Name: high content screening analysis to evaluate the toxicological effects of harmful and potentially harmful constituents (hphc)
Uploaded: 2016-05-10T15:00:00.000+00:00
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Description: Watch this Scientific Journal Video about High Content Screening Analysis to Evaluate the Toxicological Effects of Harmful and Potentially Harmful Constituents HPHC at JoVE.com

The authors would like to thank Karsta Luettich and Gr&#233;gory Vuillaume for their review of the manuscript.

<ol>
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Y. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Pardaxin+an+antimicrobial+peptide,+triggers+caspase-dependent+and+ROS-mediated+apoptosis+in+HT-1080+Cells.">Pardaxin an antimicrobial peptide, triggers caspase-dependent and ROS-mediated apoptosis in HT-1080 Cells.</a> Mar. Drugs. 9 (10), 1995-2009 (2011).</li><li>Bao, S., Knoell, D. L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Zinc+modulates+cytokine-induced+lung+epithelial+cell+barrier+permeability.">Zinc modulates cytokine-induced lung epithelial cell barrier permeability.</a> Am. J. Physiol. Lung Cell Mol. 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All authors are employees of Philip Morris International. Philip Morris International is the sole source of funding and sponsor of this project.

The needs for alternatives to animal experimentation and for new high throughput testing approaches have been widely discussed over the past years. This has led scientists and regulatory authorities to investigate alternative methods for standard toxicity testing, utilizing cellular assays that closely mimic the physiology of target tissues. In this study, we have demonstrated the applicability of combining a real-time cell analyzer (RTCA) with a high content screening (HCS) platform to assess the impact of exposure to single CS constituents on human lung epithelial cells. This setup could be analogously applied to evaluate cytotoxicity induced by various other airborne pollutants, airborne particles, and nanoparticles. Furthermore, the obtained results can be matched with those from whole-genome transcriptomics and computational methods based on causal biological networks. As previously reported, this approach allowed us to corroborate data on molecular pathway perturbation upon CS exposure5 with HCS endpoints, addressing these pathway perturbations also phenotypically.
As a flowchart assay, real-time cell analysis provides cell viability-related information in a dose- and time-dependent resolution, which allows better decision making which dose and exposure time point may be favorable for downstream analysis14. The principle of the analyzer relies on changes in electrical impedance generated by the cells as they attach and spread on a culture well surface covered with a gold microelectrode. The impedance is converted into a dimensionless parameter named cell-index, which can be used to monitor cell adhesion, spreading, morphology and ultimately cell viability. Though this technique does not provide information on cytotoxic mechanisms, its sensitivity enables detection of morphological cellular changes even at very low doses at which the HCS is not informative (data not shown). Based on previous experiments, we have noted that RTCA methodology is able to detect morphological changes at lower doses compared to the HCS endpoints.
Following initial screening with the real-time cell analyzer, a HCS platform was used to gain more in-depth information on the kind of cytotoxicity elicited by each HPHC. The HCS assay panel allowed to profile HPHCs towards their potential impact on cellular compartments/organelles as well as to identify those eliciting genotoxicity or oxidative stress. The analysis revealed distinct profiles whereby the selected HPHCs induce cytotoxicity in NHBE cells. In general, all the compounds, except Phenol, were found to induce necrosis at the highest tested doses. Consistent with a potential role in cancer development 1-aminonaphtalene induced phosphorylation of H2AX as a marker for genotoxicity, however the HCS panel also uncovered activity of this HPHC in the mitochondrial toxicity readout (mass increased and cytochrome C release) and oxidative stress (GSH depletion). Similarly, as previously described, Phenol was identified to induce mitochondrial dysfunction, and cause DNA damage as well as GSH depletion. Chromium (VI), one of the compounds classified as group I carcinogens, and Crotonaldehyde were also both identified as genotoxic, in particular Chromium (VI) also induced apoptosis (caspase cascade activation) and Crotonaldehyde caused increased ROS generation. Finally Arsenic (V), was found to induce cJun phosphorylation which is a marker of stress kinase pathway activation.
In this study, we utilized NHBE cells as a model for lung epithelial cells in vitro. Using these cells in a HCS setting is unprecedented and enabled the investigation of a broader range of endpoints, including genotoxicity and oxidative stress markers. Both live cell and fixed cell staining approaches were described within our protocols, demonstrating the flexibility of the overall technique. In fact, the very same protocols can be applied to a broader range of targets, which can be addressed by the use of any fluorescent dye or antibody. For the successful execution of the live staining protocols, it is important to respect the incubation time, as some of the dyes have a limited half-life and the fluorescence signal may decrease before the image acquisition is completed. It is also important to consider that if a different cell type is used, all the staining conditions should be re-evaluated, as the optimal dye concentration and the incubation time may be different.
In the current paper we have described a scenario where only five compounds where screened with the HCS methodology. Considering the previously described plate layout, they were dosed over 2 different plate sets for a total of 24 plates (6 assays and 2 time-points).The number of plates could also be increased, thereby allowing for the simultaneous screening of more compounds or the investigation of more endpoints. Before doing so, however, one should take into consideration that certain endpoints (GSH and ROS) require immediate acquisition, and as a consequence, the dosing of the plates should be performed in a staggered fashion to permit the acquisition of the previous plate. On the other hand, using a fixed cell staining protocol represents an advantage as the plates can be stacked, interrupting the protocol at any step after the fixation, for completion of the staining procedure at a later stage. This approach, for example, would provide the operator with the time to complete all live cell staining plates without compromising the data quality.
To further optimize the workflow by decreasing the number of plates, it would also be possible to multiplex more endpoints together. For example in this context DNA Damage and Stress Kinase could be investigated together simply using two secondary antibody with fluorochromes emitting in different channels. Continuous development of the HCS platform, including fully automated cell seeding, compound dilution, dosing and staining, as well as the addition of new endpoints will further expand the capability of the HCS platform as a powerful profiling tool for HPHCs on epithelial and other cell types.

