This work was supported by ANR P2N (Nanother project 2010-NANO-008-04), by the Region Ile de France (contract no E539),&#160;and by CNRS. Open Access was paid for by EMD Millipore.

1. Preparation of Water Dispersible Carbon Nanotubes (CNTs)
<ol>
	<li>Disperse first CNTs in cell culture water, before sonicating them for 20 min in a bath-water sonicator at 20 &#176;C. If CNTs are functionalized with a fluorescent probe, protect them as much as possible from light throughout the experiment.</li>
</ol>
2. Labeling Cells with CNTs
<ol>
	<li>Grow human umbilical vein endothelial cells (HUVEC) (for example) on 25 cm&#178; plates in DMEM medium, containing 10% fetal bovine serum and 1% penicillin streptomycin.</li>
	<li>Prepare solutions of CNTs at concentration of 0, 10, 20, and 50 &#181;g/ml&#160;in complete medium and incubate cells with at 37 &#176;C for 20 hr or at 4 &#176;C for 20 hr (2ml&#160;of CNT suspension for a 25 cm&#178; plate).</li>
</ol>
3. Cell Fixation
<ol>
	<li>Remove incubation medium afterwards; rinse cells with PBS, trypsinize,&#160;and resuspend cells in complete DMEM medium. Centrifuge for 5 min at 1,200 rpm.</li>
	<li>Replace the medium first by paraformaldehyde 4% for 1 hr at 4 &#176;C, then by PBS to preserve them. If needed, cells can be stored at this stage of the process at 4 &#176;C for several days until the cytometry analysis.</li>
	<li>Each sample has to contain about 106 cells concentrated in 50 &#181;l&#160;of PBS. Suspend them correctly to avoid aggregates during the analysis and filter them through a 50 &#956;m mesh stainer. 
	Note: Each step has to be performed very gently to preserve cells.</li>
</ol>
4. ImageStream Acquisition
Use the multispectral imaging flow cytometer ImageStream to acquire images of cells. 
Some points have to be respected:
<ol>
	<li>Select an adapted magnification (here a 40X objective is used).</li>
	<li>If fluorochromes are used: 
	- prepare a control sample without fluorochrome. 
	- prepare cells with a single-color positive control for each fluorochrome used in 
	addition to your samples.</li>
	<li>Use the laser 488 nm to excite the FITC and the channel 02 to collect the fluorescence emission (band-pass 480-560 nm). In addition, use also the channels 01 and 06 for the bright field (BF) and dark field(DF) respectively.</li>
</ol>
5. Post Processing - IDEAS Analysis Software (Version 4.0)
<ol>
	<li>Among all the events acquired, the analysis has to be first restricted to the population of single cells: use a biparametric dot plot representing &#39;aspect ratio&#39; (i.e.&#160;width/height) versus &#39;cell area&#39; (parameters applied on cells on BF) (Figure 1). Single cells included in the region of interest with a standard area and aspect ratio close to 1 are then discriminated from multicellular events (large area and small aspect ratio) and debris (extremely small area).</li>
	<li>To select cells in the focused plane, use a biparametric dot plot adapted for highly contrasted CNTs-labeled cells: plot the &#39;contrast&#39; versus the &#39;RMS gradient&#39; (which measures the sharpness quality of an image) on the BF image - it allows the exclusion of unfocused cells showing both a low rms gradient and a low contrast in their BF images (Figure 1).</li>
	<li>
	<ol>
		<li>Determine the parameter which provides the best statistical separation between labeled and nonlabeled cells by using the &#34;find the best feature&#34;. In our study, the mean pixel object feature is the parameter which is the most suitable (Figure 2).</li>
		<li>Trace an histogram using this parameter versus the normalized frequency to compare the quantity of uptaken-CNTs for tested concentrations (Figure 3).</li>
		<li>Trace the biparametric graph &#39;mean pixel object on BF&#39; (Notation: Mean Pixel_Object (M01,Ch01,Tight)_Ch01) versus &#39;intensity on DF&#39;(Intensity_MC_Ch06), in order to study the correlation between these two parameters (Figure 4).</li>
	</ol>
	</li>
	<li>The quantification is also assessed by means of masks:
	<ol>
		<li>As CNTs appears as strongly absorbing dark spots on BF, create first a threshold mask that fit them precisely by selecting a restricted range of pixels with a low intensity comprised between 0-533 in this study (Mask 1, notation: Intensity(M01, BF, 0-533)) (Figure 5). The choice of the threshold intensity is made on labeled cells in comparison to the control cells.</li>
		<li>Conversely create also a mask fitting with the pixels of high intensity (150-4095 in this case) of the DF (Mask 2, notation: Intensity (M06, DF, 150-4095)) (Figure 6).</li>
		<li>Plot a graph using the area of the mask (either 1 or 2; (notation: Area_Intensity(M01, BF, 0-533)for mask 1): it will provide a relative quantification of the internalization of CNTs at different concentrations (Figure 7).</li>
		<li>Check the degree of correlation between these two masks (thanks to the biparametric plot &#39;area of Mask 1&#39; versus &#39;area of Mask 2&#39;) (Figure 7).</li>
	</ol>
	</li>
	<li>Create other masks to localize CNTs in cells:
	<ol>
		<li>A mask fitting the interior of the cell: Erode(M01, 7) - corresponding to the mask of the entire cell (M01) (Figure 8), which is further eroded of 7 pixels (Figure 9).</li>
		<li>A mask fitting the membrane only using the Boolean equation: M01 and not Erode(M01,7) - mask of the entire cell (M01) subtracted from the interior (Erode(M01,7)) (Figure 10).</li>
		<li>To consider the dark pixels on the membrane (corresponding to CNTs), create then the mask: Intensity(M01 and not Erode(M01, 7), BF, 0-533) (Figure 11).</li>
		<li>Visualize the different masks applied on a collection of cells to check their relevance (Figure 12) for labeled and unlabeled cells.</li>
		<li>Apply the feature area on the mask selecting the black pixels on the membrane &#39;Area_Intensity(M01 and not Erode(M01, 7), BF, 0-533)&#39; so called black area. It will allow the quantification of the CNTs on the membrane. 
		 
