Name: excitation-scanning hyperspectral imaging microscopy to efficiently discriminate fluorescence signals
Uploaded: 2019-08-22T12:30:00
Description: Watch this Scientific Journal Video about Excitation-Scanning Hyperspectral Imaging Microscopy to Efficiently Discriminate Fluorescence Signals at JoVE.com

The authors would like to acknowledge support from NSF 1725937, NIH P01HL066299, NIH R01HL058506, NIH S10OD020149, NIH UL1 TR001417, NIH R01HL137030, AHA 18PRE34060163, and the Abraham Mitchell Cancer Research Fund.

1. Device set-up
<ol>
	<li>Light source: select a broad-band spectral light source with high power output and high collimation (a 300 W Xe arc lamp was used for these studies).</li>
	<li>Shutter (optional): add a shutter to the optical path to reduce photobleaching for time-lapse imaging.</li>
	<li>Tunable filter system: incorporate a mechanical tuning assembly and thin-film tunable filter (TFTF) set to enable the desired wavelength-adjustable excitation range (e.g., 360-485 nm).</li>
	<li>Microscope: use an inverted f...

The optimal use of an excitation-scanning hyperspectral imaging set-up begins with construction of the light path. In particular, choice of light source, filters (tunable and dichroic), filter switching method, and camera determine the available spectral range, possible scan speed, detector sensitivity, and spatial sampling. Mercury arc lamps offer many excitation wavelength peaks but do not provide a flat spectral output and will require significant signal reduction at the output peaks to correct the spectral image data...

Spectral imaging may be performed in a variety of ways and is referred to by several terms1,2,3,4. In general, spectral imaging refers to data acquired in at least two spatial dimensions and one spectral dimension. Multispectral and hyperspectral imaging are most often distinguished by the number of wavelength bands or whether the spectral bands are contiguous1. For this application, hyperspectral data is defined as spectral data acquired with contiguous wavelength bands achieved by spacing of center wavelengths no less than half the full width at half maximum (FWHM) of each bandpass filter used for excitation (i.e., 5 nm center wavelength spacing for bandpass filters with 14-20 nm bandwidths). The contiguous nature of the data bands allows for an oversampling of the dataset, ensuring that Nyquist criteria are satisfied when sampling the spectral domain.
Hyperspectral imaging was developed by NASA in the 1970s and 1980s in conjunction with the first Landsat satellite5,6. Collecting data from several contiguous spectral bands allowed the generation of a radiance spectrum of each pixel. Identifying and defining the radiance spectrum of individual components made it possible to not only detect surface materials by their characteristic spectra, but it also allowed for the removal of intervening signals, such as variations in the signal due to atmospheric conditions. The concept of detecting materials using their characteristic spectra was applied to biological systems in 1996 when Schr&#246;ck et al. used combinations of five different fluorophores and their known spectra to distinguish labeled chromosomes in a process termed spectral karyotyping7. This technique was elaborated upon in 2000 by Tsurui et al. for fluorescence imaging of tissue samples, using seven fluorescent dyes and singular value decomposition to achieve spectral separation of each pixel into linear combinations of spectra in the reference library8. Similar to their remote sensing counterparts, the contribution of each known fluorophore can be calculated from the hyperspectral image, given a priori information of the spectrum of each fluorophore.
Hyperspectral imaging has also been used in the areas of agriculture9, astronomy10, biomedicine11, chemical imaging12, environmental applications13, eye care14, food science15, forensic science16,17, medical science18, mineralogy19, and surveillance20. A key limitation of current fluorescence microscope hyperspectral imaging systems is that the standard hyperspectral imaging technology isolates fluorescence signals in narrow bands by 1) first filtering the excitation light to control sample excitation, then 2) further filtering emitted light to separate the fluorescence emission into narrow bands that can later be separated mathematically21. Filtering both the excitation illumination and emitted fluorescence reduces the amount of available signal, which lowers the signal-to-noise ratio and necessitates lengthy acquisition times. The low signal and lengthy acquisition times limit the applicability of hyperspectral imaging as a diagnostic tool.
An imaging modality has been developed that makes use of hyperspectral imaging but boosts the available signal, thereby reducing the necessary acquisition time21,22. This new modality, called excitation-scanning hyperspectral imaging, acquires spectral image data by varying the excitation wavelength and collecting a broad range of emitted light. It has been previously shown that this technique yields orders of magnitude increases in signal-to-noise ratio compared to emission scanning techniques21,22. The increase in signal-to-noise ratio is largely due to the wide bandpass (~600 nm) of emission light detected, while specificity is provided by filtering only the excitation light instead of the fluorescence emission. This allows all emitted light (for every excitation wavelength) to reach the detector21. Additionally, this technique can be used to discriminate autofluorescence from exogenous labels. Furthermore, the ability to reduce acquisition time due to increased detectable signal reduces the danger of photobleaching as well as allows spectral scans at an acquisition rate that is acceptable for spectral video imaging.
The goal of this protocol is to serve as a data acquisition guide for excitation-scanning hyperspectral imaging microscopy. In addition, descriptions are included that help to understand the light path and hardware. Also described is the implementation of open-source software for an excitation-scanning hyperspectral imaging microscope. Finally, descriptions are provided for how to calibrate the system to a NIST-traceable standard, adjust software and hardware settings for accurate results, and unmix the detected signal into contributions from individual components.