Toxicological risk assessment has historically relied on the use of animal models which, though fundamental in the life sciences, are also linked with shortcomings such as inconsistent translatability to humans and high cost. Furthermore, there has been an increasing effort to find alternatives to animal testing in the spirit of &#34;The 3Rs&#34;2 (replacement, reduction, and refinement). This effort has been accelerated over the past few years, not only because of recent advances such as high-throughput techniques and systems biology approaches, but also because of legislation restricting the use of animal testing, especially in the European Union.
The complexity of cellular signaling pathways regulating the response to toxic insults makes it evident that using single toxicological endpoints will not be sufficient to describe the toxicological basis of certain compounds. For this, the interplay of hundreds of interacting proteins contributing to a biological network will also need to be taken into account. To study the effect of toxicants on those networks, a system toxicology approach combined with phenotypic medium- and high-throughput screening assays is useful to infer potencies and at the same time provide more information on the mechanism of action of individual toxicants.
In this study, we employed HCS as a powerful screening tool, which is composed of an automated microscope and a biological software application, that can acquire, process and analyze image data derived from specific fluorescence-based cellular assays. This allows for visual changes within a cell to be quantified, at a single cell or subcellular level, and many parameters to be analyzed simultaneously.3 For example, DNA double-strand breaks were evaluated using an antibody-based identification of histone H2AX phosphorylation and reactive oxygen species (ROS) were quantified using a cell-permeable superoxide sensitive dye.
Because lung epithelial cells represent the first biological barrier against inhaled toxicants, including cigarette smoke, we utilized primary bronchial epithelial cells as an in vitro model to profile the effect of HPHCs published by the United States Food and Drug Administration.4 This manuscript is a follow-up on a previous study5 in which we evaluated the biological impact of a different subset of HPHCs.
As part of our workflow to assess cytotoxicity in vitro, we initially evaluated the potencies of a selection of 15 HPHC&#39;s, using an impedance-based real-time cellular analysis (RTCA) system which allowed us to establish dose-ranges, suitable for subsequent HCS analysis (Figure 1). A toxicological HCS assessment was then conducted using nine multi-parametric endpoints of cellular toxicity, each monitored at two time points (4 and 24 hr). The markers used were indicative of mitochondrial toxicity, DNA damage, stress kinase, reactive oxygen species (ROS), glutathione (GSH) content, caspase 3 - 7 activity, cytochrome C release and cell membrane permeability, as described in Table 1.
Our approach enabled identification and characterization of the effect of cigarette smoke constituents through dose- and time-dependent sampling. Ultimately, this produced an in vitro toxicological profile for each HPHC. Multi-omics approaches can also be used to further complement the HCS analysis. This would finally also provide a deeper understanding of the effects at the cell signaling and/or transcriptional level.

