This work was funded in part by the National Institute of General Medical Sciences (NIGMS) T32 program (T32 GM133369) and the National Science Foundation (NSF 1454230). Additionally, WVU Shared Research Facilities and Applied Biophysics assistance and support are acknowledged.

1. ZIF-8 synthesis
<ol>
	<li>For the purpose of this example, use a 1:10:100 (metal:linker:solvent) mass ratio to synthesize the ZIF-8. For this, measure out zinc nitrate hexahydrate, and record the measurement. Utilize the example mass ratio to calculate the amount needed for the linker, 2-methylimidazole, and the solvent (i.e., methanol).</li>
	<li>Place the zinc nitrate hexahydrate and linker into two different glass vials. Add half of the calculated amount of methanol to the zinc nitrate hexahydrate and the other half to the linker. Allow each solution to dissolve.</li>
	<li>Combine the two solutions (i.e., solutions containing the metal and linker, respectively). Place the container with the combined solution for the reaction onto a stir plate and stir at 700 rpm for 24 h at room temperature (RT).</li>
</ol>
2. ZIF-8 collection
<ol>
	<li>Once the above reaction has concluded (i.e., after 24 h), place the solution into 50 mL centrifuge tubes and centrifuge at 3,075 x g for 5 min (use equal amounts and balance the rotor). Remove any of the supernatants from the centrifuged tubes.</li>
	<li>Add methanol (5-15 mL) to the centrifuge tubes and redisperse the particles.</li>
	<li>Repeat the centrifugation and washing steps at least two to four more times. After the last wash, discharge the supernatant. 
	NOTE: The washing steps remove any non-precipitated species.</li>
	<li>Remove the lids of the tubes and place parafilm tape over the top; subsequently, poke holes in the parafilm. Place the tube/s containing the sample in a vacuum chamber at RT to dry for 24 h.</li>
</ol>
3. ZIF-8 surface morphology (scanning electron microscopy [SEM])
<ol>
	<li>Mount the dry powders of ZIF-8 onto carbon tape and sputter for 120 s with gold-palladium to prevent any charging that could occur during the SEM analysis.</li>
	<li>Set the accelerating voltage of the microscope to 15 kV. Bring the particles into focus and adjust the magnification (magnifications of 500x, 1,000x, 1,500x, 4,000x, 10,000x, 20,000x, 30,000x, and 40,000x were used.)</li>
	<li>Image the particles under the magnification that allows both a clear particle size and morphology assessment (recommended to consider ranges for particles of 5 &#181;m, 10 &#181;m, and 20 &#181;m).</li>
	<li>Collect data from at least three different fields of view, and for each, consider different magnifications.</li>
</ol>
4. ZIF-8 elemental composition
<ol>
	<li>Follow the steps for SEM imaging.</li>
	<li>Using the energy-dispersive X-ray (EDX) spectroscopy unit of the SEM microscope, analyze the sample elemental composition.</li>
	<li>Make sure the SEM accelerating voltage and magnification match the EDX monitor. Turn off the infrared camera on the SEM microscope.</li>
	<li>On the EDX monitor, go to Collect Spectrum and input a collection time of 200 s. This is recommended to avoid particle charging and disintegration that could lead to false evaluations.</li>
	<li>Collect data from at least three different fields of view. Once the collection is finished, analyze the data, and identify the elements of interest.</li>
</ol>
5. Cell culture
<ol>
	<li>Culture immortalized BEAS-2B cells in media supplemented with 5% fetal bovine serum (FBS) and 0.2% penicillin/streptomycin. 