<table border="0" cellpadding="0" cellspacing="0" style="width:2119px;" width="2120">
	<tbody>
		<tr height="21">
			<td height="21" style="height:21px;width:327px;">Airway Smooth Muscle Cells</td>
			<td style="width:327px;">National Disease Research Interchange (NDRI)</td>
			<td style="width:360px;">Isolated from human lung tissues obtained from NDRI</td>
			<td style="width:1105px;">Highly autofluorescent, calcium sensitive cells</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:327px;">Automated Shutter</td>
			<td style="width:327px;">Thorlabs Inc.</td>
			<td style="width:360px;">SHB1</td>
			<td>Remote-controllable shutter to minimize photobleaching</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:327px;">Automated Stage</td>
			<td style="width:327px;">Prior Scientific</td>
			<td style="width:360px;">H177P1T4</td>
			<td>Remote-controllable stage for automated multiple field of view or stitched image collection.</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:327px;">Automated Stage Controller (XY)</td>
			<td style="width:327px;">Prior Scientific</td>
			<td style="width:360px;">Proscan III (H31XYZE-US)</td>
			<td>For interfacing automated stage with computer and joystick</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:327px;">Buffer</td>
			<td style="width:327px;">Made in-house</td>
			<td style="width:360px;">Made in-house</td>
			<td>145 mM NaCl, 4 mM KCl, 20 mM HEPES, 10 mM D-glucose, 1 mM MgCl2, and 1mM CaCl2, at pH 7.3</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:327px;">Cell Chamber</td>
			<td style="width:327px;">ThermoFisher Scientific</td>
			<td style="width:360px;">Attofluor Cell Chamber, A7816</td>
			<td>Coverslip holder composed of surgical stainless steel and a rubber O-ring to seal in media and prevent sample and/or objective contamination</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:327px;">Excitation Filters</td>
			<td style="width:327px;">Semrock Inc.</td>
			<td style="width:360px;">TBP01-378/16</td>
			<td>Center wavelength range (340-378 nm), Bandwidth (Minimum 16 nm, nominal FWHM 20 nm), Refractive index (1.88)</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:327px;"></td>
			<td style="width:327px;">Semrock Inc.</td>
			<td style="width:360px;">TBP01-402/16</td>
			<td>Center wavelength range (360-400 nm), Bandwidth (Minimum 16 nm, nominal FWHM 20 nm), Refractive index (1.8)</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:327px;"></td>
			<td style="width:327px;">Semrock Inc.</td>
			<td style="width:360px;">TBP01-449/15</td>
			<td>Center wavelength range (400-448.8 nm), Bandwidth (Minimum 15 nm, nominal FWHM 20 nm), Refractive index (1.8)</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:327px;"></td>
			<td style="width:327px;">Semrock Inc.</td>
			<td style="width:360px;">TBP01-501/15</td>
			<td>Center wavelength range (448.8-501.5 nm), Bandwidth (Minimum 15 nm, nominal FWHM 20 nm), Refractive index (1.84)</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:327px;"></td>
			<td style="width:327px;">Semrock Inc.</td>
			<td style="width:360px;">TBP01-561/14</td>
			<td>Center wavelength range (501.5-561 nm), Bandwidth (Minimum 14 nm, nominal FWHM 20 nm), Refractive index (1.83)</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:327px;">Fluorescence Filter Cube Dichroic Beamsplitter</td>
			<td style="width:327px;">Semrock Inc.</td>
			<td style="width:360px;">FF495-Di03</td>
			<td>Separates excitation and emission light at 495 nm (&#62;98% reflection between 350-488 nm, &#62;93% transmission between 502-950 nm), Filter effective index (1.78)</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:327px;">Fluorescence Filter Cube Longpass Filter</td>