<table><tbody><tr><td>Cellomics ArrayScan VTI HCS Reader</td><td>Thermo</td><td>N01-0002B</td><td></td></tr><tr><td>xCelligence RTCA MP</td><td>ACEA</td><td>05331625001</td><td></td></tr><tr><td>Screener (HCS)</td><td>Genedata</td><td>NA</td><td></td></tr><tr><td>CASY counter TTC</td><td>Roche</td><td>05 651 719 001</td><td></td></tr><tr><td>e-Plates VIEW 96</td><td>ACEA</td><td>06 472 451 001</td><td></td></tr><tr><td>RTCA Frame 96</td><td>ACEA</td><td>05232392001</td><td></td></tr><tr><td>RTCA Cardio Temperature Tool</td><td>ACEA</td><td>2801171</td><td></td></tr><tr><td>Plate sealer breathseal</td><td>Greiner bio-one</td><td>676051</td><td></td></tr><tr><td>Normal Human Bronchial Epithelial cells (NHBE)</td><td>Lonza</td><td>CC-2540</td><td>non-smoking 60-year-old Caucasian male donor&amp;nbsp;</td></tr><tr><td>BEGM BulletKit</td><td>Lonza</td><td>CC-3170</td><td>Warm at 37 &amp;deg;C before use</td></tr><tr><td>ReagentPack Subculture Reagents kit</td><td>Lonza</td><td>CC-5034</td><td>Warm at 37 &amp;deg;C before use</td></tr><tr><td>Penicillin/Streptomycin (100x)</td><td>Corning</td><td>30-002-CI</td><td></td></tr><tr><td>Easy Flask filter cap 75&amp;nbsp;cm&lt;sup&gt;2&lt;/sup&gt;</td><td>Thermo Scientific</td><td>12-565-349</td><td></td></tr><tr><td>96 well assay plate&amp;nbsp; black&amp;nbsp;</td><td>Corning</td><td>3603</td><td></td></tr><tr><td>Hoechst 33342&amp;nbsp;</td><td>Fisher Scientific</td><td>PI-62249</td><td></td></tr><tr><td>Draq5 (For Far Red Nuclear Staining)</td><td>Biostatus</td><td>DR50200</td><td></td></tr><tr><td>Mitochondrial Dye: MitoTracker Red CMXRos</td><td>Life technologies</td><td>M-7512</td><td></td></tr><tr><td>Mitochondrial Dye: MitoTracker Red CM-H2XRos</td><td>Life technologies</td><td>M-7513</td><td></td></tr><tr><td>ROS Dye: Dihydroethidium</td><td>Sigma</td><td>D7008</td><td></td></tr><tr><td>ROS Dye: CellROX</td><td>Life technologies</td><td>C10422</td><td></td></tr><tr><td>ROS Dye: MitoSOX</td><td>Life technologies</td><td>M36008</td><td></td></tr><tr><td>GSH Dye: Monochlorobimane</td><td>Sigma</td><td>69899</td><td>Toxic</td></tr><tr><td>GSH Dye: Monobromobimane</td><td>Life technologies</td><td>M-1378</td><td>Toxic</td></tr><tr><td>Membrane permeability Dye: YO-PRO-1&amp;nbsp;</td><td>Life technologies</td><td>Y3603</td><td>Irritating&amp;nbsp;</td></tr><tr><td>Membrane permeability Dye: TO-PRO-1&amp;nbsp;</td><td>Life technologies</td><td>T3602</td><td>Irritating&amp;nbsp;</td></tr><tr><td>Membrane permeability Dye: TOTO-1&amp;nbsp;</td><td>Life technologies</td><td>T3600</td><td>Irritating&amp;nbsp;</td></tr><tr><td>Caspase Dye: Cellevent Caspase 3/7 green</td><td>Life technologies</td><td>C10423</td><td>Irritating&amp;nbsp;</td></tr><tr><td>Anti-Cytochrome C antibody (Mouse)</td><td>Thermo</td><td>MA5-11823</td><td></td></tr><tr><td>Anti-phospho-c-Jun antibody (Mouse)</td><td>Thermo</td><td>MA5-15889</td><td></td></tr><tr><td>Anti-phospho-H2AX antibody (Mouse)</td><td>Thermo</td><td>MA1-2022</td><td></td></tr><tr><td>Goat anti-Mouse IgG DyLight 650&amp;nbsp;</td><td>Abcam</td><td>ab96878</td><td></td></tr><tr><td>10x permeabilization buffer</td><td>Fisher</td><td>8408400</td><td></td></tr><tr><td>4% Formaldehyde solution</td><td>Sigma</td><td>F1635</td><td>Toxic</td></tr><tr><td>10x blocking buffer</td><td>Fisher</td><td>8408500</td><td></td></tr><tr><td>Dulbecco&amp;rsquo;s Phosphate Buffered Saline&amp;nbsp;</td><td>Sigma</td><td>D8537</td><td></td></tr><tr><td>Hanks&#039; Balanced Salt solution</td><td>Sigma</td><td>H8264</td><td></td></tr><tr><td>Staurosporine</td><td>Sigma</td><td>S4400</td><td>Toxic</td></tr><tr><td>Valinomycin</td><td>Sigma</td><td>V0627</td><td>Toxic</td></tr><tr><td>Paraquat</td><td>Sigma</td><td>36541</td><td>Toxic</td></tr><tr><td>Anisomycin</td><td>Sigma</td><td>A9789</td><td>Toxic</td></tr><tr><td>Ethacrynic acid</td><td>Sigma</td><td>E4754</td><td>Toxic</td></tr><tr><td>1-Aminonaphthalene</td><td>Sigma</td><td>34390</td><td>Toxic</td></tr><tr><td>2-Nitropropane</td><td>Sigma</td><td>130265</td><td>Toxic</td></tr><tr><td>Acetamide</td><td>Sigma</td><td>695122</td><td>Toxic</td></tr><tr><td>Acetone</td><td>Sigma</td><td>650501</td><td>Toxic</td></tr><tr><td>Acrylamide</td><td>Sigma</td><td>A9099</td><td>Toxic</td></tr><tr><td>Arsenic (V)</td><td>Sigma</td><td>A6756</td><td>Toxic</td></tr><tr><td>Benzene</td><td>Sigma</td><td>12540</td><td>Toxic</td></tr><tr><td>Chromium (VI)</td><td>Sigma</td><td>216623</td><td>Toxic</td></tr><tr><td>Crotonaldehyde</td><td>Sigma</td><td>262668</td><td>Toxic</td></tr><tr><td>Methyl ethyl ketone</td><td>Sigma</td><td>34861</td><td>Toxic</td></tr><tr><td>Nickel&amp;nbsp;</td><td>Sigma</td><td>203866</td><td>Toxic</td></tr><tr><td>Nitrobenzene</td><td>Sigma</td><td>48547</td><td>Toxic</td></tr><tr><td>Phenol</td><td>Sigma</td><td>P5566</td><td>Toxic</td></tr><tr><td>Quinoline</td><td>Sigma</td><td>241571</td><td>Toxic</td></tr><tr><td>Toluene</td><td>Sigma</td><td>34866</td><td>Toxic</td></tr></tbody></table>

high content screening analysis to evaluate the toxicological effects of harmful and potentially harmful constituents (hphc)