	NOTE: Passages between 5-10 should be used to ensure that no phenotypical changes have previously taken place in the cell batch being used37 (all reagents are listed in the Table of Materials).</li>
	<li>Take a 100 mm cell culture plate and place 10 mL of the media onto the plate. Add 1 mL of the BEAS-2B cell solution to the plate.</li>
	<li>Place the plate into an incubator (37 &#176;C, 5% CO2) and allow the cells to grow.</li>
	<li>Check the plate after 24 h to determine if the cells have reached 80% confluency. Herein, the 80% confluency refers to the percentage of the surface covered by adhered cells. If not, change the media and allow the cells to grow until the 80% confluency level is reached.</li>
</ol>
6. Cell counting
<ol>
	<li>Once the cells on the plate have reached a confluency of 80%, remove the media from the plate. Wash the plate with 5 mL of phosphate-buffered saline (PBS).</li>
	<li>Remove the PBS from the plate. Add 2 mL of trypsin to the plate and place it in the incubator (37 &#176;C, 5% CO2) for 2 min.</li>
	<li>Add 2 mL of media to the plate and pipet the media up and down to remove the cells from the plate. Transfer the solution to a 15 mL tube and centrifuge at 123 x g for 5 min.</li>
	<li>Remove the supernatant from the tube and add 2 mL of media. Pipet the media up and down to redisperse the cells.</li>
	<li>Using a 1.5 mL tube, add 20 &#181;L of trypan blue and then 20 &#181;L of the cell solution (1:1 ratio of trypan blue:cell solution).</li>
	<li>Place 10 &#181;L of the cell mixture onto a glass slide and place it onto an automatic cell counter. Wait until the screen comes into focus, then select capture.</li>
	<li>The screen displays the live cell numbers and cell viability. The measurement range extends from 1 x 104-1 x 107 cells.</li>
	<li>Alternatively, count the cells manually using a hemocytometer.
	<ol>
		<li>For this, add 15-20 &#181;L of the trypan blue-treated cell solution to the hemocytometer.</li>
		<li>Use an upright microscope with a 10x objective focus on the grid lines of the hemocytometer.</li>
		<li>Count the number of cells in the four outer squares and divide the number by four. Then, multiply by 10,000 to obtain the live cell count number.</li>
		<li>To calculate cell viability, add together the live and dead cell count to obtain the total cell count, and subsequently divide the live cell count by the total cell count.</li>
	</ol>
	</li>
</ol>
7. ZIF-8 dose preparation
<ol>
	<li>Make a ZIF-8 stock solution of 1 mg/mL. For this, measure the amount of ZIF-8 and add deionized (DI) water to the particles to reach a 1 mg/mL concentration.</li>
	<li>Sonicate (set the sonicator to sonics) the ZIF-8 stock solution for 2 min at 30 s intervals in a water bath.</li>
	<li>Make different doses of ZIF-8 for cellular exposures by calculating the amount of stock solution and Dulbecco&#39;s modified eagle medium (DMEM) needed to reach the desired doses using the equation C1V1 = C2V2. The doses will range from 0-950 &#181;g/mL. 
	NOTE: In this experiment, doses of 0 &#181;g/mL, 1 &#181;g/mL, 10 &#181;g/mL, 50 &#181;g/mL, 100 &#181;g/mL, 250 &#181;g/mL, 500 &#181;g/mL, 750 &#181;g/mL, and 950 &#181;g/mL were selected.</li>
</ol>
8. Half-maximal inhibitory concentration (IC&#160;&#160;50)
<ol>
	<li>After cell counting, seed the BEAS-2B cells at a density of 4 x 104 cells/mL in a 96-well plate, with a volume of 100 &#181;L/well.
