systems for cancer therapy. Lipid-coated nanoparticles are inspired in structure and size by low-density lipoproteins (LDLs) because cancer cells have an increased need for cholesterol to proliferate, and this has been exploited as a mechanism for delivering anticancer drugs to cancer cells. Moreover, depending on drug chemistry, encapsulating the drug can be advantageous to avoid degradation of the drug during circulation in vivo. Therefore, in this&#160;study, this design is used to fabricate lipid-coated nanoparticles of the anticancer drug falcarindiol, providing a potential new delivery system of falcarindiol in order to stabilize its chemical structure against degradation and improve its uptake by tumors. Falcarindiol nanoparticles, with a phospholipid and cholesterol monolayer encapsulating the purified drug core of the particle, were designed. The lipid monolayer coating consists of 1,2-distearoyl-sn-glycero-3-phosphocholine (DSPC), cholesterol (Chol), and 1,2-distearoyl-sn-glycero-3-phosphoethanolamine-N-[methoxy(polyethylene glycol)-2000] (DSPE PEG 2000) along with the fluorescent label DiI (molar ratios of 43:50:5:2). The nanoparticles are fabricated using the rapid injection method, which is a fast and simple technique to precipitate nanoparticles by good-solvent for anti-solvent exchange. It consists of a rapid injection of an ethanol solution containing the nanoparticle components into an aqueous phase. The size of the fluorescent nanoparticles is measured using dynamic light scattering (DLS) at 74.1 &#177; 6.7 nm. The uptake of the nanoparticles is tested in human mesenchymal stem cells (hMSCs) and imaged using fluorescence and confocal microscopy. The uptake of the nanoparticles is observed in hMSCs, suggesting the potential for such a stable drug delivery system for falcarindiol.

This article describes the encapsulation of falcarindiol in lipid-coated 74 nm nanoparticles. The cellular uptake of the nanoparticles&#160;by human stem cells into lipid droplets is monitored by fluorescent and confocal imaging. Nanoparticles are fabricated by the rapid injection method of solvent shifting, and their size is measured with the dynamic light scattering technique.

Nanoparticles are the focus of an increased interest in drug delivery systems for cancer therapy. Lipid-coated nanoparticles are inspired in structure and ...

Generation of Heterogeneous Drug Gradients Across Cancer Populations on a Microfluidic Evolution Accelerator for Real-Time Observation

Conventional cell culture remains the most frequently used preclinical model, despite its proven limited ability to predict clinical results in cancer. Microfluidic cancer-on-chip models have been proposed to bridge the gap between the oversimplified conventional 2D cultures and more complicated animal models, which have limited ability to produce reliable and reproducible quantitative results. Here, we present a microfluidic cancer-on-chip model that reproduces key components of a complex tumor microenvironment in a comprehensive manner, yet is simple enough to provide robust quantitative descriptions of cancer dynamics. This microfluidic cancer-on-chip model, the &#34;Evolution Accelerator,&#34; breaks down a large population of cancer cells into an interconnected array of tumor microenvironments while generating a heterogeneous chemotherapeutic stress landscape. The progression and the evolutionary dynamics of cancer in response to drug gradient can be monitored for weeks in real time, and numerous downstream experiments can be performed complementary to the time-lapse images taken through the course of the experiments.

We present a microfluidic cancer-on-chip model, the &#34;Evolution Accelerator&#34; technology, which provides a controllable platform for long-term real-time quantitative studies of cancer dynamics within well-defined environmental conditions at the single-cell level. This technology is expected to work as an in vitro model for fundamental research or pre-clinical drug development.

Conventional cell culture remains the most frequently used preclinical model, despite its proven limited ability to predict clinical results in cancer. ...