Cigarette smoke (CS) is a major risk factor for cardiovascular and lung diseases. Because CS is a complex aerosol containing more than 7,000 chemicals1 it is challenging to assess the contributions of individual constituents to its overall toxicity. Toxicological profiles of individual constituents as well as mixtures can be however established in vitro, by applying high through-put screening tools, which enable the profiling of Harmful and Potentially Harmful Constituents (HPHCs) of tobacco smoke, as defined by the U.S. Food and Drug Administration (FDA).2
For an initial assessment, an impedance-based instrument was used for a real-time, label-free assessment of the compound&#39;s toxicity. The instrument readout relies on cell adhesion, viability and morphology that all together provide an overview of the cell status. A dimensionless parameter, named cell index, is used for quantification. A set of different staining protocols was developed for a fluorescence imaging-based investigation and a HCS platform was used to gain more in-depth information on the kind of cytotoxicity elicited by each HPHC.
Of the 15 constituents tested, only five were selected for HCS-based analysis as they registered a computable LD50 (&#60; 20 mM). These included 1-aminonaphtalene, Arsenic (V), Chromium (VI), Crotonaldehyde and Phenol. Based on their effect in the HCS, 1-aminonaphtalene and Phenol could be identified to induce mitochondrial dysfunction, and, together with Chromium (VI) as genotoxic based on the increased histone H2AX phosphorylation. Crotonaldehyde was identified as an oxidative stress inducer and Arsenic as a stress kinase pathway activator.
This study demonstrates that a combination of impedance-based and HCS technologies provides a robust tool for in vitro assessment of CS constituents.

