We thank Mr. P. Yeung for preparing the MCF-7 for us. This work was partially supported by grants from the Research Grant Council of the Hong Kong Special Administration Region, China (Project no. 17259316, 17207715, 17207714, 17205215, and HKU 720112E), the Innovation and Technology Support Programme (ITS/090/14), and the University Development Fund of HKU.

1. Sample Preparation
<ol>
	<li>Sample preparation (adherent cells; MCF-7 cells)
	<ol>
		<li>Take out the cell culture dish from the incubator and drain the culture medium.</li>
		<li>Rinse the cells on a dish with 1x phosphate-buffered saline (PBS) to remove excessive culture medium.</li>
		<li>Add 3 mL of a solution of 0.25% trypsin to the culture dish (diameter of 100 mm) and put it in a 37 &#176;C, 5% CO2 incubator for 4 min. 
		NOTE: The trypsin dissolves the adhesive protein of the cells so that they will detach from the culture dish.</li>
		<li>Check to see if all the cells have detached from the culture dish using a light microscope (10X objective). If not, gently shake the cell culture dish.</li>
		<li>Add 4 mL of the standard culture medium (formulated with 89% Dulbecco&#39;s Modified Eagle Medium (DMEM), 10% fetal bovine serum (FBS), and 1% penicillin-streptomycin (PS)) to stop the action of the trypsin.</li>
		<li>Transfer the whole mixture (cells in trypsin solution and culture medium) to a centrifuge tube and centrifuge for 5 min at 200 x g.</li>
		<li>Remove all the fluid and re-suspend the cells in 1 mL of 1x PBS (pH value: 7.4, pre-heated to 37 &#176;C).</li>
	</ol>
	</li>
	<li>Sample preparation (cultured micro-algae)
	<ol>
		<li>Transfer the cultured micro-algae and the culture medium (e.g., sea water, agar, or fresh water) to new glass culture tubes (~15 mL) in a volume ratio (micro-algae to culture medium) of 1:5 to establish a new sub-culture medium.</li>
		<li>Place the glass culture tubes in a dust-proof chamber under constant illumination by artificial lighting from fluorescent bulbs according to a light/dark (LD) cycle (usually LD 16:8) for 72 - 120 h before the experiment.</li>
		<li>Transfer the sub-cultured samples to a centrifuge tube and mix well.</li>
	</ol>
	</li>
</ol>
2. ATOM System Setup
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/55840/55840fig1.jpg" /> 
Figure 1: Schematic of an ATOM System. A broadband pulsed laser is employed to deliver ultrafast pulses to (a) a time-stretch module and (b) an in-line optical amplifier module. The time-stretch module generates a train of temporal waveforms, each of which is the replica of the wavelength spectrum of the laser source, (i.e., wavelength-to-time mapping). The amplifier module is used to for pulse-stretching (dispersive) loss compensation. The stretched pulse is then (c) spatially dispersed by a diffraction grating, forming a 1D spectral shower illumination in which individual wavelength components are relayed by a relay lens pair and focused by the objective lens onto different positions on the flowing cell inside the (d) microfluidic chip. This is the process of spectral-encoding. The spectrally encoded light will again pass the cell through another objective lens and a mirror, returning to the diffraction grating and recombining as a spatially undispersed pulsed beam. This image-encoded pulsed beam is then (e) split into two paths, such that both beams are partially blocked with (f) the knife edge, but from opposite directions, before being coupled into the fibers. These two beams represent the two (opposite) encoded phase-gradient contrasts of the final image. For the simultaneous detection of both signal contrasts, one of the signals undergoes (g) a time-delay line, such that the two signals are multiplexed (interleaved) in time. A high-speed photodetector and real-time oscilloscope are used for data acquisition. <a href="http://cloudfront.jove.com/files/ftp_upload/55840/55840fig1large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<ol>
	<li>Time stretch module
	<ol>
		<li>Employ a broadband femtosecond (fs) or picosecond (ps) pulsed laser source with a recommended center wavelength in the near infrared (NIR) range, 800-1,500 nm. 
		NOTE: The typical required pulse width can range from sub-100 fs to a few ps. Detailed requirements of the pulsed laser sources can be seen in References 4 and 5. Important metrics are highlighted in Table 1.
		<ol>
			<li>Ensure that the laser source has a high repetition rate, which should be in the megahertz regime (e.g., tens of MHz) to ensure ultrafast imaging in ATOM. Also, set the peak output laser power well below the damage power threshold of the fiber cavity, approximately 1 kW.</li>
			<li>Ensure good shot-to-shot temporal and spectral stability of the pulsed laser source. 
			NOTE: Typical tolerance in the spectral amplitude fluctuation should be kept within 1.2%19,20,21, as achieved by the fiber mode-locked laser in this setup. 
			NOTE: The optical bandwidth of the laser source is expected to be 10-100 nm, which is essential to guarantee sufficient imaging field-of-view (FOV) in single-cell imaging21.</li>
		</ol>
		</li>
		<li>Through a fiber collimator, couple the laser pulsed beam to a single-mode dispersive optical fiber, in which the pulses are stretched via group velocity dispersion (GVD) (Figure 1a). 
		NOTE: This is the process after which the spectrum of each pulse is mapped onto time as a wavelength-swept waveform (i.e., wavelength-to-time mapping). 