		To discriminate finally CNTs that have been internalized from those adsorbed only on the membrane, plot the black area on the membrane versus the black area on the entire cell (i.e. &#39;Area_ Intensity(M01 and not Erode(M01, 7), BF, 0-533&#39; versus &#39;Area_ Intensity(M01, BF, 0-533)&#39;). 
		 
		Note: The same type of procedure is applied with the FITC-fluorescent signal: compare the increase of the intensity of FITC fluorescence versus the decrease of the mean pixel signal on the BF, or the colocalization between dark spots on BF and FITC fluorescence intensity. In our case, this type of analysis is not relevant because fluorescence signal does not correctly match with dark spots on BF on one hand and with bright field on DF on the other hand, showing that intrinsic properties of CNTs (light absorbance and scattering) are more appropriate than the signal related to the fluorescence probe.</li>
	</ol>
	</li>
	<li>Once all plots are created on one experimental condition create a &#34;statistical report template&#34;, save template as .ast file and batch all data files.</li>
</ol>

<ol>
	<li>Kostarelos, K., Bianco, A., Prato, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Promises,+facts+and+challenges+for+carbon+nanotubes+in+imaging+and+therapeutics.">Promises, facts and challenges for carbon nanotubes in imaging and therapeutics.</a> Nat. Nano. 4, 627-633 (2009).</li><li>De La Zerda, A., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Carbon+nanotubes+as+photoacoustic+molecular+imaging+agents+in+living+mice.">Carbon nanotubes as photoacoustic molecular imaging agents in living mice.</a> Nat. Nano. 3, 557-562 (2008).</li><li>Zavaleta, C., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Noninvasive+Raman+Spectroscopy+in+Living+Mice+for+Evaluation+of+Tumor+Targeting+with+Carbon+Nanotubes.">Noninvasive Raman Spectroscopy in Living Mice for Evaluation of Tumor Targeting with Carbon Nanotubes.</a> Nano Lett. 8, 2800-2805 (2008).</li><li>Tong, L., 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=Label-free+imaging+of+semiconducting+and+metallic+carbon+nanotubes+in+cells+and+mice+using+transient+absorption+microscopy.">Label-free imaging of semiconducting and metallic carbon nanotubes in cells and mice using transient absorption microscopy.</a> Nat. Nano. 7, 56-61 (2012).</li><li>Welsher, K., 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=A+route+to+brightly+fluorescent+carbon+nanotubes+for+near-infrared+imaging+in+mice.">A route to brightly fluorescent carbon nanotubes for near-infrared imaging in mice.</a> Nat. Nano. 4, 773-780 (2009).</li><li>Jin, H., Heller, D. A., Sharma, R., Strano, M. S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Size+dependent+cellular+uptake+and+expusion+of+single-wall+carbon+nanotubes:+single+particle+tracking+and+a+generic+uptake+model+for+nanoparticles.">Size dependent cellular uptake and expusion of single-wall carbon nanotubes: single particle tracking and a generic uptake model for nanoparticles.</a> ACS Nano. 3, 149-158 (2009).</li><li>Al-Jamal, K. T., 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=Cellular+uptake+mechanisms+of+functionalised+multi-walled+carbon+nanotubes+by+3D+electron+tomography+imaging.">Cellular uptake mechanisms of functionalised multi-walled carbon nanotubes by 3D electron tomography imaging.</a> Nanoscale. 3, 2627-2635 (2011).</li><li>Reuel, N. F., Dupont, A., Thouvenin, O., Lamb, D. C., Strano, M. S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Three-Dimensional+Tracking+of+Carbon+Nanotubes+within+Living+Cells.">Three-Dimensional Tracking of Carbon Nanotubes within Living Cells.</a> ACS Nano. 6, 5420-5428 (2012).</li><li>Phanse, Y., Ramer-Tait, A. E., Friend, S. L., Carrillo-Conde, B., Lueth, P., Oster, C. 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=Analyzing+Cellular+Internalization+of+Nanoparticles+and+Bacteria+by+Multi-spectral+Imaging+Flow+Cytometry.">Analyzing Cellular Internalization of Nanoparticles and Bacteria by Multi-spectral Imaging Flow Cytometry.</a> J. Vis. Exp. (64), e3884 (2012).</li><li>Qian, F., Montgomery, R. R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Quantitative+Imaging+of+Lineage-specific+Toll-like+Receptor-mediated+Signaling+in+Monocytes+and+Dendritic+Cells+from+Small+Samples+of+Human+Blood.">Quantitative Imaging of Lineage-specific Toll-like Receptor-mediated Signaling in Monocytes and Dendritic Cells from Small Samples of Human Blood.</a> J. Vis. Exp. (62), e3741 (2012).</li><li>Marangon, I., 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=Intercellular+Carbon+Nanotube+Translocation+Assessed+by+Flow+Cytometry+Imaging.">Intercellular Carbon Nanotube Translocation Assessed by Flow Cytometry Imaging.</a> Nano Lett. 12, 4830-4837 (2012).</li><li>Lacerda, L., 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=Translocation+mechanisms+of+chemically+functionalised+carbon+nanotubes+across+plasma+membranes.">Translocation mechanisms of chemically functionalised carbon nanotubes across plasma membranes.</a> Biomaterials. 33, 3334-3343 (2012).</li><li>Al-Jamal, K. 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The authors declare that they have no competing financial interests.