			<td style="width:327px;">Semrock Inc.</td>
			<td style="width:360px;">FF01 496/LP-25</td>
			<td>Allows passage of light longer than 496 nm ( &#62;93% average transmission between 503.2-1100 nm), Refractive index (1.86)</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:327px;">GCaMP Probe</td>
			<td style="width:327px;">Addgene</td>
			<td style="width:360px;">G-CaMP3; Plasmid #22692</td>
			<td>A single-wavelength GCaMP2-based genetically encoded calcium indicator</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:327px;">Integrating Sphere</td>
			<td style="width:327px;">Ocean Optics</td>
			<td style="width:360px;">FOIS-1</td>
			<td>Used for accurate measurement of wide-angle illumination</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:327px;">Inverted Fluorescence Microscope</td>
			<td style="width:327px;">Nikon Instruments</td>
			<td style="width:360px;">TE2000</td>
			<td>Inverted microscopes allow direct excitation of sample without the need to penetrate layers of media and/or tissue.</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:327px;">Mitotracker Green FM</td>
			<td style="width:327px;">ThermoFisher Scientific</td>
			<td style="width:360px;">M7514</td>
			<td>Labels mitochondria</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:327px;">NIST-Traceable Calibration Lamp</td>
			<td style="width:327px;">Ocean Optics</td>
			<td style="width:360px;">LS-1-CAL-INT</td>
			<td>A lamp with a known spectrum for use as a standard</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:327px;">NIST-Traceable Fluorescein</td>
			<td style="width:327px;">ThermoFisher Scientific</td>
			<td style="width:360px;">F36915</td>
			<td>For verifying appropriate spectral response of the system</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:327px;">NucBlue</td>
			<td style="width:327px;">ThermoFisher Scientific</td>
			<td style="width:360px;">R37605</td>
			<td>Labels cell nuclei</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:327px;">Objective (10X)</td>
			<td style="width:327px;">Nikon Instruments</td>
			<td style="width:360px;">Plan Apo &#955; 10X/0.45 &#8734;/0.17 MRD00105</td>
			<td>Useful for large fields of view</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:327px;">Objective (20X)</td>
			<td style="width:327px;">Nikon Instruments</td>
			<td style="width:360px;">Plan Apo &#955; 20X/0.75 &#8734;/0.17 MRD00205</td>
			<td>Most often used for tissue samples</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:327px;">Objective (60X)</td>
			<td style="width:327px;">Nikon Instruments</td>
			<td>Plan Apo VC 60X/1.2 WI &#8734;/0.15-0.18 WD 0.27</td>
			<td>Most often used for cell samples</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:327px;">sCMOS Camera</td>
			<td style="width:327px;">Photometrics</td>
			<td style="width:360px;">Prime 95B (Rev A8-062802018)</td>
			<td>For acquiring high-sensitivity digital images</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:327px;">Spectrometer</td>
			<td style="width:327px;">Ocean Optics</td>
			<td style="width:360px;">QE65000</td>
			<td>Used to measure spectral output of excitation-scanning spectral system</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:327px;">Tunable Filter Changer</td>
			<td style="width:327px;">Sutter Instrument</td>
			<td style="width:360px;">Lambda VF-5</td>
			<td>Motorized unit for automated excitation filter tuning/switching</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:327px;">Xenon Arc Lamp</td>
			<td style="width:327px;">Sunoptic Technologies</td>
			<td style="width:360px;">Titan 300HP Lightsource</td>
			<td>Light source with relatively uniform spectral output</td>
		</tr>
	</tbody>
</table>