		NOTE: The total required GVD should be sufficient to ensure that the overall ATOM image resolution is not affected by the wavelength-to-time mapping process (See the Discussion). Typically, in the NIR range, the GVD should be well beyond 0.1 ns/nm. For instance, a single-mode fiber employed in this current setup provides a total GVD of 0.38 ns/nm around the wavelength of 1,060 nm (a total fiber length of 10 km).</li>
	</ol>
	</li>
	<li>Spectral-encoding module
	<ol>
		<li>Construct an optical microscope system to perform the spectrally encoded imaging of the cells flowing along the microfluidic channel, as illustrated in Figure 1. 
		NOTE: The key components of this optical microscope include: (1) a diffraction grating, a telescopic relay-lens module (RL1 and RL2 in Figure 1), and two objective lenses (Obj1 and Obj2 in Figure 1).
		<ol>
			<li>First, illuminate the time-stretched and collimated beam onto a diffraction grating (transmission-type grating is employed in this setup) to generate a spectral shower (Figure 1c). 
			NOTE: The power of the diffracted beam (i.e., diffraction efficiency) can be maximized by adjusting the grating orientation closed to the Littrow configuration.</li>
			<li>Configure the two relay lenses (RL1 and RL2) in a 4-f imaging system (i.e., place the diffraction grating on the focal plane of RL1 and separate RL1 and RL2 by a distance equal to the sum of their focal lengths. The spectral shower will then be imaged onto the back focal plane of the objective lens Obj1).</li>
			<li>Carefully align the spectral shower to fill the back aperture of the Obj1, such that the spectral shower can be projected and focused onto the image plane of the microscope. 
			NOTE: Here, the NA of the objective lens (Obj1 in Figure 1) is 0.75.</li>
			<li>Place another objective lens (Obj2 in Figure 1) with a similar NA and a plane mirror at the back aperture of this objective lens (Obj2), such that the spectral shower beam can be aligned to double-pass the image plane and return to the diffraction grating.</li>
			<li>Adjust the pair of objective lenses (Obj1 and Obj2) such that their focal planes overlap with each other. Check to see if the spectral shower double-passes the image plane at the same location and returns to the grating following the same path. If not, perform further alignment and tuning of the optical system. 
			NOTE: The returned light should pass through an additional beam-splitter, such that the light can be transmitted to an asymmetric detection module.</li>
			<li>Adjust the optical amplifier gain at a suitable level, such that the resultant signal can be detected by the photodetector with a good SNR, which is typically at &#62;10 dB.</li>
			<li>Place and adjust the position of the microfluidic chip on the sample platform and make sure that the spectral shower, and thus the imaging area, is placed across the microfluidic channel (Figure 1d). 
			NOTE: The spectral shower is illuminated orthogonally to the flow direction of fluidics inside the microfluidic chip, such that the flowing motion automatically performs two-dimensional (2D) scans.</li>
		</ol>
		</li>
	</ol>
	</li>
	<li>Asymmetric detection module
	<ol>
		<li>Place an additional beam-splitter to separate the imaged-encoded beam into two (Figure 1e). 
		NOTE: Each beam replica is partially blocked by a knife edge.</li>
		<li>Measure and record the optical power of the beam before the beam block. Then, manually position the knife edges (mounted on a linear translation stage) such that they roughly block half of the beam (by visual inspection). Afterward, use the optical power meter to monitor the beam power while fine-tuning the position of the knife edges by translating them across the beam. 
		NOTE: It is suggested that the optimal position is where the power is decreased by ~50% of the original value (i.e., the unblocked case). This is the condition that provides the best combination of image signal strength and image contrast enhancement.</li>
		<li>Repeat step 2.3.2 for another beam replica. Note that the orientation of the partial beam block for one beam should be opposite with respect to the other beam (Figure 1f).</li>
		<li>Couple the two partially-blocked beams into two separate, single-mode fiber arms through two-fiber collimators. 
		NOTE: One of the arms has an extra length of fiber, serving as a fiber-based delay-line, to introduce a time-delay with respect to the other replica (without the delay-line) (Figure 1g). Both are directed to a single fiber by a fiber coupler before photodetection. The time-delay should be long enough to temporally separate the two replicas and short enough to avoid temporal overlap with the next waveform (i.e., the two replicas are always time-interleaved and time-multiplexed in a single fiber prior to detection (Figure 2a)).</li>
		<li>Capture and digitize the detected optical signals with the real-time oscilloscope. Note that the bandwidth and thus the sampling rate of the oscilloscope should be sufficiently high to ensure that they do not influence the final image resolution (See the Discussion). 
		NOTE: Here, with the GVD of 0.38 ns/nm, a backend acquisition bandwidth and sampling rate of &#62;20 GHz and &#62;40 GSa/s, respectively, are required.</li>
	</ol>
	</li>
</ol>
3. Experimental Procedures
<ol>
	<li>Specimen loading
	<ol>
		<li>Perform cell counting under a conventional phase contrast microscope in a standard hemocytometer.</li>