RTCA
Because the HCS endpoints will not be informative when no toxic effect is detected, those compounds not showing decreased cell viability up to the highest concentration in the RCTA are not tested by HCS (Figure 3b,c,d,g,k,l,m,p). Compounds showing decreased cell viability at only the highest concentration (Figure 3e,o) are also deselected for HCS. Finally, only the constituents with a computable LD50 (&#60; 20 mM) are selected for further HCS analysis (Figure 3a,f,h,j,n). HPHCs meeting the above criteria are: 1-aminonaphtalene, Arsenic (V), Chromium (VI), Crotonaldehyde and Phenol.
HCS
As a Quality Check (QC), positive controls are first analyzed to assure that staining procedure is correctly performed. Representative pictures of positive control-treated cells are shown in Figure 6. Data values are normalized to vehicle as previously described. No dose-response curves are plotted as only three doses are tested and not all the three doses are considered at every time-point. Positive control doses are selected (based on previous experiments, data not shown) so that appropriate responses are observed for each endpoint at both 4 hr and 24 hr. In particular doses 1 and 2 are used to evaluate the effect at 4 hr while doses 2 and 3 are used to evaluate the effect at 24 hr. Plates are discarded if no response is observed for the positive control doses. Note that for all the endpoints, except mitochondrial membrane potential and GSH content, an increase of the signal intensity is expected.
All compounds, except for Phenol, induced a necrotic phenotype, based on increased cell membrane permeability (Figure 7a,f,h,l). 1-aminonaphtalene, Chromium (VI), Crotonaldehyde and Phenol were identified as being genotoxic based on increased phosphorylation of the histone H2AX (Figure 7e,j,n,p). Phenol and 1-aminonaphtalene were found to induce severe mitochondrial dysfunction (Figure 7b,o) which, with 1-aminonaphtalene, led to an increased cytochrome C release (Figure 7c). Detection of increased caspase 3/7 activity provided evidence of apoptotic event upon chromium exposure. Oxidative stress induction (ROS or GSH) was also detected upon treatment with 1-aminonaphtalene, Crotonaldehyde and Phenol (Figure 7d,m,q). Finally, Arsenic induces cell stress as demonstrated by the increased phosphorylation of the transcription factor cJun (Figure 7g).
<img alt="Figure 1" src="/files/ftp_upload/53987/53987fig1.jpg" /> 
Figure 1. Compound Tox-Profiler Workflow. a) Schematic of the workflow followed in this study. First, a dose-range finding was performed using the RTCA platform to select appropriate doses for subsequent HCS to characterize the compound-specific toxicity profiles. b) Experimental design of the study. 24 hr after seeding, cells were dosed and impedance values continuously monitored over the following 24 hr, whereas HCS endpoints were investigated 4 and 24 hr after dosing. <a href="https://www.jove.com/files/ftp_upload/53987/53987fig1large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 2" src="/files/ftp_upload/53987/53987fig2.jpg" /> 
Figure 2. RTCA Exposure Plate. Compound master plate is first generated by performing a five-step 1:10 serial dilution. Each compound, including the vehicle control (dose 0) is then added in triplicate to the exposure plate together with medium and Staurosporine as controls. Note that the doses sequence is maintained upon transfer, highest doses are in row number 1 while vehicle controls are in row number 7. <a href="https://www.jove.com/files/ftp_upload/53987/53987fig2large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 3" src="/files/ftp_upload/53987/53987fig3.jpg" /> 
Figure 3. Representative RTCA Cell Viability Results. a) 1-aminonaphtalene, b) 2-nitropropane, c) Acetamide, d) Acetone, e) Acrylamide, f) Arsenic (V), g) Benzene, h) Chromium (VI), j) Crotonaldehyde, k) Methyl Ethyl Ketone, l) Nickel (II), m) Nitrobenzene, n) Phenol, o) Quinoline, p) Toluene. At 24 hr post-dosing, area under the curve (AUC) was calculated for each dose (including positive control and vehicle) and normalized in a range from 0 to -100% activity (y-axis), where 0 reflects the activity of the vehicle and -100 of the positive control. Values were then plotted and fitted using a four-parameter Hill equation and, when possible, LD50 was calculated. Concentrations are expressed on a log scale (x-axis). <a href="https://www.jove.com/files/ftp_upload/53987/53987fig3large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 4" src="/files/ftp_upload/53987/53987fig4.jpg" /> 
Figure 4. Dilution Scheme for Positive Control Compounds for HCS Assays. a) Addition of Positive controls and vehicle to the serial dilution plate. b) Serial dilution of the positive controls. c) 200X positive controls doses. d-e) Dilution of the 200x positive controls doses in medium (1:40) to generate the positive control plate containing the 5x doses. Note that each doses is diluted in triplicates to reflect the final layout in the exposure plate). <a href="https://www.jove.com/files/ftp_upload/53987/53987fig4large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 5" src="/files/ftp_upload/53987/53987fig5.jpg" /> 
Figure 5. HCS Exposure Plate. Compound master plate is first generated by performing a five-step dilution. Each compound, including the vehicle control (dose 0) is then added in triplicate to the exposure plate together with the positive controls. Note that the doses order is maintained upon transfer, highest doses are in row number 1 while vehicle controls are in row number 7. <a href="https://www.jove.com/files/ftp_upload/53987/53987fig5large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 6" src="/files/ftp_upload/53987/53987fig6.jpg" /> 
Figure 6. Representative Fluorescent Photos of Antibody- or Dye-Stained Cells. a) Nuclear parameters - Nuclear dye: A permeable dye which binds to DNA in live or fixed cells. This stain is used to identify individual cells labeling the nuclear region. b) Necrosis - Cell membrane permeability dye: Dye-based detection of cell membrane integrity. Reagent is intrinsically impermeable to the cell membrane. During necrosis, the membrane becomes permeable and the dye enters the cell and binds to DNA producing a strong fluorescent signal. c) Apoptosis - Cytochrome C: Antibody-based detection of cytochrome C release, a well-known hallmark of early apoptosis. Upon induction of apoptosis, cytochrome c is released from the mitochondria and diffuses into the nucleus. d) DNA Damage - pH2AX: Antibody-based detection of phosphorylation of histone H2AX, a well-known hallmark of double strand DNA breaks. e) Stress Kinase - cJun: Antibody-based detection of phosphorylation at Ser-73 of cJun, a well-known hallmark of cellular stress. f) Oxidative stress - DHE: Dye-based detection of superoxide radicals. Dihydroethidium itself fluoresces blue in the cytoplasm while the oxidized form ethidium fluoresces red upon DNA intercalation. g) GSH - mBcl: Dye-based detection of free GSH molecules. mBcl reacts with GSH to generate a highly fluorescent product. h) Apoptosis - Caspase 3/7 activation: Dye-based detection of caspase 3/7 activity. Reagent is non-fluorescent with a four amino acid peptide that inhibits DNA binding. Upon caspase-3/7 activation, the peptide is cleaved enabling the dye to bind to DNA and produce a bright, fluorogenic response. Panels b-h show positive control-treated cells. <a href="https://www.jove.com/files/ftp_upload/53987/53987fig6large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 7" src="/files/ftp_upload/53987/53987fig7.jpg" /> 