1. Modification and Troubleshooting
In this study, the first objective was to evaluate the quantity and the localization of CNTs in cells. The confocal microscopy could have been a priori the gold method to assess the intracellular distribution of CNTs functionalized with the fluorescent marker FITC8,14. However, the main drawback is the limitation to single cell imaging and, therefore, a lack of statistically relevant data. The ImageStream allows work beyond these obstacles: indeed, by screening a large number of cells (5,000-10,000) in a short time (&#60;min), it yields statistically robust results, enhanced also by the high resolution imaging which provides images for each cell with a subcellular resolution (0.5 &#181;m). It makes then possible to analyze a large amount of data based on single image analysis.
In comparison to conventional flow cytometry, the unique advantage of ImageStream is to provide multispectral images of each cell and a pixel by pixel comparison of signal intensity. Thus ImageStream combines the statistical power of high throughput flow cytometry with the analytical advantages of confocal imaging for each analyzed cell. It is crucial for a label-free relative quantification and localization of CNTs in cells.
2. Critical Steps Within the Protocol
The critical step consists of the choice of parameters most suitable of each study. In our case, the best way was to base the analysis on the absorption and scattering properties of the nanotubes: the good correlation between the localization of dark spots on BF and bright spots on DF supports that the developed method is relevant and reliable - and may not have been possible without cell imaging.
3. Limitations of the Technique
It must be emphasized that the visualization of CNTs in cells was possible only because they tend to accumulate in endosomal intracellular vesicles, and then appear as strong absorptive and scattering spots. Individual nanotubes should not be detected based on this method whereas it could be eventually detected on fluorescence, which constitutes a clear limitation. Second, the quantification is not &#39;absolute&#39; but relative for different labeling concentrations and in comparison to the control unlabeled cells. Some quantitative features (mean pixel, intensity, etc.) are absolute parameters, whereas others depend on the choice of the masks (threshold mask, localization masks).
4. Significance with Respect to Existing Methods
In regards to fluorescence, the ImageStream analysis highlights the poor colocalization of CNT clusters between FITC bright signal and spots on the others channels. Therefore, it appears that fluorescence was not a reliable indicator for the quantification and localization of CNTs. Nevertheless, overcoming the limitation of conventional flow cytometry, which is mainly based on fluorescence quantification, the multispectral high throughput ImageStream paves the way for a statistical label-free quantification, while providing localization of carbon nanotubes inside the cells.
5. Future Applications
This high throughput statistical nanometrology method could be generalized to any nanomaterials, which show high absorption and scattering of light when interacting with cells. Therefore, it may have important applications for investigations of the nano-bio-interface, nanotoxicology, and nanomedicine.

During the last decades, the place of nanoparticles has gained in importance in a wide range of applications. In particular, carbon nanotubes (CNTs) are more and more explored as nanotools for diverse diagnostic and therapeutic applications; thanks to their particular electrical, thermal, and spectroscopic properties, CNTs can act as delivery vehicles for varied drugs or contrast agents, or can also be involved in tissue engineering1.
However, concerns about the potential toxicity of such nanomaterials are still under debate, mainly because the fate of CNTs in the organism remains very controversial. There is indeed a lack of appropriate methods to detect and quantify them in live cells and tissues: for example, techniques such as Raman spectroscopy, photoacoustic, and near-infrared photoluminescence imaging have been suggested, but each method shows limitations depending on the type of nanotubes and/or their environment2-8.
Here, the method proposed could be applicable for the detection and quantification of nanoparticles in cells. This was made possible by the use of ImageStream, a device combining both flow cytometry and high resolution imaging. It couples the advantages of acquiring a large among of cells (up to 5000 events/sec) - and benefits of statistical data and high resolution images of each cell at the same time (0.5 &#181;m spatial resolution). Generally, images are collected using a CCD camera and are a two dimensional grey scale representation of the cell. The light is quantified for each pixel in the image and identifies both the intensity and the location of either fluorescence or components with a subcellular size (in BF for example), allowing thus a powerful ability to discriminate cells based on their appearance9,10.&#160;
The aim was here to design a nanometrology method which would enable a quantitative assessment of the distribution and behavior of CNTs in cells. In particular, this method was developed to study cellular uptake, processing and exocytosis of CNTs by cells. We evidenced first the complex cellular trafficking of CNTs and secondly the transfer of these nanomaterials between cells: cell-internalized CNTs escape their host cells when stressed, spread abroad in the extracellular space and are reinternalized by na&#239;ve cells, whether they are homotypic or heterotypic11
.
Previous study showed that different mechanisms of cell uptake, either active or passive ones, could occur depending on CNT functionalization and aggregation state12. Here the multi-walled CNTs were functionalized through 1,3-dipolar cycloaddition and amidation and then derivatized with a fluorescent probe, fluoresce in isothiocyanate (FITC). On transmission electron microscopy, they appear to be internalized by cells either individually with cytosolic localization or as bundles, mostly found in endosomal and lysosomal compartments11. On ImageStream, the clustered CNTs appear with a high correlation as dark spots on BF and bright spots on DF, allowing a clear distinction between CNT-labeled cells and control cells. On the other hand, the distribution of the fluorescent signal emitted by the fluorescent marker functionalized with CNTs was not as well colocalized: indeed, likely due to a quenching phenomenon, the green fluorescent spots do not necessarily match the spots on BF and DF. This indicates that, firstly, a fluorescent probe is not mandatory for the detection of CNTs with the ImageStream, and secondly - a fortiori - that it is not fully representative for both quantification and localization of CNTs.
Beyond giving a statistical relative quantification of nanoparticles, this method also provides information concerning the localization of CNTs in cells, meaning that it discriminates, for instance, CNTs on the interior of the cell versus those which are bound to the plasma membrane. The ability to localize CNTs on cell images clearly overcomes the limitation of conventional flow cytometry analysis13. The procedure was developed here via the creation of masks fitting with specific regions of the cell and selecting also the dark spots corresponding to loaded CNTs.
Generally speaking, this method could be applied for a large range of experiments involving the need of visualization, or quantification, in cells on condition that the nanoparticles used are able to strongly absorb (and/or scatter) the light.