		<li>Adjust the cell density by diluting with 1x PBS (with spring water for micro-algae) and mix well with a pipette. 
		NOTE: The suggested concentration is from 105 to 106 cells/mL.</li>
		<li>Mount the microfluidic chip onto the sample platform of the optical imaging system. 
		NOTE: The microfluidic chip is primarily made of polydimethylsiloxane (PDMS) and is fabricated using the standard replica molding method. The microfluidic channel is designed with an asymmetric curved channel to generate the inertial flow focusing effect, such that the cells can flow in single file in the imaging section (with a dimension of 80 &#181;m x 80 &#181;m (height x width)) at high speed.</li>
		<li>Transfer the density-adjusted cell solution to a 10 mL syringe.</li>
		<li>Connect the syringe to the inlet of the microfluidic chip and a centrifugal tube to the outlet of the microfluidic chip for disposal collection.</li>
		<li>Mount the syringe onto a syringe pump and set a suitable flow rate to give desirable throughput and to avoid imposing excessive shear force between the cells and the channel. 
		NOTE: The linear speed of the samples should be within 0.5 and 10 m/s. Note that before the actual image recording, it is often necessary to further fine-tune the system, in terms of maximizing the image signal strength and optimizing the image focusing by repeating steps 2.2.1.4-2.2.1.6.</li>
	</ol>
	</li>
</ol>
4. Data Acquisition
<ol>
	<li>Set a suitable number of data points to be saved for each experiment. The number of data points to be saved depends on the size and flow rate of the samples. 
	NOTE: Typically, it is set to 8-16 million sample points under a sampling rate of 80 GSa/s.</li>
	<li>Acquire and save the data in a batch mode using the oscilloscope.</li>
</ol>
5. Backend Processing
<img alt="Figure 2" class="xfigimg" src="/files/ftp_upload/55840/55840fig2.jpg" /> 
Figure 2: Reconstruction of ATOM Images from the Line-scan Time Trace. To reconstruct the ATOM images with the absorption contrast and differential (enhanced) phase-gradient contrast, two sets of time-stretched pulses (see the purple and green pulses) are extracted from (a) the time-multiplexed temporal waveform trace and are then digitally segmented and stacked to form (b) two 2D images showing the two opposite phase-gradient contrasts. Note that a shearing operation is needed to form (c) the distortion-free images by compensating for the sub-index shift due to the round-off error in the laser repetition rate estimation. By subtracting the (d) raw line-scan from the spectral intensity envelope of the laser source, the background of the images can be removed. (g) An absorption contrast image can be obtained by a pixel-by-pixel intensity summation of images (e) and (f), whereas (h) a differential phase-gradient contrast image can be obtained from the subtraction of images (e) and (f). <a href="http://cloudfront.jove.com/files/ftp_upload/55840/55840fig2large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<ol>
	<li>Transfer the data from the oscilloscope to the computers for offline image reconstruction. 
	NOTE: Here, the data are stored in a portable hard disk and transferred manually between the oscilloscope and the processing computers. The capacity of the hard disk should be more than 500 GB for each experiment.
	<ol>
		<li>Use the key image reconstruction routine to digitally stack the line-scans to form a 2D image (Figure 2). 
		NOTE: The custom program (in MATLAB) then produces two asymmetric detection images by separating the two time-multiplexed data sets (purple and green waveforms in Figure 2).
		<ol>
			<li>Obtain a differential phase-gradient contrast image by subtracting the intensities of the two asymmetric detection images; an absorption contrast image can be obtained by adding the two asymmetric detection images. See selected images of MCF-7 and micro-algae in Figure 3. Note that the background profiles of individual images should first be eliminated, and their intensities should be normalized, prior to the image summation and subtraction operations.</li>
		</ol>
		</li>
		<li>Generate a library of parameters derived from the images, such as cell volume, circularity, and absorption density, etc. for further analysis.</li>
	</ol>
	</li>
	<li>Input the library of data into the data visualization platform (Figure 4).
	<ol>
		<li>Load the library of parameters and the corresponding reconstructed images to the visualization interface platform.</li>
		<li>Set the axes to be the parameters of interest. 
		NOTE: The parameters are problem-specific and are defined by the user. They are derived from the ATOM images by the MATLAB program. Here, the optical absorption density of the cell, cell area, cell volume, and cell circularity are available for selection.</li>
		<li>Select the dataset to be displayed, such that every cell image can be visualized as a different data point on the scatter plot.</li>
		<li>Move the mouse cursor to each point, such that the corresponding image and other parameters are shown in a floating sub-window. 
		NOTE: The axes can be changed between the linear and logarithmic scales in an interactive manner.</li>
		<li>Perform further analysis of any subset of the dataset by manually gating on the scatter plot. 
		NOTE: The histogram in every parameter of the gated subset can be plotted against those of the entire library. The separate histograms are displayed in another floating sub-window.</li>
	</ol>
	</li>
</ol>