Figure 7. Representative HCS Results. 1-aminonaphtalene (a-e), Arsenic (V) (f and g), Chromium (VI) (h-k), Crotonaldehyde (l-n) and Phenol (o-q). 4 hr (blue line) and 24 hr (orange line) signals were calculated for each doses and normalized to the vehicle activity (0%). Values that are not included in curve fitting computations are shown in grey. Concentrations are expressed on a log scale (x-axis). <a href="https://www.jove.com/files/ftp_upload/53987/53987fig7large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>Assay</td>
			<td>Endpoint #</td>
			<td>Biological endpoint</td>
			<td>Cellular compartment</td>
			<td>Output feature</td>
		</tr>
		<tr>
			<td rowspan="4">Cytotoxicity</td>
			<td>1</td>
			<td>Mitochondrial mass 6</td>
			<td>Cytoplasm</td>
			<td>Spot average area</td>
		</tr>
		<tr>
			<td>2</td>
			<td>Mitochondrial membrane potential 6</td>
			<td>Cytoplasm</td>
			<td>Spot average intensity</td>
		</tr>
		<tr>
			<td>3</td>
			<td>Cytochrome C release 7</td>
			<td>Nucleus</td>
			<td>Average intensity</td>
		</tr>
		<tr>
			<td>4</td>
			<td>Cell membrane permeability 8</td>
			<td>Nucleus</td>
			<td>Average intensity</td>
		</tr>
		<tr>
			<td>DNA Damage</td>
			<td>5</td>
			<td>phospho-H2AX 9</td>
			<td>Nucleus</td>
			<td>Average intensity</td>
		</tr>
		<tr>
			<td>Stress Kinase</td>
			<td>6</td>
			<td>phospho-cJun10</td>
			<td>Nucleus</td>
			<td>Average intensity</td>
		</tr>
		<tr>
			<td>ROS</td>
			<td>7</td>
			<td>ROS 11</td>
			<td>Nucleus</td>
			<td>Average intensity</td>
		</tr>
		<tr>
			<td>GSH content</td>
			<td>8</td>
			<td>GSH 12</td>
			<td>Cytoplasm</td>
			<td>Spot average intensity</td>
		</tr>
		<tr>
			<td>Apoptosis</td>
			<td>9</td>
			<td>Caspase 313</td>
			<td>Cytoplasm</td>
			<td>Spot average intensity</td>
		</tr>
	</tbody>
</table>
Table 1. List of HCS assays and endpoints. 
<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td colspan="2"></td>
			<td rowspan="2">Vehicle</td>
			<td colspan="6" rowspan="2">RTCA doses (&#181;M)</td>
			<td rowspan="2">LD50</td>
			<td colspan="5">HCS doses</td>
		</tr>
		<tr>
			<td colspan="2"></td>
			<td colspan="4">Cell viability-selected (&#181;M)</td>
			<td>3R4F (nM)</td>
		</tr>
		<tr>
			<td colspan="2">1-Aminonaphtalene</td>
			<td>EtOH</td>
			<td>20,000</td>
			<td>2,000</td>
			<td>200</td>
			<td>20</td>
			<td>2</td>
			<td>0.2</td>
			<td>280 &#181;M</td>
			<td>2,000</td>
			<td>500</td>
			<td>200</td>
			<td>150</td>
			<td>0.27</td>
		</tr>
		<tr>
			<td colspan="2">2-Nitropropane</td>
			<td>EtOH</td>
			<td>20,000</td>
			<td>2,000</td>
			<td>200</td>
			<td>20</td>
			<td>2</td>
			<td>0.2</td>
			<td>&#62;20 mM</td>
			<td></td>
			<td></td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td colspan="2">Acetamide</td>
			<td>EtOH</td>
			<td>20,000</td>
			<td>2,000</td>
			<td>200</td>
			<td>20</td>
			<td>2</td>
			<td>0.2</td>
			<td>&#62;20 mM</td>
			<td></td>
			<td></td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td colspan="2">Acetone</td>
			<td>Water</td>
			<td>20,000</td>
			<td>2,000</td>
			<td>200</td>
			<td>20</td>
			<td>2</td>
			<td>0.2</td>
			<td>&#62;20 mM</td>
			<td></td>
			<td></td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td colspan="2">Acrylamide</td>
			<td>Water</td>
			<td>20,000</td>
			<td>2,000</td>
			<td>200</td>
			<td>20</td>
			<td>2</td>
			<td>0.2</td>
			<td>&#62;20 mM</td>
			<td></td>
			<td></td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td colspan="2">Arsenic (V)</td>
			<td>Water</td>
			<td>20,000</td>
			<td>2,000</td>
			<td>200</td>
			<td>20</td>
			<td>2</td>
			<td>0.2</td>
			<td>160 &#181;M</td>
			<td>200</td>
			<td>100</td>
			<td>50</td>
			<td>25</td>
			<td>0.17</td>
		</tr>
		<tr>
			<td colspan="2">Benzene</td>
			<td>EtOH</td>
			<td>20,000</td>
			<td>2,000</td>
			<td>200</td>
			<td>20</td>
			<td>2</td>
			<td>0.2</td>
			<td>&#62;20 mM</td>
			<td></td>
			<td></td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td colspan="2">Chromium (VI)</td>
			<td>Water</td>
			<td>20,000</td>
			<td>2,000</td>
			<td>200</td>
			<td>20</td>
			<td>2</td>
			<td>0.2</td>
			<td>20 &#181;M</td>
			<td>100</td>
			<td>50</td>
			<td>20</td>
			<td>10</td>
			<td>0.06</td>
		</tr>
		<tr>
			<td colspan="2">Crotonaldehyde</td>
			<td>Water</td>
			<td>20,000</td>
			<td>2,000</td>
			<td>200</td>
			<td>20</td>
			<td>2</td>
			<td>0.2</td>
			<td>200 &#181;M</td>
			<td>20,000</td>
			<td>2,000</td>
			<td>200</td>
			<td>20</td>
			<td>2,000</td>
		</tr>
		<tr>
			<td colspan="2">Methyl Ethyl Ketone</td>
			<td>Water</td>
			<td>20,000</td>
			<td>2,000</td>
			<td>200</td>
			<td>20</td>
			<td>2</td>
			<td>0.2</td>
			<td>&#62;20 mM</td>
			<td></td>
			<td></td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td colspan="2">Nickel</td>
			<td>Water</td>
			<td>20,000</td>
			<td>2,000</td>
			<td>200</td>
			<td>20</td>
			<td>2</td>
			<td>0.2</td>
			<td>&#62;20 mM</td>
			<td></td>
			<td></td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td colspan="2">Nitrobenzene</td>
			<td>EtOH</td>
			<td>20,000</td>
			<td>2,000</td>
			<td>200</td>
			<td>20</td>
			<td>2</td>
			<td>0.2</td>
			<td>&#62;20 mM</td>
			<td></td>
			<td></td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td colspan="2">Phenol</td>
			<td>EtOH</td>
			<td>20,000</td>
			<td>2,000</td>
			<td>200</td>
			<td>20</td>
			<td>2</td>
			<td>0.2</td>
			<td>2,300 &#181;M</td>
			<td>5,000</td>
			<td>2,000</td>
			<td>1,000</td>
			<td>500</td>
			<td>240</td>
		</tr>
		<tr>
			<td colspan="2">Quinoline</td>
			<td>EtOH</td>
			<td>20,000</td>
			<td>2,000</td>
			<td>200</td>
			<td>20</td>
			<td>2</td>
			<td>0.2</td>
			<td>&#62;20 mM</td>
			<td></td>
			<td></td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td colspan="2">Toluene</td>
			<td>Water</td>
			<td>20,000</td>
			<td>2,000</td>
			<td>200</td>
			<td>20</td>
			<td>2</td>
			<td>0.2</td>
			<td>&#62;20 mM</td>
			<td></td>
			<td></td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
	</tbody>
</table>
Table 2. List of Tested HPHC Compounds with Relative LD50 at 24 hr of Treatment. Compounds selected for HCS analysis are highlighted in orange and doses tested are also given. The 3R4F dose is equivalent to the amount of constituent present in the smoke of one stick from the reference cigarette 3R4F.
<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>Assay</td>
			<td>Compound</td>
			<td>Stock Solution</td>
			<td>Solvent</td>
			<td colspan="3">Dose(s) (&#181;M)</td>
		</tr>
		<tr>
			<td>Cell viability</td>
			<td>Staurosporine</td>
			<td>10 mM</td>
			<td>DMSO</td>
			<td colspan="3">50</td>
		</tr>
		<tr>
			<td>Cytotoxicity</td>
			<td>Valinomycin</td>
			<td>10 mM</td>
			<td>DMSO</td>
			<td>50</td>
			<td>20</td>
			<td>5</td>
		</tr>
		<tr>
			<td>DNA Damage</td>
			<td>Paraquat</td>
			<td>100 mM</td>
			<td>DMSO</td>
			<td>500</td>
			<td>200</td>
			<td>50</td>
		</tr>
		<tr>
			<td>Stress Kinase</td>
			<td>Anisomycin</td>
			<td>2 mM</td>
			<td>DMSO</td>
			<td>10</td>
			<td>4</td>
			<td>1</td>
		</tr>
		<tr>
			<td>ROS</td>
			<td>Rotenone</td>
			<td>200 mM</td>
			<td>DMSO</td>
			<td>1,000</td>
			<td>400</td>
			<td>100</td>
		</tr>
		<tr>
			<td>GSH content</td>
			<td>Ethacrynic acid</td>
			<td>200 mM</td>
			<td>DMSO</td>
			<td>1,000</td>
			<td>400</td>
			<td>100</td>
		</tr>
		<tr>
			<td>Apoptosis</td>
			<td>Staurosporine</td>
			<td>40 mM</td>
			<td>DMSO</td>
			<td>200</td>
			<td>50</td>
			<td>20</td>
		</tr>
	</tbody>
</table>
Table 3. List of Positive Controls and Concentrations Used for Each Assay.