<table border="0" cellpadding="0" cellspacing="0" width="481">
	<colgroup>
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		<col width="71" />
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		<col width="79" />
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	<tbody>
		<tr height="21">
			<td height="21" style="height:15.75pt;width:146pt" width="194">ImageStream</td>
			<td class="xl63" style="width:53pt" width="71">Amnis</td>
			<td class="xl63" style="width:103pt" width="137"></td>
			<td class="xl63" style="width:59pt" width="79"></td>
		</tr>
	</tbody>
</table>

localization and relative quantification of carbon nanotubes in cells with multispectral imaging flow cytometry

Carbon-based nanomaterials, like carbon nanotubes (CNTs), belong to this type of nanoparticles which are very difficult to discriminate from carbon-rich cell structures and de facto there is still no quantitative method to assess their distribution at cell and tissue levels. What we propose here is an innovative method allowing the detection and quantification of CNTs in cells using a multispectral imaging flow cytometer (ImageStream, Amnis). This newly developed device integrates both a high-throughput of cells and high resolution imaging, providing thus images for each cell directly in flow and therefore statistically relevant image analysis. Each cell image is acquired on bright-field (BF), dark-field (DF), and fluorescent channels, giving access respectively to the level and the distribution of light absorption, light scattered and fluorescence for each cell. The analysis consists then in a pixel-by-pixel comparison of each image, of the 7,000-10,000 cells acquired for each condition of the experiment. Localization and quantification of CNTs is made possible thanks to some particular intrinsic properties of CNTs: strong light absorbance and scattering; indeed CNTs appear as strongly absorbed dark spots on BF and bright spots on DF with a precise colocalization.
This methodology could have a considerable impact on studies about interactions between nanomaterials and cells given that this protocol is applicable for a large range of nanomaterials, insofar as they are capable of absorbing (and/or scattering) strongly enough the light.