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G., 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=Molecular+analysis+of+circulating+tumour+cells-biology+and+biomarkers.">Molecular analysis of circulating tumour cells-biology and biomarkers.</a> Nat Rev Clin Oncol. 11 (3), 129-144 (2014).</li><li>Wu, 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=Ultrafast+Laser-Scanning+Time-Stretch+Imaging+at+Visible+Wavelengths.">Ultrafast Laser-Scanning Time-Stretch Imaging at Visible Wavelengths.</a> Light Sci Appl. , (2016).</li></ol>

The authors have nothing to disclose.

There are several technical details that require special attention during the ATOM system setup. First, it is essential to note that asymmetric/oblique spectrally-encoded illumination could introduce residual phase-gradient components (i.e., the shadowing effect) in the absorption contrast and influence the enhancement of phase-gradient contrast in ATOM. Therefore, this effect of oblique illumination should be minimized. Second, it should be emphasized that the time-multiplexing or time-interleaving schemeinvolv...

Optical imaging presents a powerful tool and cell-based assay to (almost) non-invasively visualize the detailed spatial distribution of many cellular/subcellular components, thus uncovering a multitude of morphological, biophysical, and biomolecular signatures of cells. However, this ability to extract high-content information from single cells has generally been compromised when an enormous and heterogeneous population of cells had to be investigated. This marks a common trade-off in cell-based assays between measurement throughput and content. A notable example is that adding imaging capability to flow cytometry has resulted in a down-scaling of throughput by at least 1-2 orders of magnitude compared to that of the classical non-imaging flow cytometers. Although it could offer complex morphological single-cell analysis that is not possible with standard flow cytometers1, imaging flow cytometry generally lacks sufficient throughput to identify cellular heterogeneity with high statistical confidence. This is necessary for new discoveries in biology and for gaining an understanding of the pathogenesis of diseases. The key technical challenge lies in the inherent speed limit imposed by the common optical imaging strategies: laser-beam scanning, (e.g., by galvanometric mirrors), and/or image sensors (e.g., charge-coupled device (CCD) and complementary metal-oxide semiconductor (CMOS)). The laser scanning speed is intrinsically restricted by the mechanical inertia of the scanning mirrors, whereas the frame rate of CCD or CMOS is limited by the fundamental trade-off between imaging speed and sensitivity (i.e., increasing the frame rate leads to reduced signal detection sensitivity, and vice versa).
Based on an all-optical, ultrafast image-encoding mechanism, optical time-stretch imaging has been demonstrated as an attractive platform for high-throughput imaging flow cytometers, without need of the conventional image sensors or mechanical laser scanning2,3. Detailed descriptions of the working principle of time-stretch imaging can be found in references4,5,6,7. In brief, it consists of two interchangeable mapping steps: (i) spectral encoding (wavelength-space mapping), in which the spatial coordinates of the imaged specimen are mapped to different wavelengths across the spectrum of the light-pulsed beam8,9, and (ii) a dispersive Fourier transformation (wavelength-time mapping)9, in which the wavelength components of individual laser pulses are transformed (stretched) via group velocity dispersion (GVD) into temporal (wavelength-swept) waveforms (Figure 1). An important feature of time-stretch imaging is optical amplification, which plays a critical role in combatting the loss of sensitivity due to ultrafast photodetection and GVD loss, thus enhancing the image signal-to-noise ratio (SNR) without being contaminated by the photodetector noise9. Since each laser pulse encodes a line-scan of the imaged specimen, which is orthogonal to the unidirectional flow of the cells, an effective line-scan rate is determined by the laser repetition rate, which is typically beyond 10 MHz. This ultrafast operation enables blur-free, single-cell image capture at a throughput of 10,000-100,000 cells/s (i.e., 10-100 times higher than conventional imaging flow cytometry). As a result, time-stretch imaging could find unique applications in high-throughput, single-cell, image-based screening, especially when there is a need for identifying unknown heterogeneity or rare/aberrant cells within a sizable population (thousands to millions of cells), such as rare cancer cell screening10 or micro-algae classification11.
Time-stretch imaging predominantly relies on bright-field (BF) image capture, from which the image contrast is generated through light scattering and absorption from the cells2,3,9,10,11. Such label-free, single-cell imaging capabilities could bypass the detrimental effects associated with the fluorescent labels, such as cytotoxicity and photobleaching, and yet provide valuable information for single-cell analysis based on the cellular and sub-cellular texture and morphology. These label-free parameters are proven to be effective for the deep image classification of cells, especially when an enormous cell population is available11,12. However, in many occasions, BF imaging fails to provide sufficient contrast to reveal the detailed morphology of the label-free transparent cells. Different label-free, phase-contrast, time-stretch imaging modalities have been developed for enhancing the imaging contrast at ultrafast frame rates13,14,15. Among these techniques, asymmetric-detection time-stretch optical microscopy (ATOM) was developed to reveal the phase-gradient (differential-interference-contrast-(DIC)-like) contrast based on a concept similar to Schlieren photography, enabling the label-free, high-contrast imaging of single cells at an ultrahigh microfluidic speed (up to 10 m/s)16. This effect can be readily generated through oblique detection or illumination by partially blocking the image-encoded beam path or tilting the beam before photodetection. Another advantage of ATOM is its ability to simultaneously acquire two phase-gradient contrasts along opposite orientations. Intensity subtraction and summation of two opposite-contrast images yield the differential phase-gradient contrast and the absorption contrast, respectively, from the same line-scan. This work presents a detailed protocol describing the implementation of ATOM, including the establishment of the optical setup, the sample preparation, and the data acquisition and visualization. Specifically, this work demonstrates the ATOM operation with single-cell imaging of human blood cells, cancer cells, and phytoplankton (microalgae). This highlights the applicability of ATOM to imaging flow cytometry, not only in the biomedical arena, but also in marine and biofuel research17,18.