Watch this Scientific Journal Video about High Content Screening Analysis to Evaluate the Toxicological Effects of Harmful and Potentially Harmful Constituents HPHC at JoVE.com

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Biology

12.1K Views.  Philip Morris International R&D. The objective of the study was to assess the biological impact of 15 cigarette smoke constituents using a combination of an impedance-based real time cell analyzer and a high-content screening (HCS)-based platform for toxicological assessment in vitro. This study provides information on effective doses, toxicity and modes of action of the tested compounds. 

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Increasing levels of compounds have been detected in the environment, causing widespread pollution and posing risks to human health. However, despite ...

High-Content Screening Assay for the Identification of Antibody-Dependent Cellular Cytotoxicity Modifying Compounds

Immunotherapy with antigen-specific antibodies or immune checkpoint inhibitors has revolutionized the therapy of breast cancer. Breast cancer cells expressing the epidermal growth factor receptor HER2 can be targeted by the anti-HER-2 antibody trastuzumab. Antibody-dependent cellular cytotoxicity (ADCC) is an important mechanism implicated in the antitumor action of HER-2. Trastuzumab bound to cancer cells can be recognized by the Fc receptors of ADCC effector cells (e.g., natural killer (NK) cells, macrophages, and granulocytes), triggering the cytotoxic activity of these immune cells leading to cancer cell death. We set out to develop an image-based assay for the quantification of ADCC to identify novel ADCC modulator compounds by high-content screening. In the assay, HER2 overexpressing JIMT-1 breast cancer cells are co-cultured with NK-92 cells in the presence of trastuzumab, and target cell death is quantified by automated microscopy and quantitative image analysis. Target cells are distinguished from effector cells based on their EGFP fluorescence. We show how compound libraries can be tested in the assay to identify ADCC modulator drugs. For this purpose, a compound library test plate was set up using randomly selected fine chemicals off the lab shelf. Three microtubule destabilizing compounds (colchicine, vincristine, podophyllotoxin) expected to interfere with NK cell migration and degranulation were also included in the test library. The test screen identified all three positive control compounds as hits proving the suitability of the method to identify ADCC-modifying drugs in a chemical library. With this assay, compound library screens can be performed to identify ADCC-enhancing compounds that could be used as adjuvant therapeutic agents for the treatment of patients receiving anticancer immunotherapies. In addition, the method can also be used to identify any undesirable ADCC-inhibiting side effects of therapeutic drugs taken by cancer patients for different indications.

This protocol presents an automated, image-based high-throughput technique to identify compounds modulating natural killer cell-mediated breast cancer cell killing in the presence of a therapeutic anti-HER-2 antibody.

Immunotherapy with antigen-specific antibodies or immune checkpoint inhibitors has revolutionized the therapy of breast cancer. Breast cancer cells ...

Cancer Research

Assessment of the Cytotoxic and Immunomodulatory Effects of Substances in Human Precision-cut Lung Slices

Respiratory diseases in their broad diversity need appropriate model systems to understand the underlying mechanisms and enable development of new therapeutics. Additionally, registration of new substances requires appropriate risk assessment with adequate testing systems to avoid the risk of individuals being harmed, for example, in the working environment. Such risk assessments are usually conducted in animal studies. In view of the 3Rs principle and public skepticism against animal experiments, human alternative methods, such as precision-cut lung slices (PCLS), have been evolving. The present paper describes the ex vivo technique of human PCLS to study the immunomodulatory potential of low-molecular-weight substances, such as ammonium hexachloroplatinate (HClPt). Measured endpoints include viability and local respiratory inflammation, marked by altered secretion of cytokines and chemokines. Pro-inflammatory cytokines, tumor necrosis factor alpha (TNF-&#945;), and interleukin 1 alpha (IL-1&#945;) were significantly increased in human PCLS after exposure to a sub-toxic concentration of HClPt. Even though the technique of PCLS has been substantially optimized over the past decades, its applicability for the testing of immunomodulation is still in development. Therefore, the results presented here are preliminary, even though they show the potential of human PCLS as a valuable tool in respiratory research.