An overview of the principle of the ImageStream device is given in Figure 1. It produces multiple high resolution images of each cell in flow, including bright-field (BF), dark-field (DF or side-scattered light), and fluorescence channel(s), as exemplified in Figure 2 with three different cells labeled with CNTs. The overlays of these channels are also shown, at first sight illustrating the correlation.
Given that all the post-processing analysis is based on cell imaging, the selection of focused cells is crucial for the study (Figure 3). Actually, the presence of CNTs induces changes on both the contrast and the gradient compared to nonlabeled cells: focused cells, having internalized an important quantity of CNTs, tend to have a low rms gradient (which is usually the unique parameter used for the discrimination of focused versus unfocused cells) but also an important contrast, explaining why a biparametric plot is essential. On Figure 3 is shown the discrimination between unfocused (yellow area) versus focused cells (blue area).
Cell-internalized CNTs are clearly distinguishable - particularly on BF appearing as strongly absorbing dark spots (see the effect of diverse labeling concentration, Figure 4). Moreover, the mean pixel signal on BF was analyzed, giving a relative quantification of the uptake: graphs on Figure 5 show its significant increase with the CNT-labeling concentration (results for about 7,000 cells per experimental condition).
Second, quantification of CNTs is also possible through the use of masks, applied either on a restricted range of dark pixels of the BF or on the pixel of high intensity of the DF (see examples on Figure 6), corresponding to the spots resulting from the presence of CNTs. Thus, plotting the area of these masks allows highlighting as well as the increase of the uptake (exemplified on Figure 7 with the area of the mask on BF, selecting pixels ranging from 0-533).
In addition, the correlation between spots on BF and DF can be evaluated by plotting the DF intensity versus the BF mean pixel signal (as in Figure 8) (mask-independent analysis) or the area of the mask on BF (Mask 1) versus the area on DF (Mask 2).
Regarding the procedure created for the localization of CNTs inside the cells, Figure 9A displays the different masks that were created. Note that the robustness of the localization masks (based on erosion of default cell mask) must be checked visually on a collection of labeled and unlabeled cells. The same masks are used for all samples.
Plotting the total area of black spots on the cell membrane versus that on the entire cell provides a score of internalization for cells which have been incubated for 20 hr at 37 &#176;C in comparison to 2 hr incubation at 4 &#176;C (see Figure 9B); it indicates that CNTs are mostly located on the membrane at 4 &#176;C, whereas at 37 &#176;C CNTs are internalized in more than 90% of cells.
Finally concerning the fluorescence, this parameter was not used as indicator for the quantification of CNTs due to a too low correlation between fluorescent spots and spots on BF (and DF). Indeed, the correlation between the FITC intensity and the bright field mean pixel indicates a Pearson correlation coefficient of -0.2. On Figure 10, two cases are illustrated, in which the fluorescence signal matches properly or not with the bright field black spot.
<img alt="Figure 1" fo:content-width="5in" fo:src="/files/ftp_upload/50566/50566fig1highres.jpg" src="/files/ftp_upload/50566/50566fig1.jpg" /> 
Figure 1. Overview of the ImageStream- general operating.&#160;The multispectral imaging system acquires up to 12 images/cell in three different modes: brightfield, darkfield, and fluorescence. The setup consists in 5 excitation lasers, including 405, 488, 560, and 658 nm. Light is collected from the cells flowing in the cuvette with different objective lens (in this study, the 40X&#160;objective lens was used) and relayed to the spectral decomposition element, which consists in a set of longpass filters in an angular array. The CCD camera collecting cell images is operated using a technique called time-delay-integration in order to avoid image streaking. Extended depth of field (EDF) is an option.
<img alt="Figure 2" fo:content-width="5in" fo:src="/files/ftp_upload/50566/50566fig2highres.jpg" src="/files/ftp_upload/50566/50566fig2.jpg" /> 
Figure 2. Image gallery of cells labeled with carbon nanotubes (50 &#956;g/mL) captured by ImageStream through diverse channels (Bright Field (BF), Dark field (DF), fluorescence (FITC), and their overlays). CNTs confined within intracellular lysosomes appear as large black spots on bright field images. Conversely they create bright spots on the dark field and on the fluorescence images.
<img alt="Figure 3" fo:content-width="5in" fo:src="/files/ftp_upload/50566/50566fig3highres.jpg" src="/files/ftp_upload/50566/50566fig3.jpg" /> 
Figure 3. Selection of cells in focus. Bivariate dot plot representing root mean square (rms) gradient versus contrast on BF images allows the exclusion of unfocused cells. Here the yellow area represents unfocused cells, whereas focused cells are represented in blue. The unfocused cells are characterized by both low contrast and low gradient rms on the bright field image. In addition to rms gradient, the contrast feature is require to discriminate focused cells after their labeling with CNTs.
<img alt="Figure 4" fo:content-width="5in" fo:src="/files/ftp_upload/50566/50566fig4highres.jpg" src="/files/ftp_upload/50566/50566fig4.jpg" /> 
Figure 4.&#160;Dose-dependent uptake of CNTs visualized by ImageStream. The number and area of black spots on the bright field images are increasing with the dose of CNTs during incubation with cells (ranging from 0-50 &#181;g/ml). Note that the control cells are devoid of black spots.
<img alt="Figure 5" fo:content-width="5in" fo:src="/files/ftp_upload/50566/50566fig5highres.jpg" src="/files/ftp_upload/50566/50566fig5.jpg" /> 
Figure 5.&#160;Relative quantification of CNT-uptake based on the bright field images. Histograms of the mean pixel feature applied to the mask &#34;object&#34; featuring the whole cell clearly show a dose-dependent behavior, which can be used for quantification. R9 range encloses the CNT-positive cells.
<img alt="Figure 6" fo:content-width="5in" fo:src="/files/ftp_upload/50566/50566fig6highres.jpg" src="/files/ftp_upload/50566/50566fig6.jpg" /> 
Figure 6.&#160;Creation of masks selecting black spots on BF and bright spots on DF images. As CNTs appear as strongly absorbing dark spots on BF image, a threshold mask is created to select a restricted range of pixels with a low intensity comprised between 0-533 in this study (Mask 1, notation: Intensity(M01, BF, 0-533)). Conversely, a mask fitting with the pixels of high intensity (150-4095 in this case) on DF image (Mask 2, notation: Intensity (M06, DF, 150-4095)) is used to select bright spot on DF, corresponding to high scattering areas.
<img alt="Figure 7" fo:content-width="5in" fo:src="/files/ftp_upload/50566/50566fig7highres.jpg" src="/files/ftp_upload/50566/50566fig7.jpg" /> 
Figure 7.&#160;Dose-dependent uptake of CNTs is demonstrated by quantification of the black spot area on BF images. Using threshold mask (mask 1) applied on BF, the area of black spots can be quantified for each cell, showing a dose-dependent distribution.
<img alt="Figure 8" fo:content-width="5in" fo:src="/files/ftp_upload/50566/50566fig8highres.jpg" src="/files/ftp_upload/50566/50566fig8.jpg" /> 
Figure 8.&#160;CNT quantification methods based on BF (absorption) and DF (scattering) images are correlated. On the left, mean pixel on the BF image versus intensity on the DF image, show a good correlation for cells labeled with CNTs (50 &#181;g/ml) (Pearson correlation coefficient r = -0.68). On the right, area of the mask fitting dark spots on BF versus area of the mask fitting bright spots on DF for cells labeled with CNTs (50 &#181;g/ml). Pearson correlation coefficient is r = -0.83.Values from 7,000 cells are plotted.
<img alt="Figure 9" fo:content-width="5in" fo:src="/files/ftp_upload/50566/50566fig9highres.jpg" src="/files/ftp_upload/50566/50566fig9.jpg" /> 
Figure 9.&#160;CNT localization in cells using specific masks. (A) Masks are created to fit a particular location of the cell, namely from left to right - the entire cell, the membrane only, and the inside of the cell. Another mask fits black spots thanks to a threshold intensity (Mask 1, notation: Intensity(M01, BF, 0-533)). (B) Assessment of the localization of CNTs can be obtained by measuring the area of black spots on different localizations of the cells using the localization masks described in A. Incubation with CNTs (50 &#181;g/ml) was performed both at 37 &#176;C and at 4 &#176;C to inhibit internalization pathway. The graph representing black area on the membrane versus black area on the entire cell shows a dose-dependent absorption of CNTs on the membrane at 4 &#176;C, while the full internalization of CNTs is effective at 37 &#176;C.
<img alt="Figure 10" fo:content-width="3in" fo:src="/files/ftp_upload/50566/50566fig10highres.jpg" src="/files/ftp_upload/50566/50566fig10.jpg" /> 
Figure 10.&#160;Colocalization of CNT-induced black spots on BF with fluorescence bright spots on FITC image. The fluorescence bright spots are not always colocalized with the black spots on BF. They match properly for the first two cells displayed, but not for the last two cells.

Watch this Scientific Journal Video about Localization and Relative Quantification of Carbon Nanotubes in Cells with Multispectral Imaging Flow Cytometry at JoVE.com

Localization and Relative Quantification of Carbon Nanotubes in Cells with Multispectral Imaging Flow Cytometry

In this study, the main purpose was to monitor the cellular uptake and eventual exocytosis of carbon nanotubes (CNTs). From this perspective, we proposed here a unique method using multispectral imaging flow cytometry allowing a quantification and localization of CNTs in a statistically relevant number of cells.