excitation-scanning hyperspectral imaging microscopy to efficiently discriminate fluorescence signals

Several techniques rely on detection of fluorescence signals to identify or study phenomena or to elucidate functions. Separation of these fluorescence signals were proven cumbersome until the advent of hyperspectral imaging, in which fluorescence sources can be separated from each other as well as from background signals and autofluorescence (given knowledge of their spectral signatures). However, traditional, emission-scanning hyperspectral imaging suffers from slow acquisition times and low signal-to-noise ratios due to the necessary filtering of both excitation and emission light. It has been previously shown that excitation-scanning hyperspectral imaging reduces the necessary acquisition time while simultaneously increasing the signal-to-noise ratio of acquired data. Using commercially available equipment, this protocol describes how to assemble, calibrate, and use an excitation-scanning hyperspectral imaging microscopy system for separation of signals from several fluorescence sources in a single sample. While highly applicable to microscopic imaging of cells and tissues, this technique may also be useful for any type of experiment utilizing fluorescence in which it is possible to vary excitation wavelengths, including but not limited to: chemical imaging, environmental applications, eye care, food science, forensic science, medical science, and mineralogy.

Several important steps from this protocol are necessary to ensure the collection of data that is both accurate and devoid of imaging and spectral artifacts. Skipping these steps may result in data that appear significant but cannot be verified or reproduced with any other spectral imaging system, thereby effectively nullifying any conclusions made with said data. Chief among these important steps is proper spectral output correction (section 3). The correction factor compensates for wave...

Watch this Scientific Journal Video about Excitation-Scanning Hyperspectral Imaging Microscopy to Efficiently Discriminate Fluorescence Signals at JoVE.com

Excitation-Scanning Hyperspectral Imaging Microscopy to Efficiently Discriminate Fluorescence Signals

Spectral imaging has become a reliable solution for identification and separation of multiple fluorescence signals in a single sample and can readily distinguish signals of interest from background or autofluorescence. Excitation-scanning hyperspectral imaging improves on this technique by decreasing the necessary image acquisition time while simultaneously increasing the signal-to-noise ratio.

Several techniques rely on detection of fluorescence signals to identify or study phenomena or to elucidate functions. Separation of these fluorescence ...