<table><tbody><tr><td>Nikon Plan Fluorite Physiology Objectives 40X</td><td>Nikon</td><td>MRF07420</td><td>Objective lens (Obj2)</td></tr><tr><td>Olympus Plan Fluorite Objective, 0.75 NA, 0.51 mm WD, 40X</td><td>Olympus</td><td>RMS40X-PF</td><td>Objective lens (Obj1)</td></tr><tr><td>N-BK7 Plano-Convex Lenses</td><td>Thorlabs</td><td>LA1145-C</td><td>For relaying spectral shower</td></tr><tr><td>FC/APC Fiber Collimation Package</td><td>Thorlabs</td><td>F220APC-1064</td><td>For outputing and collecting laser pulses</td></tr><tr><td>Pellicle beamsplitter</td><td>Thorlabs</td><td>BP145B3</td><td>For making beam replica</td></tr><tr><td>Protected silver mirror</td><td>Thorlabs</td><td>PF10-03-P01</td><td>For reflecting light</td></tr><tr><td>800-1650nm 12GHz single mode DC-coupled NIR Photoreceiver</td><td>Newport</td><td>1544-B</td><td>For converting light into electrical signal</td></tr><tr><td>Infiniium High-Performance Oscilloscope</td><td>Agilent</td><td>DSOX91604A</td><td>To save the light-converted electrical signals</td></tr><tr><td>HI1060 optical fiber</td><td>Corning</td><td>HI1060</td><td>Optical fiber for time-stretch</td></tr><tr><td>YTTERBIUM DOPED FIBER AMPLIFIER</td><td>Keopsys</td><td>KPS-STD-BT-YFA-37-BO-SM-111-FA-FA</td><td>Optical in-line amplifier</td></tr><tr><td>Holographic grating</td><td>Wasatch Photonics</td><td>020305-6</td><td>Grating</td></tr><tr><td>Infuse/Withdraw Syringe Pumps</td><td>Harvard Apparatus</td><td>PHD 2000</td><td>Syringe pump for sample loading in micro-fluidic channels</td></tr></tbody></table>

microfluidic imaging flow cytometry by asymmetric-detection time-stretch optical microscopy (atom)

Scaling the number of measurable parameters, which allows for multidimensional data analysis and thus higher-confidence statistical results, has been the main trend in the advanced development of flow cytometry. Notably, adding high-resolution imaging capabilities allows for the complex morphological analysis of cellular/sub-cellular structures. This is not possible with standard flow cytometers. However, it is valuable for advancing our knowledge of cellular functions and can benefit life science research, clinical diagnostics, and environmental monitoring. Incorporating imaging capabilities into flow cytometry compromises the assay throughput, primarily due to the limitations on speed and sensitivity in the camera technologies. To overcome this speed or throughput challenge facing imaging flow cytometry while preserving the image quality, asymmetric-detection time-stretch optical microscopy (ATOM) has been demonstrated to enable high-contrast, single-cell imaging with sub-cellular resolution, at an imaging throughput as high as 100,000 cells/s. Based on the imaging concept of conventional time-stretch imaging, which relies on all-optical image encoding and retrieval through the use of ultrafast broadband laser pulses, ATOM further advances imaging performance by enhancing the image contrast of unlabeled/unstained cells. This is achieved by accessing the phase-gradient information of the cells, which is spectrally encoded into single-shot broadband pulses. Hence, ATOM is particularly advantageous in high-throughput measurements of single-cell morphology and texture &#8211; information indicative of cell types, states, and even functions. Ultimately, this could become a powerful imaging flow cytometry platform for the biophysical phenotyping of cells, complementing the current state-of-the-art biochemical-marker-based cellular assay. This work describes a protocol to establish the key modules of an ATOM system (from optical frontend to data processing and visualization backend), as well as the workflow of imaging flow cytometry based on ATOM, using human cells and micro-algae as the examples.

This work illustrates two single-cell imaging demonstrations by ATOM: one with mammalian cells (human peripheral blood mononuclear cells (PBMC) and breast cancer cells (MCF-7)) and another with phytoplanktons (Scenedesmus and Chlamydomonas). The first experiment was motivated by the growing interest in liquid biopsy for the detection, enumeration, and characterization of circulating tumor cells (CTCs) in the blood23. The ability to...

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Microfluidic Imaging Flow Cytometry by Asymmetric-detection Time-stretch Optical Microscopy ATOM

This protocol describes the implementation of an asymmetric-detection time-stretch optical microscopy system for single-cell imaging in ultrafast microfluidic flow and its applications in imaging flow cytometry.

Microfluidic Imaging Flow Cytometry by Asymmetric-detection Time-stretch Optical Microscopy (ATOM)

Scaling the number of measurable parameters, which allows for multidimensional data analysis and thus higher-confidence statistical results, has been the ...

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10.2K Views.  The University of Hong Kong.  Dit protocol beschrijft de implementatie van een asymmetrische detectie tijdstens optisch microscopiesysteem voor single-cell imaging in ultrafast microfluidische stroom en zijn toepassingen in beeldstroomcytometrie. 

Video: Microfluidic Imaging Flow Cytometry by Asymmetric-detection Time-stretch Optical Microscopy ATOM