Carbon-based nanomaterials, like carbon nanotubes (CNTs), belong to this type of nanoparticles which are very difficult to discriminate from carbon-rich ...

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6.0K Views.  CNRS/Université Paris Diderot. In this study, the main purpose was to monitor the cellular uptake and eventual exocytosis of carbon nanotubes (CNTs). From this perspective, we proposed here a unique method using multispectral imaging flow cytometry allowing a quantification and localization of CNTs in a statistically relevant number of cells.

Video: Localization and Relative Quantification of Carbon Nanotubes in Cells with Multispectral Imaging Flow Cytometry

Simultaneous Synthesis of Single-walled Carbon Nanotubes and Graphene in a Magnetically-enhanced Arc Plasma

Carbon nanostructures such as single-walled carbon nanotubes (SWCNT) and graphene attract a deluge of interest of scholars nowadays due to their very promising application for molecular sensors, field effect transistor and super thin and flexible electronic devices1-4. Anodic arc discharge supported by the erosion of the anode material is one of the most practical and efficient methods, which can provide specific non-equilibrium processes and a high influx of carbon material to the developing structures at relatively higher temperature, and consequently the as-synthesized products have few structural defects and better crystallinity.
 To further improve the controllability and flexibility of the synthesis of carbon nanostructures in arc discharge, magnetic fields can be applied during the synthesis process according to the strong magnetic responses of arc plasmas. It was demonstrated that the magnetically-enhanced arc discharge can increase the average length of SWCNT 5, narrow the diameter distribution of metallic catalyst particles and carbon nanotubes 6, and change the ratio of metallic and semiconducting carbon nanotubes 7, as well as lead to graphene synthesis 8. 
 Furthermore, it is worthwhile to remark that when we introduce a non-uniform magnetic field with the component normal to the current in arc, the Lorentz force along the J&times;B direction can generate the plasmas jet and make effective delivery of carbon ion particles and heat flux to samples. As a result, large-scale graphene flakes and high-purity single-walled carbon nanotubes were simultaneously generated by such new magnetically-enhanced anodic arc method. Arc imaging, scanning electron microscope (SEM), transmission electron microscope (TEM) and Raman spectroscopy were employed to analyze the characterization of carbon nanostructures. These findings indicate a wide spectrum of opportunities to manipulate with the properties of nanostructures produced in plasmas by means of controlling the arc conditions.

Anodic arc discharge is one of the most practical and efficient methods to synthesize various carbon nanostructures. To increase the arc controllability and flexibility, a non-uniform magnetic field was introduced to process the one-step synthesis of large-scale graphene flakes and high-purity single-walled carbon nanotubes.

Carbon nanostructures such as single-walled carbon nanotubes (SWCNT) and graphene attract a deluge of interest of scholars nowadays due to their very ...

Analyzing Cellular Internalization of Nanoparticles and Bacteria by Multi-spectral Imaging Flow Cytometry

Nanoparticulate systems have emerged as valuable tools in vaccine delivery through their ability to efficiently deliver cargo, including proteins, to antigen presenting cells1-5. Internalization of nanoparticles (NP) by antigen presenting cells is a critical step in generating an effective immune response to the encapsulated antigen. To determine how changes in nanoparticle formulation impact function, we sought to develop a high throughput, quantitative experimental protocol that was compatible with detecting internalized nanoparticles as well as bacteria. To date, two independent techniques, microscopy and flow cytometry, have been the methods used to study the phagocytosis of nanoparticles. The high throughput nature of flow cytometry generates robust statistical data. However, due to low resolution, it fails to accurately quantify internalized versus cell bound nanoparticles. Microscopy generates images with high spatial resolution; however, it is time consuming and involves small sample sizes6-8. Multi-spectral imaging flow cytometry (MIFC) is a new technology that incorporates aspects of both microscopy and flow cytometry that performs multi-color spectral fluorescence and bright field imaging simultaneously through a laminar core. This capability provides an accurate analysis of fluorescent signal intensities and spatial relationships between different structures and cellular features at high speed.
	Herein, we describe a method utilizing MIFC to characterize the cell populations that have internalized polyanhydride nanoparticles or Salmonella enterica serovar Typhimurium. We also describe the preparation of nanoparticle suspensions, cell labeling, acquisition on an ImageStreamX system and analysis of the data using the IDEAS application. We also demonstrate the application of a technique that can be used to differentiate the internalization pathways for nanoparticles and bacteria by using cytochalasin-D as an inhibitor of actin-mediated phagocytosis.

In this article, we describe a method utilizing multi-spectral imaging flow cytometry to quantify the internalization of polyanhydride nanoparticles or bacteria by RAW 264.7 cells.

Nanoparticulate  systems have emerged as valuable tools in vaccine delivery through their  ability to efficiently deliver cargo, including proteins, to ...

Protocol for Relative Hydrodynamic Assessment of Tri-leaflet Polymer Valves

Limitations of currently available prosthetic valves, xenografts, and homografts have prompted a recent resurgence of developments in the area of tri-leaflet polymer valve prostheses. However, identification of a protocol for initial assessment of polymer valve hydrodynamic functionality is paramount during the early stages of the design process. Traditional in vitro pulse duplicator systems are not configured to accommodate flexible tri-leaflet materials; in addition, assessment of polymer valve functionality needs to be made in a relative context to native and prosthetic heart valves under identical test conditions so that variability in measurements from different instruments can be avoided. Accordingly, we conducted hydrodynamic assessment of i) native (n = 4, mean diameter, D = 20 mm), ii) bi-leaflet mechanical (n= 2, D = 23 mm) and iii) polymer valves (n = 5, D = 22 mm) via the use of a commercially available pulse duplicator system (ViVitro Labs Inc, Victoria, BC) that was modified to accommodate tri-leaflet valve geometries. Tri-leaflet silicone valves developed at the University of Florida comprised the polymer valve group. A mixture in the ratio of 35:65 glycerin to water was used to mimic blood physical properties. Instantaneous flow rate was measured at the interface of the left ventricle and aortic units while pressure was recorded at the ventricular and aortic positions. Bi-leaflet and native valve data from the literature was used to validate flow and pressure readings. The following hydrodynamic metrics were reported: forward flow pressure drop, aortic root mean square forward flow rate, aortic closing, leakage&#160;and regurgitant volume, transaortic closing, leakage, and total energy losses. Representative results indicated that hydrodynamic metrics from the three valve groups could be successfully obtained by incorporating a custom-built assembly into a commercially available pulse duplicator system and subsequently, objectively compared to provide insights on functional aspects of polymer valve design.