This protocol is significant as it describes a method which can be used to separate several fluorescent signals in a single sample. Compared to traditional methods, excitation-scanning can increase the speed of the experiment and improve the sensitivity of the data. By using different illumination sources such as a supercontinuum laser, this method may be applicable to spinning disk or laser scanning confocal microscope systems.When performing excitation-scannings, spectral imaging microscopy, it is important to check that the excitation peak of each fluorescent label occurs at a different wavelength. To begin, set up an inverted fluorescence microscope and camera as described in the text protocol. Then load the sample on the stage.From the drop-down menu of the micromanager main window, select 475 nanometers for initial sample viewing. Then double-click at the box next to exposure and enter 100 to set the exposure time at 100 milliseconds. Finally, click live to view the sample.Now click on Auto. The automatic intensity viewing range button to bring the minimum and maximum values into meaningful, visual ranges. Next, use the microscope's focus knobs to focus the sample.Once in focus, adjust the position of the sample so that it's edge is in the center of the field of view. Then fine-tune the focus. The sample is in focus when the edge features in the image appear sharp.Now, open the multi-dimensional acquisition tool. In the menu, click the load button and choose a preset setting containing an appropriate wavelength range for spectral acquisition. Once the acquisition settings are confirmed, move to a blank region of the sample and click acquire to collect a spectral image stack containing background and noise to use for subtraction later.Then, move about the sample to find the brightest regions. Samples are likely to have more intense fluorescence away from the edge of the sample. Once the brightest region is located, take a single image stack.Load the acquired image into Image J and use Image J's measure function to confirm that no wavelengths contain overexposed pixels. If a reduced exposure time is necessary due to overexposure, the background image should be retaken with a new exposure time as well. If any of the images were found to contain the upward detectional limit of the camera, adjust the exposure time of the spectral scan to ensure that the maximum signal throughout the spectral range does not exceed the dynamic range of the camera.With an appropriate exposure time now determined, place an unlabeled sample onto the stage. Acquire spectral image data from the unlabeled sample to determine if there is any underlying autofluoresence. Then, place a single-labeled sample on the stage.Acquire spectral image data from each of the single-labeled samples to use as spectral controls to build a spectral library. Perform the scan for each control sample using an identical wavelength range exposure time and camera settings. Next, place a slide containing the experimental sample on the microscope.Select a field of view that has appropriately labeled cells and acquire the spectral image data from the sample using the determined acquisition settings. Correct images to a flat spectral response by subtracting the background spectrum from the sample image and multiplying the image by the correction coefficient. Here, a MATLAB script is used to quickly process the images.Next, generate the spectral library. For best results, normalize each end member to the wavelength band of the greatest intensity by determining which wavelength band has the most intense value and dividing the measurement at each wavelength band by that maximum value. Then save the spectral data as a dat file.When complete, unmix the spectral image data. The unmixing step will generate an abundance image for each fluorescent label, where abundance is the amount of relative fluorescent signal in the image from the prospective label. Next, open each unmixed image to visually inspect the distribution of pure components.Compare the magnitude of the error image to those of the unmixed images. If the magnitude of the error image is similar to the unmixed abundance images, signals in the spectral image data may not be accurately accounted for. Finally, check that there are no unidentified residual structures by comparing the error image to the unmixed images.When performed correctly, the spectral unmixing process allows separation of a spectral image stack into respective contributions from each fluorescence label. Here, an unmixed spectral image set with individual images highlighting airway smooth muscle cell autofluorescence, a GCaMP probe and a mitochondrial label. There is high error associated with the nuclear and perinuclear regions of the cells indicating that the measured spectra of those regions are not well accounted for by the spectra in the spectral library.Pure spectra collected from labeled cells that are also autofluorescent will likely contaminate the spectral profile for the pure component. Here, one can see the difference of unmixing with pure spectra contaminated with autofluorescence, versus the corrected pure spectra after scaled subtraction. Proper data acquisition is essential when imaging sensitive samples as they may only survive a single imaging session unlike the background and controls which may be reimaged.Ensure that the proper hardware and acquisition settings are predetermined as much as possible. As a next step, videos created from time-lapse data acquired using this system can be used to track fluorescent sources in discreet locations over time such as second messenger signal localization. Take care when using powerful light sources to avoid eye exposure.Also, be sure to wear proper gloves when handling biological labels.

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Use of a Multi-compartment Dynamic Single Enzyme Phantom for Studies of Hyperpolarized Magnetic Resonance Agents

Imaging of hyperpolarized substrates by magnetic resonance shows great clinical promise for assessment of critical biochemical processes in real time. Due to fundamental constraints imposed by the hyperpolarized state, exotic imaging and reconstruction techniques are commonly used. A practical system for characterization of dynamic, multi-spectral imaging methods is critically needed. Such a system must reproducibly recapitulate the relevant chemical dynamics of normal and pathological tissues. The most widely utilized substrate to date is hyperpolarized [1-13C]-pyruvate for assessment of cancer metabolism. We describe an enzyme-based phantom system that mediates the conversion of pyruvate to lactate. The reaction is initiated by injection of the hyperpolarized agent into multiple chambers within the phantom, each of which contains varying concentrations of reagents that control the reaction rate. Multiple compartments are necessary to ensure that imaging sequences faithfully capture the spatial and metabolic heterogeneity of tissue. This system will aid the development and validation of advanced imaging strategies by providing chemical dynamics that are not available from conventional phantoms, as well as control and reproducibility that is not possible in vivo.