Fluorescence detection methods for microfluidic droplet platforms

The development of microfluidic platforms for performing chemistry and biology has in large part been driven by a range of potential benefits that accompany system miniaturisation. Advantages include the ability to efficiently process nano- to femoto- liter volumes of sample, facile integration of functional components, an intrinsic predisposition towards large-scale multiplexing, enhanced analytical throughput, improved control and reduced instrumental footprints.1
In recent years much interest has focussed on the development of droplet-based (or segmented flow) microfluidic systems and their potential as platforms in high-throughput experimentation.2-4 Here water-in-oil emulsions are made to spontaneously form in microfluidic channels as a result of capillary instabilities between the two immiscible phases. Importantly, microdroplets of precisely defined volumes and compositions can be generated at frequencies of several kHz. Furthermore, by encapsulating reagents of interest within isolated compartments separated by a continuous immiscible phase, both sample cross-talk and dispersion (diffusion- and Taylor-based) can be eliminated, which leads to minimal cross-contamination and the ability to time analytical processes with great accuracy. Additionally, since there is no contact between the contents of the droplets and the channel walls (which are wetted by the continuous phase) absorption and loss of reagents on the channel walls is prevented.
Once droplets of this kind have been generated and processed, it is necessary to extract the required analytical information. In this respect the detection method of choice should be rapid, provide high-sensitivity and low limits of detection, be applicable to a range of molecular species, be non-destructive and be able to be integrated with microfluidic devices in a facile manner. To address this need we have developed a suite of experimental tools and protocols that enable the extraction of large amounts of photophysical information from small-volume environments, and are applicable to the analysis of a wide range of physical, chemical and biological parameters. Herein two examples of these methods are presented and applied to the detection of single cells and the mapping of mixing processes inside picoliter-volume droplets. We report the entire experimental process including microfluidic chip fabrication, the optical setup and the process of droplet generation and detection.

Droplet-based microfluidic platforms are promising candidates for high throughput experimentation since they are able to generate picoliter, self-compartmentalized vessels inexpensively at kHz rates. Through integration with fast, sensitive and high resolution fluorescence spectroscopic methods, the large amounts of information generated within these systems can be efficiently extracted, harnessed and utilized.

The development of microfluidic platforms for performing chemistry and biology has in large part been driven by a range of potential benefits that ...

Bioengineering

A Microfluidic Device for Studying Multiple Distinct Strains

The study of cell responses to environmental changes poses many experimental challenges: cells need to be imaged under changing conditions, often in a comparative manner. Multiwell plates are routinely used to compare many different strains or cell lines, but allow limited control over the environment dynamics. Microfluidic devices, on the other hand, allow exquisite dynamic control over the surrounding conditions, but it is challenging to image and distinguish more than a few strains in them. Here we describe a method to easily and rapidly manufacture a microfluidic device capable of applying dynamically changing conditions to multiple distinct yeast strains in one channel. The device is designed and manufactured by simple means without the need for soft lithography. It is composed of a Y-shaped flow channel attached to a second layer harboring microwells. The strains are placed in separate microwells, and imaged under the exact same dynamic conditions. We demonstrate the use of the device for measuring protein localization responses to pulses of nutrient changes in different yeast strains.

We present a simple method to produce microfluidic devices capable of applying similar dynamic conditions to multiple distinct strains, without the need for a clean room or soft lithography.

The study of cell responses to environmental changes poses many experimental challenges: cells need to be imaged under changing conditions, often in a ...

Wide-field Fluorescent Microscopy and Fluorescent Imaging Flow Cytometry on a Cell-phone

Fluorescent microscopy and flow cytometry are widely used tools in biomedical research and clinical diagnosis. However these devices are in general relatively bulky and costly, making them less effective in the resource limited settings. To potentially address these limitations, we have recently demonstrated the integration of wide-field fluorescent microscopy and imaging flow cytometry tools on cell-phones using compact, light-weight, and cost-effective opto-fluidic attachments. In our flow cytometry design, fluorescently labeled cells are flushed through a microfluidic channel that is positioned above the existing cell-phone camera unit. Battery powered light-emitting diodes (LEDs) are butt-coupled to the side of this microfluidic chip, which effectively acts as a multi-mode slab waveguide, where the excitation light is guided to uniformly excite the fluorescent targets. The cell-phone camera records a time lapse movie of the fluorescent cells flowing through the microfluidic channel, where the digital frames of this movie are processed to count the number of the labeled cells within the target solution of interest. Using a similar opto-fluidic design, we can also image these fluorescently labeled cells in static mode by e.g. sandwiching the fluorescent particles between two glass slides and capturing their fluorescent images using the cell-phone camera, which can achieve a spatial resolution of e.g. ~ 10 &mu;m over a very large field-of-view of ~ 81 mm2. This cell-phone based fluorescent imaging flow cytometry and microscopy platform might be useful especially in resource limited settings, for e.g. counting of CD4+ T cells toward monitoring of HIV+ patients or for detection of water-borne parasites in drinking water.

We review our recent results on the integration of fluorescent microscopy and imaging flow cytometry tools on a cell-phone using compact and cost-effective opto-fluidic attachments. These cell-phone based micro-analysis devices might be useful for cytometric analysis, such as performing various cell counting tasks as well as for high-throughput screening of e.g., water samples in resource limited settings.

Fluorescent microscopy and flow cytometry are widely used tools in biomedical research and clinical diagnosis. However these devices are in general ...

Combining Fluidic Devices with Microscopy and Flow Cytometry to Study Microbial Transport in Porous Media Across Spatial Scales

Understanding the transport, dispersion and deposition of microorganisms in porous media is a complex scientific task comprising topics as diverse as hydrodynamics, ecology and environmental engineering. Modeling bacterial transport in porous environments at different spatial scales is critical to better predict the consequences of bacterial transport, yet current models often fail to up-scale from laboratory to field conditions. Here, we introduce experimental tools to study bacterial transport in porous media at two spatial scales. The aim of these tools is to obtain macroscopic observables (such as breakthrough curves or deposition profiles) of bacteria injected into transparent porous matrices. At the small scale (10-1000 &#181;m), microfluidic devices are combined with optical video-microscopy and image processing to obtain breakthrough curves and, at the same time, to track individual bacterial cells at the pore scale. At larger scale, flow cytometry is combined with a self-made robotic dispenser to obtain breakthrough curves. We illustrate the utility of these tools to better understand how bacteria are transported in complex porous media such as the hyporheic zone of streams. As these tools provide simultaneous measurements across scales, they pave the way for mechanism-based models, critically important for upscaling. Application of these tools may not only contribute to the development of novel bioremediation applications but also shed new light on the ecological strategies of microorganisms colonizing porous substrates.