There has been renewed interest in developing polymer valves. Here, the objectives are to demonstrate the feasibility of modifying a commercial pulse duplicator to accommodate tri-leaflet geometries and to define a protocol to present polymer valve hydrodynamic data in comparison to native and prosthetic valve data collected under near-identical conditions.

Limitations of currently available prosthetic valves, xenografts, and homografts have prompted a recent resurgence of developments in the area of ...

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 ...

Quantification of Global Diastolic Function by Kinematic Modeling-based Analysis of Transmitral Flow via the Parametrized Diastolic Filling Formalism

Quantitative cardiac function assessment remains a challenge for physiologists and clinicians.&#160;Although historically invasive methods have comprised the only means available, the development of noninvasive imaging modalities (echocardiography, MRI, CT) having high temporal and spatial resolution provide a new window for quantitative diastolic function assessment. Echocardiography is the agreed upon standard for diastolic function assessment, but indexes in current clinical use merely utilize selected features of chamber dimension (M-mode) or blood/tissue motion (Doppler) waveforms without incorporating the physiologic causal determinants of the motion itself.&#160;The recognition that all left ventricles (LV) initiate filling by serving as mechanical suction pumps allows global diastolic function to be assessed based on laws of motion that apply to all chambers. What differentiates one heart from another are the parameters of the equation of motion that governs filling. Accordingly, development of the Parametrized Diastolic Filling (PDF) formalism&#160;has shown that the entire range of clinically observed early transmitral flow (Doppler E-wave) patterns are extremely well fit by the laws of damped oscillatory motion.&#160;This permits analysis of individual E-waves in accordance with a causal mechanism (recoil-initiated suction) that yields three (numerically) unique lumped parameters whose physiologic analogues are chamber stiffness (k), viscoelasticity/relaxation (c), and load (xo).&#160;The recording of transmitral flow (Doppler E-waves) is standard practice in clinical cardiology and, therefore, the echocardiographic recording method is only briefly reviewed. Our focus is on determination of the PDF parameters from routinely recorded E-wave data.&#160;As the highlighted results indicate, once the PDF parameters have been obtained from a suitable number of load varying E-waves, the investigator is free to use the parameters or construct indexes from the parameters (such as stored energy 1/2kxo2, maximum A-V pressure gradient kxo, load independent index of diastolic function, etc.) and select the aspect of physiology or pathophysiology to be quantified.

Accurate, causality-based quantification of global diastolic function has been achieved by kinematic modeling-based analysis of transmitral flow via the Parametrized Diastolic Filling (PDF) formalism. PDF generates unique stiffness, relaxation,&#160;and load parameters and elucidates &#39;new&#39; physiology while providing sensitive and specific indexes of dysfunction.

Quantitative cardiac function assessment remains a challenge for physiologists and clinicians.&#160;Although historically invasive methods have comprised ...

Sensitive Detection of Proteopathic Seeding Activity with FRET Flow Cytometry

Increasing evidence supports transcellular propagation of toxic protein aggregates, or proteopathic seeds, as a mechanism for the initiation and progression of pathology in several neurodegenerative diseases, including Alzheimer's disease and the related tauopathies. The potentially critical role of tau seeds in disease progression strongly supports the need for a sensitive assay that readily detects seeding activity in biological samples. 
By combining the specificity of fluorescence resonance energy transfer (FRET), the sensitivity of flow cytometry, and the stability of a monoclonal cell line, an ultra-sensitive seeding assay has been engineered and is compatible with seed detection from recombinant or biological samples, including human and mouse brain homogenates. The assay employs monoclonal HEK 293T cells that stably express the aggregation-prone repeat domain (RD) of tau harboring the disease-associated P301S mutation fused to either CFP or YFP, which produce a FRET signal upon protein aggregation. The uptake of proteopathic tau seeds (but not other proteins) into the biosensor cells stimulates aggregation of RD-CFP and RD-YFP, and flow cytometry sensitively and quantitatively monitors this aggregation-induced FRET. The assay detects femtomolar concentrations (monomer equivalent) of recombinant tau seeds, has a dynamic range spanning three orders of magnitude, and is compatible with brain homogenates from tauopathy transgenic mice and human tauopathy subjects. With slight modifications, the assay can also detect seeding activity of other proteopathic seeds, such as &#945;-synuclein, and is also compatible with primary neuronal cultures. The ease, sensitivity, and broad applicability of FRET flow cytometry makes it useful to study a wide range of protein aggregation disorders.

Cell-to-cell transfer of protein aggregates, or proteopathic seeds, may underlie the progression of pathology in neurodegenerative diseases. Here, a novel FRET flow cytometry assay is described that enables specific and sensitive detection of seeding activity from recombinant or biological samples.

Increasing evidence supports transcellular propagation of toxic protein aggregates, or proteopathic seeds, as a mechanism for the initiation and ...