A multi-compartment dynamic phantom is used to simulate some biology of interest for metabolic studies using hyperpolarized magnet resonance agents.

Imaging of hyperpolarized substrates by magnetic resonance shows great clinical promise for assessment of critical biochemical processes in real time. Due ...

Dynamic Pore-scale Reservoir-condition Imaging of Reaction in Carbonates Using Synchrotron Fast Tomography

Underground storage permanence is a major concern for carbon capture and storage. Pumping CO2 into carbonate reservoirs has the potential to dissolve geologic seals and allow CO2 to escape. However, the dissolution processes at reservoir conditions are poorly understood. Thus, time-resolved experiments are needed to observe and predict the nature and rate of dissolution at the pore scale. Synchrotron fast tomography is a method of taking high-resolution time-resolved images of complex pore structures much more quickly than traditional &#181;-CT. The Diamond Lightsource Pink Beam was used to dynamically image dissolution of limestone in the presence of CO2-saturated brine at reservoir conditions. 100 scans were taken at a 6.1 &#181;m resolution over a period of 2 hours. The images were segmented and the porosity and permeability were measured using image analysis and network extraction. Porosity increased uniformly along the length of the sample; however, the rate of increase of both porosity and permeability slowed at later times.

Synchrotron fast tomography was used to dynamically image dissolution of limestone in the presence of CO2-saturated brine at reservoir conditions. 100 scans were taken at a 6.1 &#181;m resolution over a period of 2 h.

Underground storage permanence is a major concern for carbon capture and storage. Pumping CO2 into carbonate reservoirs has the potential to dissolve ...

Advanced Compositional Analysis of Nanoparticle-polymer Composites Using Direct Fluorescence Imaging

The fabrication of polymer-nanoparticle composites is extremely important in the development of many functional materials. Identifying the precise composition of these materials is essential, especially in the design of surface catalysts, where the surface concentration of the active component determines the activity of the material. Antimicrobial materials which utilize nanoparticles are a particular focus of this technology. Recently swell encapsulation has emerged as a technique for inserting antimicrobial nanoparticles into a host polymer matrix. Swell encapsulation provides the advantage of localizing the incorporation to the external surfaces of materials, which act as the active sites of these materials. However, quantification of this nanoparticle uptake is challenging. Previous studies explore the link between antimicrobial activity and surface concentration of the active component, but this is not directly visualized. Here we show a reliable method to monitor the incorporation of nanoparticles into a polymer host matrix via swell encapsulation. We show that the surface concentration of CdSe/ZnS nanoparticles can be accurately visualized through cross-sectional fluorescence imaging. Using this method, we can quantify the uptake of nanoparticles via swell encapsulation and measure the surface concentration of encapsulated particles, which is key in optimizing the activity of functional materials.

Here we present a reliable method to monitor the incorporation of nanoparticles into a polymer host matrix via swell encapsulation. We show that the surface concentration of cadmium selenide quantum dots can be accurately visualized through cross-sectional fluorescence imaging.

The fabrication of polymer-nanoparticle composites is extremely important in the development of many functional materials. Identifying the precise ...

Sub-nanometer Resolution Imaging with Amplitude-modulation Atomic Force Microscopy in Liquid

Atomic force microscopy (AFM) has become a well-established technique for nanoscale imaging of samples in air and in liquid. Recent studies have shown that when operated in amplitude-modulation (tapping) mode, atomic or molecular-level resolution images can be achieved over a wide range of soft and hard samples in liquid. In these situations, small oscillation amplitudes (SAM-AFM) enhance the resolution by exploiting the solvated liquid at the surface of the sample. Although the technique has been successfully applied across fields as diverse as materials science, biology and biophysics and surface chemistry, obtaining high-resolution images in liquid can still remain challenging for novice users. This is partly due to the large number of variables to control and optimize such as the choice of cantilever, the sample preparation, and the correct manipulation of the imaging parameters. Here, we present a protocol for achieving high-resolution images of hard and soft samples in fluid using SAM-AFM on a commercial instrument. Our goal is to provide a step-by-step practical guide to achieving high-resolution images, including the cleaning and preparation of the apparatus and the sample, the choice of cantilever and optimization of the imaging parameters. For each step, we explain the scientific rationale behind our choices to facilitate the adaptation of the methodology to every user's specific system.