Breakthrough curves (BTCs) are efficient tools to study the transport of bacteria in porous media. Here we introduce tools based on fluidic devices in combination with microscopy and flow cytometric counting to obtain BTCs.

Understanding the transport, dispersion and deposition of microorganisms in porous media is a complex scientific task comprising topics as diverse as ...

Environment

Multicolor Fluorescence Detection for Droplet Microfluidics Using Optical Fibers

Fluorescence assays are the most common readouts used in droplet microfluidics due to their bright signals and fast time response. Applications such as multiplex assays, enzyme evolution, and molecular biology enhanced cell sorting require the detection of two or more colors of fluorescence. Standard multicolor detection systems that couple free space lasers to epifluorescence microscopes are bulky, expensive, and difficult to maintain. In this paper, we describe a scheme to perform multicolor detection by exciting discrete regions of a microfluidic channel with lasers coupled to optical fibers. Emitted light is collected by an optical fiber coupled to a single photodetector. Because the excitation occurs at different spatial locations, the identity of emitted light can be encoded as a temporal shift, eliminating the need for more complicated light filtering schemes. The system has been used to detect droplet populations containing four unique combinations of dyes and to detect sub-nanomolar concentrations of fluorescein.

Multicolor fluorescence detection in droplet microfluidics typically involves bulky and complex epifluorescence microscope-based detection systems. Here we describe a compact and modular multicolor detection scheme that utilizes an array of optical fibers to temporally encode multicolor data collected by a single photodetector.

Fluorescence assays are the most common readouts used in droplet microfluidics due to their bright signals and fast time response. Applications such as ...

Cortical Actin Flow in T Cells Quantified by Spatio-temporal Image Correlation Spectroscopy of Structured Illumination Microscopy Data

Filamentous-actin plays a crucial role in a majority of cell processes including motility and, in immune cells, the formation of a key cell-cell interaction known as the immunological synapse. F-actin is also speculated to play a role in regulating molecular distributions at the membrane of cells including sub-membranous vesicle dynamics and protein clustering. While standard light microscope techniques allow generalized and diffraction-limited observations to be made, many cellular and molecular events including clustering and molecular flow occur in populations at length-scales far below the resolving power of standard light microscopy. By combining total internal reflection fluorescence with the super resolution imaging method structured illumination microscopy, the two-dimensional molecular flow of F-actin at the immune synapse of T cells was recorded. Spatio-temporal image correlation spectroscopy (STICS) was then applied, which generates quantifiable results in the form of velocity histograms and vector maps representing flow directionality and magnitude. This protocol describes the combination of super-resolution imaging and STICS techniques to generate flow vectors at sub-diffraction levels of detail. This technique was used to confirm an actin flow that is symmetrically retrograde and centripetal throughout the periphery of T cells upon synapse formation.

To investigate flow velocities and directionality of filamentous-actin at the T cell immunological synapse, live-cell super-resolution imaging is combined with total internal reflection fluorescence and quantified with spatio-temporal image correlation spectroscopy.

Filamentous-actin plays a crucial role in a majority of cell processes including motility and, in immune cells, the formation of a key cell-cell ...

Immunology and Infection

Computer Numerical Control Micromilling of a Microfluidic Acrylic Device with a Staggered Restriction for Magnetic Nanoparticle-Based Immunoassays

Microfluidic systems have greatly improved immunoassay techniques. However, many microfabrication techniques require specialized, expensive, or complicated equipment, making fabrication costly and incompatible with mass production, which is one of the most important preconditions for point-of-care tests (POCT) to be adopted in low-resource settings. This work describes the fabrication process of an acrylic (polymethylmethacrylate, PMMA) device for nanoparticle-conjugated enzymatic immunoassay testing using the computer numerical control (CNC) micromilling technique. The functioning of the microfluidic device is shown by performing an immunoassay to detect a commercial antibody using lysozyme as a model antigen conjugated to 100 nm magnetic nanoparticles. This device integrates a physical staggered restriction of only 5 &#181;m in height, used to capture magnetic microparticles that make up a magnetic trap by placing an external magnet. In this way, the magnetic force on the immunosupport of conjugated nanoparticles is enough to capture them and resist flow drag. This microfluidic device is particularly suitable for low-cost mass production without the loss of precision for immunoassay performance.

Microfluidics is a powerful tool for the development of diagnostic tests. However, expensive equipment and materials, as well as laborious fabrication and handling techniques, are often required. Here, we detail the fabrication protocol of an acrylic microfluidic device for magnetic micro- and nanoparticle-based immunoassays in a low-cost and simple-to-use setting.

Microfluidic systems have greatly improved immunoassay techniques. However, many microfabrication techniques require specialized, expensive, or ...