Engineering Molecular Recognition with Bio-mimetic Polymers on Single Walled Carbon Nanotubes

Semiconducting single-wall carbon nanotubes (SWNTs) are a class of optically active nanomaterial that fluoresce in the near infrared, coinciding with the optical window where biological samples are most transparent. Here, we outline techniques to adsorb amphiphilic polymers and polynucleic acids onto the surface of SWNTs to engineer their corona phases and create novel molecular sensors for small molecules and proteins. These functionalized SWNT sensors are both biocompatible and stable. Polymers are adsorbed onto the nanotube surface either by direct sonication of SWNTs and polymer or by suspending SWNTs using a surfactant followed by dialysis with polymer. The fluorescence emission, stability, and response of these sensors to target analytes are confirmed using absorbance and near-infrared fluorescence spectroscopy. Furthermore, we demonstrate surface immobilization of the sensors onto glass slides to enable single-molecule fluorescence microscopy to characterize polymer adsorption and analyte binding kinetics.

We present a protocol for engineering the corona phase of near infrared fluorescent single walled carbon nanotubes (SWNTs) using amphiphilic polymers and DNA to develop sensors for molecular targets without known recognition elements.

Semiconducting single-wall carbon nanotubes (SWNTs) are a class of optically active nanomaterial that fluoresce in the near infrared, coinciding with the ...

Isolation of Primary Murine Retinal Ganglion Cells (RGCs) by Flow Cytometry

Neurodegenerative diseases often have a devastating impact on those affected. Retinal ganglion cell (RGC) loss is implicated in an array of diseases, including diabetic retinopathy and glaucoma, in addition to normal aging. Despite their importance, RGCs have been extremely difficult to study until now due in part to the fact that they comprise only a small percentage of the wide variety of cells in the retina. In addition, current isolation methods use intracellular markers to identify RGCs, which produce non-viable cells. These techniques also involve lengthy isolation protocols, so there is a lack of practical, standardized, and dependable methods to obtain and isolate RGCs. This work describes an efficient, comprehensive, and reliable method to isolate primary RGCs from mice retinae using a protocol based on both positive and negative selection criteria. The presented methods allow for the future study of RGCs, with the goal of better understanding the major decline in visual acuity that results from the loss of functional RGCs in neurodegenerative diseases.

Isolation of Primary Murine Retinal Ganglion Cells RGCs by Flow Cytometry

Millions of people suffer from retinal degenerative diseases that result in irreversible blindness. A common element of many of these diseases is the loss of retinal ganglion cells (RGCs). This detailed protocol describes the isolation of primary murine RGCs by positive and negative selection with flow cytometry.

Neurodegenerative diseases often have a devastating impact on those affected. Retinal ganglion cell (RGC) loss is implicated in an array of diseases, ...

Synthesis of Multi-walled Carbon Nanotubes Modified with Silver Nanoparticles and Evaluation of Their Antibacterial Activities and Cytotoxic Properties

In this study, multi-walled carbon nanotubes (MWCNTs) were treated with an aqueous sulfuric acid solution to form an oxygen-based functional group. Silver MWCNTs were prepared by the reductive deposition of silver from an aqueous solution of AgNO3 on the oxidized MWCNTs. Given the unique color of the CNTs, it was not possible to apply them to the minimum inhibitory concentration or mitochondrial toxicity assays to evaluate the toxicity and antibacterial properties, since they would interfere with the assays. The inhibition zone and minimum bactericidal concentration for the Ag-MWCNTs were measured and Live/Dead and Trypan Blue assays were used to measure the toxicity and antibacterial properties without interfering with the color of the CNTs.

In this study, antimicrobial nanomaterials were synthesized by acidic oxidation of multiwalled carbon nanotubes and subsequent reductive deposition of silver nanoparticles. Antimicrobial activity and cytotoxicity tests were performed with the as-prepared nanomaterials.

In this study, multi-walled carbon nanotubes (MWCNTs) were treated with an aqueous sulfuric acid solution to form an oxygen-based functional group. Silver ...

An Automated Method to Perform The In Vitro Micronucleus Assay using Multispectral Imaging Flow Cytometry

The in vitro micronucleus (MN) assay is often used to evaluate cytotoxicity and genotoxicity but scoring the assay via manual microscopy is laborious and introduces uncertainty in results due to variability between scorers. To remedy this, automated slide-scanning microscopy as well as conventional flow cytometry methods have been introduced in an attempt to remove scorer bias and improve throughput. However, these methods have their own inherent limitations such as inability to visualize the cytoplasm of the cell and the lack of visual MN verification or image data storage with flow cytometry. Multispectral Imaging Flow Cytometry (MIFC) has the potential to overcome these limitations. MIFC combines the high resolution fluorescent imagery of microscopy with the statistical robustness and speed of conventional flow cytometry. In addition, all collected imagery can be stored in dose-specific files. This paper describes the protocol developed to perform a fully automated version of the MN assay on MIFC. Human lymphoblastoid TK6 cells were enlarged using a hypotonic solution (75 mM KCl), fixed with 4% formalin and the nuclear content was stained with Hoechst 33342. All samples were run in suspension on the MIFC, permitting acquisition of high resolution images of all key events required for the assay (e.g. binucleated cells with and without MN as well as mononucleated and polynucleated cells). Images were automatically identified, categorized and enumerated in the MIFC data analysis software, allowing for automated scoring of both cytotoxicity and genotoxicity. Results demonstrate that using MIFC to perform the in vitro MN assay allows statistically significant increases in MN frequency to be detected at several different levels of cytotoxicity when compared to solvent controls following exposure of TK6 cells to Mitomycin C and Colchicine, and that no significant increases in MN frequency are observed following exposure to Mannitol.

The in vitro micronucleus assay is a well-established method for evaluating genotoxicity and cytotoxicity but scoring the assay using manual microscopy is laborious and suffers from subjectivity and inter-scorer variability. This paper describes the protocol developed to perform a fully automated version of the assay using multispectral imaging flow cytometry.

The in vitro micronucleus (MN) assay is often used to evaluate cytotoxicity and genotoxicity but scoring the assay via manual microscopy is laborious and ...