We present a method for achieving sub-nanometer resolution images with amplitude-modulation (tapping mode) atomic force microscopy in liquid. The method is demonstrated on commercial atomic force microscopes. We explain the rationale behind our choices of parameters and suggest strategies for resolution optimization.

Atomic force microscopy (AFM) has become a well-established technique for nanoscale imaging of samples in air and in liquid. Recent studies have shown ...

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.

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.

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

Novel Photoacoustic Microscopy and Optical Coherence Tomography Dual-modality Chorioretinal Imaging in Living Rabbit Eyes

Photoacoustic ocular imaging is an emerging ophthalmic imaging technology that can noninvasively visualize ocular tissue by converting light energy into sound waves and is currently under intensive investigation. However, most reported work to date is focused on the imaging of the posterior segment of the eyes of small animals, such as rats and mice, which poses challenges for clinical human translation due to small eyeball sizes. This manuscript describes a novel photoacoustic microscopy (PAM) and optical coherence tomography (OCT) dual-modality system for posterior segment imaging of the eyes of larger animals, such as rabbits. The system configuration, system alignment, animal preparation, and dual-modality experimental protocols for in vivo, noninvasive, label-free chorioretinal imaging in rabbits are detailed. The effectiveness of the method is demonstrated through representative experimental results, including retinal and choroidal vasculature obtained by the PAM and OCT. This manuscript provides a practical guide to reproducing the imaging results in rabbits and advancing photoacoustic ocular imaging in larger animals.

This manuscript describes the novel setup and operating procedure of a photoacoustic microscopy and optical coherence tomography dual-modality system for noninvasive, label-free chorioretinal imaging of larger animals, such as rabbits.

Photoacoustic ocular imaging is an emerging ophthalmic imaging technology that can noninvasively visualize ocular tissue by converting light energy into ...

Synchrotron X-ray Microdiffraction and Fluorescence Imaging of Mineral and Rock Samples

In this report, we describe a detailed procedure for acquiring and processing&#160;x-ray microfluorescence (&#956;XRF), and Laue and powder microdiffraction two-dimensional (2D) maps at beamline 12.3.2 of the Advanced Light Source (ALS), Lawrence Berkeley National Laboratory. Measurements can be performed on any sample that is less than 10 cm x 10 cm x 5 cm, with a flat exposed surface. The experimental geometry is calibrated using standard materials (elemental standards for XRF, and crystalline samples such as Si, quartz, or Al2O3 for diffraction). Samples are aligned to the focal point of the x-ray microbeam, and raster scans are performed, where each pixel of a map corresponds to one measurement, e.g., one XRF spectrum or one diffraction pattern. The data are then processed using the in-house developed software XMAS, which outputs text files, where each row corresponds to a pixel position. Representative data from moissanite and an olive snail shell are presented to demonstrate data quality, collection, and analysis strategies.

We describe a beamline setup meant to carry out rapid two-dimensional x-ray fluorescence and x-ray microdiffraction mapping of single crystal or powder samples using either Laue (polychromatic radiation) or powder (monochromatic radiation) diffraction. The resulting maps give information about strain, orientation, phase distribution, and plastic deformation.

In this report, we describe a detailed procedure for acquiring and processing&#160;x-ray microfluorescence (&#956;XRF), and Laue and powder ...