Use of Dual Optical Tweezers and Microfluidics for Single-Molecule Studies

Visual biochemistry is a powerful technique for observing the stochastic properties of single enzymes or enzyme complexes that are obscured in the averaging that takes place in bulk-phase studies. To achieve visualization, dual optical tweezers, where one trap is fixed and the other is mobile, are focused into one channel of a multi-stream microfluidic chamber positioned on the stage of an inverted fluorescence microscope. The optical tweezers trap single molecules of fluorescently labeled DNA and fluid flow through the chamber and past the trapped beads, stretches the DNA to B-form (under minimal force, i.e., 0 pN) with the nucleic acid being observed as a white string against a black background. DNA molecules are moved from one stream to the next, by translating the stage perpendicular to the flow to enable the initiation of reactions in a controlled manner. To achieve success, microfluidic devices with optically clear channels are mated to glass syringes held in place in a syringe pump. Optimal results use connectors permanently bonded to the flow cell, tubing that is mechanically rigid and chemically resistant, and which is connected to switching valves that eliminate bubbles that prohibit laminar flow.

Visual, single-molecule biochemistry studied through microfluidic chambers is greatly facilitated using glass barrel, gas-tight syringes, stable connections of tubing to flow cells, and elimination of bubbles by placing switching valves between the syringes and tubing. The protocol describes dual optical traps that enable visualization of DNA transactions and intermolecular interactions.

Visual biochemistry is a powerful technique for observing the stochastic properties of single enzymes or enzyme complexes that are obscured in the ...

Biochemistry

Spatial Temporal Analysis of Fieldwise Flow in Microvasculature

Changes in blood flow velocity and distribution are vital in maintaining tissue and organ perfusion in response to varying cellular needs. Further, appearance of defects in microcirculation can be a primary indicator in the development of multiple pathologies. Advances in optical imaging have made intravital microscopy (IVM) a practical approach, permitting imaging at the cellular and subcellular level in live animals at high-speed over time. Yet, despite the importance of maintaining adequate tissue perfusion, spatial and temporal variability in capillary flow is seldom documented. In the standard approach, a small number of capillary segments are chosen for imaging over a limited time. To comprehensively quantify capillary flow in an unbiased way we developed Spatial Temporal Analysis of Fieldwise Flow (STAFF), a macro for FIJI open-source&#160;image analysis software. Using high-speed image sequences of full fields of blood flow within capillaries, STAFF produces&#160;images that represent motion over time called kymographs for every time interval for every vascular segment. From the kymographs STAFF calculates velocities from the distance that red blood cells move over time, and outputs the velocity data as a sequence of color-coded spatial maps for visualization and tabular output for quantitative analyses. In normal mouse livers, STAFF analyses quantified profound differences in flow velocity between pericentral and periportal regions within lobules. Even more unexpected are the differences in flow velocity seen between sinusoids&#160;that are side by side and fluctuations seen within individual vascular segments over seconds. STAFF is a powerful new tool capable of providing novel insights by enabling measurement of the complex spatiotemporal dynamics of capillary flow.

To quantify microvascular flow from high speed capillary flow image sequences, we developed STAFF (Spatial Temporal Analysis of Fieldwise Flow) software. Across the full image field and over time, STAFF evaluates flow velocities and generates a sequence of color-coded spatial maps for visualization and tabular output for quantitative analyses.

Changes in blood flow velocity and distribution are vital in maintaining tissue and organ perfusion in response to varying cellular needs. Further, ...

Microfluidic Droplet Assay for Single-Cell Cytokine Secretion Analysis

Microfluidic Approach to Resolve Simultaneous and Sequential Cytokine Secretion of Individual Polyfunctional Cells

Infections, autoimmune diseases, desired and adverse immunological responses to treatment can lead to a complex and dynamic cytokine response in vivo. This response involves numerous immune cells secreting various cytokines to orchestrate the immune reaction. However, the secretion dynamics, amounts, and co-occurrence of the different cytokines by various cell subtypes remain poorly understood due to a lack of appropriate tools to study them. Here, we describe a protocol using a microfluidic droplet platform that allows the time-resolved quantitative measurement of secretion dynamics for several cytokines in parallel on the single-cell level. This is enabled by the encapsulation of individual cells into microfluidic droplets together with a multiplexed immunoassay for parallel quantification of cytokine concentrations, their immobilization for dynamic fluorescent imaging, and the analysis of the respective images to derive secreted quantities and dynamics. The protocol describes the preparation of functionalized magnetic nanoparticles, calibration experiments, cell preparation, and the encapsulation of the cells and nanoparticles into droplets for fluorescent imaging and subsequent image and data analysis using the example of lipopolysaccharide-stimulated human peripheral blood mononuclear cells. The presented platform identified distinct cytokine secretion behavior for single and co-secreting cells, characterizing the expected phenotypic heterogeneity in the measured cell sample. Furthermore, the modular nature of the assay allows its adaptation and application to study a variety of proteins, cytokines, and cell samples, potentially leading to a deeper understanding of the interplay between different immune cell types and the role of the different cytokines secreted dynamically to shape the tightly regulated immune response. These new insights could be particularly interesting in the studies of immune dysregulations or in identifying target populations in therapy and drug development.

Author Spotlight: Unveiling the Polyfunctionality and Heterogeneity in Immune Responses

The protocol describes an advanced microfluidic platform to quantitatively measure cytokine secretion dynamics of individual human peripheral blood mononuclear cells. The platform measures up to three cytokines in parallel (IL-6, TNF&#945;, and IL-1&#946;) for each individual cell stimulated with lipopolysaccharide as an example.

Infections, autoimmune diseases, desired and adverse immunological responses to treatment can lead to a complex and dynamic cytokine response in vivo. ...

Microfluidic Imaging Flow Cytometry by Asymmetric-detection Time-stretch Optical Microscopy (ATOM)

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