In view of the 3Rs principle, respiratory models as alternatives to animal studies are evolving. Especially for risk assessment of respiratory substances, there is a lack of appropriate assays. Here, we describe the use of human precision-cut lung slices for the assessment of airborne substances.

Respiratory diseases in their broad diversity need appropriate model systems to understand the underlying mechanisms and enable development of new ...

Immunology and Infection

Evaluating MOF-Induced Cell Behavior Changes by Electric Cell-Substrate Sensing

Electric Cell-Substrate Sensing for Real-Time Evaluation of Metal-Organic Framework Toxicological Profiles

Metal-organic frameworks (MOFs) are hybrids formed through the coordination of metal ions and organic linkers in organic solvents. The implementation of MOFs in biomedical and industrial applications has led to concerns regarding their safety. Herein, the profile of a selected MOF, a zeolitic imidazole framework, was evaluated upon exposure to human lung epithelial cells. The platform for evaluation was a real-time technique (i.e., electric cell-substrate impedance sensing [ECIS]). This study identifies and discusses some of the deleterious effects of the selected MOF on the exposed cells. Furthermore, this study demonstrates the benefits of using the real-time method versus other biochemical assays for comprehensive cell evaluations. The study concludes that observed changes in cell behavior could hint at possible toxicity induced upon exposure&#160;to MOFs of different physicochemical characteristics and the dosage of those frameworks being used. By understanding changes in cell behavior, one foresees the ability to improve safe-by-design strategies of MOFs to be used for biomedical applications by specifically tailoring their physicochemical characteristics.

Author Spotlight: Advances in Evaluating Human Lung Epithelial Cells' Response to Metal-Organic Frameworks 

The following study evaluates the toxicological profile of a selected metal-organic framework utilizing electric cell-substrate impedance sensing (ECIS), a real-time, high-throughput screening technique.

Metal-organic frameworks (MOFs) are hybrids formed through the coordination of metal ions and organic linkers in organic solvents. The implementation of ...

Bioengineering

Assessment of the Acute Inhalation Toxicity of Airborne Particles by Exposing Cultivated Human Lung Cells at the Air-Liquid Interface

Here, we present a specially designed modular in vitro exposure system that enables the homogenous exposure of cultivated human lung cells at the ALI to gases, particles or complex atmospheres (e.g., cigarette smoke), thus providing realistic physiological exposure of the apical surface of the human alveolar region to air. In contrast to sequential exposure models with linear aerosol guidance, the modular design of the radial flow system meets all requirements for the continuous generation and transport of the test atmosphere to the cells, a homogenous distribution and deposition of the particles and the continuous removal of the atmosphere. This exposure method is primarily designed for the exposure of cells to airborne particles, but can be adapted to the exposure of liquid aerosols and highly toxic and aggressive gases depending on the aerosol generation method and the material of the exposure modules.
Within the framework of a recently completed validation study, this exposure system was proven as a transferable, reproducible and predictive screening method for the qualitative assessment of the acute pulmonary cytotoxicity of airborne particles, thereby potentially reducing or replacing animal experiments that would normally provide this toxicological assessment.

We present a robust, transferable and predictive in vitro exposure system for the screening and monitoring of airborne particles concerning their acute pulmonary cytotoxicity by exposing cultivated human lung cells at the air-liquid interface (ALI).

Here, we present a specially designed modular in vitro exposure system that enables the homogenous exposure of cultivated human lung cells at the ALI to ...

Medicine

High-throughput Screening for Chemical Modulators of Post-transcriptionally Regulated Genes

Both transcriptional and post-transcriptional regulation have a profound impact on genes expression. However, commonly adopted cell-based screening assays focus on transcriptional regulation, being essentially aimed at the identification of promoter-targeting molecules. As a result, post-transcriptional mechanisms are largely uncovered by gene expression targeted drug development. Here we describe a cell-based assay aimed at investigating the role of the 3&#39; untranslated region (3&#8217; UTR) in the modulation of the fate of its mRNA, and at identifying compounds able to modify it. The assay is based on the use of a luciferase reporter construct containing the 3&#8217; UTR of a gene of interest stably integrated into a disease-relevant cell line. The protocol is divided into two parts, with the initial focus on the primary screening aimed at the identification of molecules affecting luciferase activity after 24 hr of treatment. The second part of the protocol describes the counter-screening necessary to discriminate compounds modulating luciferase activity specifically through the 3&#8217; UTR. In addition to the detailed protocol and representative results, we provide important considerations about the assay development and the validation of the hit(s) on the endogenous target. The described cell-based reporter gene assay will allow scientists to identify molecules modulating protein levels via post-transcriptional mechanisms dependent on a 3&#8217; UTR.

Here we describe a cell-based reporter gene assay as a valuable tool to screen chemical libraries for compounds modulating post-transcriptional control mechanisms exerted through 3&#8217; UTR.

Both transcriptional and post-transcriptional regulation have a profound impact on genes expression. However, commonly adopted cell-based screening assays ...

High Content Screening Analysis to Evaluate the Toxicological Effects of Harmful and Potentially Harmful Constituents (HPHC)

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