Label-Free Imaging of Single Proteins Secreted from Living Cells via iSCAT Microscopy

We demonstrate interferometric scattering (iSCAT) microscopy, a method capable of detecting single unlabeled proteins secreted from individual living cells in real time. In this protocol, we cover the fundamental steps to realize an iSCAT microscope and complement it with additional imaging channels to monitor the viability of a cell under study. Following this, we use the method for real-time detection of single proteins as they are secreted from a living cell which we demonstrate with an immortalized B-cell line (Laz388). Necessary steps concerning the preparation of microscope and sample as well as the analysis of the recorded data are discussed. The video protocol demonstrates that iSCAT microscopy offers a straightforward method to study secretion at the single-molecule level.

We present a protocol for the real-time optical detection of single unlabeled proteins as they are secreted from living cells. This is based on interferometric scattering (iSCAT) microscopy, which can be applied to a variety of different biological systems and configurations.

We demonstrate interferometric scattering (iSCAT) microscopy, a method capable of detecting single unlabeled proteins secreted from individual living ...

Multiplexing Focused Ultrasound Stimulation with Fluorescence Microscopy

By focusing low-intensity ultrasound pulses that penetrate soft tissues, LIPUS represents a promising biomedical technology to remotely and safely manipulate neural firing, hormonal secretion and genetically-reprogrammed cells. However, the translation of this technology for medical applications is currently hampered by a lack of biophysical mechanisms by which targeted tissues sense and respond to LIPUS. A suitable approach to identify these mechanisms would be to use optical biosensors in combination with LIPUS to determine underlying signaling pathways. However, implementing LIPUS to a fluorescence microscope may introduce undesired mechanical artefacts due to the presence of physical interfaces that reflect, absorb and refract acoustic waves. This article presents a step-by-step procedure to incorporate LIPUS to commercially-available upright epi-fluorescence microscopes while minimizing the influence of physical interfaces along the acoustic path. A simple procedure is described to operate a single-element ultrasound transducer and to bring the focal zone of the transducer into the objective focal point. The use of LIPUS is illustrated with an example of LIPUS-induced calcium transients in cultured human glioblastoma cells measured using calcium imaging.

Low-Intensity Pulsed Ultrasound Stimulation (LIPUS) is a modality for non-invasive mechanical stimulation of endogenous or engineered cells with high spatial and temporal resolution. This article describes how to implement LIPUS to an epi-fluorescence microscope and how to minimize acoustic impedance mismatch along the ultrasound path to prevent unwanted mechanical artefacts.

By focusing low-intensity ultrasound pulses that penetrate soft tissues, LIPUS represents a promising biomedical technology to remotely and safely ...

In Situ Transmission Electron Microscopy with Biasing and Fabrication of Asymmetric Crossbars Based on Mixed-Phased a-VOx

Resistive switching crossbar architecture is highly desired in the field of digital memories due to low cost and high-density benefits. Different materials show variability in resistive switching properties due to the intrinsic nature of the material used, leading to discrepancies in the field because of underlying operation mechanisms. This highlights a need for a reliable technique to understand mechanisms using nanostructural observations. This protocol explains a detailed process and methodology of in&#160;situ nanostructural analysis as a result of electrical biasing using transmission electron microscopy (TEM). It provides visual and reliable evidence of underlying nanostructural changes in real time memory operations. Also included is the methodology of fabrication and electrical characterizations for asymmetric crossbar structures incorporating amorphous vanadium oxide. The protocol explained here for vanadium oxide films can be easily extended to any other materials in a metal-dielectric-metal sandwiched structure. Resistive switching crossbars are predicted to serve the programmable logic and neuromorphic circuits for next-generation memory devices, given the understanding of the operation mechanisms. This protocol reveals the switching mechanism in a reliable, timely, and cost-effective way in any type of resistive switching materials, and thereby predicts the device&#39;s applicability.

In Situ Transmission Electron Microscopy with Biasing and Fabrication of Asymmetric Crossbars Based on Mixed-Phased a-VOx

Presented here is a protocol for analyzing nanostructural changes during in&#160;situ biasing with transmission electron microscopy (TEM) for a stacked metal-insulator-metal structure. It has significant applications in resistive switching crossbars for the next generation of programmable logic circuits and neuromimicking hardware, to reveal their underlying operation mechanisms and practical applicability.