	<ol>
		<li>To reach a density of 4 x 104 cells/mL, use C1V1 = C2V2 to calculate the amount of cell solution needed to be combined with the media.</li>
		<li>Ensure to maintain blank wells for each dose; leave these wells empty until ZIF-8 exposure.</li>
	</ol>
	</li>
	<li>Place the 96-well plate into the incubator at 37 &#176;C and 5% CO2 and allow the cells to grow to a confluent monolayer for 24 h.</li>
	<li>Remove the media from the wells and expose the BEAS-2B cells to ZIF-8 doses ranging from 0-950 &#181;g/mL. Add 100 &#181;L of ZIF-8 to their respective blank and cell wells.</li>
	<li>Place the 96-well plates back into the incubator for an exposure time of 48 h.</li>
	<li>After the exposure, add 10 &#181;L of 4-[3-(4-idophenyl)-2-(4-nitrophenyl)-2H-5-tetrazolio]-1,3-benzene disulfonate (WST-1) to each well (blank and cell wells) and incubate for 2 h. The media remains in the wells; the ratio is 1:10 (reagent:media).</li>
	<li>Read the changes in absorbance on a plate reader using a 485 nm absorbance.</li>
	<li>Calculate the cell viability through the software to determine the IC50 value (see section 10).</li>
</ol>
9. Electrical cell-substrate impedance sensing (ECIS)
<ol>
	<li>Use a 96-well plate (96W10idf) to perform ECIS analysis. The plate28 contains inter-digitated finger connection electrodes covering an area of about 4 mm2.</li>
	<li>First, test that all the wells are being read by the sensors. For this, place the 96-well plate onto the well station and click on the Setup button.</li>
	<li>If the wells are connected properly, green will appear; any unconnected wells will be identified as red. If such a case arises, remove and reinsert the well plate and click the Setup button again, until all the wells offer viable green readings.</li>
	<li>Stabilize the electrodes for 40 min with 200 &#181;L of media per well to prevent potential drift. Add 200 &#181;L of media to each well being used and then place the 96-well plate onto the ECIS station. Click on Setup/Check to ensure the plate is properly connected. Click on Stabilize.</li>
	<li>Once stabilization is complete, remove the plate from the station and remove the media from each well.</li>
	<li>Seed the BEAS-2B cells at a density of 4 x 104 cells/mL, with a volume of 100 &#181;L per well, into the wells containing the cells and place the plate onto the ECIS station in the incubator.</li>
	<li>On the monitor, click on Check to determine that all the electrodes are read by the sensors on the station.</li>
	<li>Set up the time course measurement by selecting Multiple Freq/Time (MFT). The program will measure each well at seven different frequencies.</li>
	<li>Click Start and allow it to run for 24 h so the cells can form a confluent monolayer.</li>
	<li>After 24 h, the wells containing cells will show increased resistance on the monitor. This is an indicator that cells have attached to the electrodes.</li>
	<li>Press Pause on the monitor to stop the data collection.</li>
	<li>Make the ZIF-8 doses at, above, and below the calculated IC50 value by following the steps outlined in section 7 above.</li>
	<li>Expose the ZIF-8 nanoparticles to their respective blank and cell wells at a volume of 100 &#181;L per well and place the 96-well plate back onto the station.</li>
	<li>Click on Check again on the monitor to ensure the sensors are reading all the electrodes. Click on Resume and allow the system to run for 72 h to monitor the cellular behavior and attachment.</li>
	<li>Once data collection has finished, click on Finish on the monitor. To save the file, click File &#62; Save As. Save the data as a spreadsheet file.</li>
	<li>To get the alpha parameters, click on Model. On the screen pop-up, click on Media-Only Well, then select the well that has only media.</li>
	<li>Click on Set Ref. On the monitor, click on Find.</li>
	<li>If the well shown in the system is not the same as what was chosen, repeat step 9.16.</li>
	<li>Click on Set. Click on Fit T-Range to determine the time range desired for data collection.</li>
	<li>While it is processing, click on Alpha. When the system finishes the analysis, click on Save RbA and save it as a spreadsheet file. 
	NOTE: Refer to the ECIS manual, which can be found on the manufacturer&#39;s website38.</li>
</ol>
10. Data analysis
<ol>
	<li>SEM
	<ol>
		<li>Open the imaging software to analyze the SEM images. Click File &#62; Open, and then select the image to analyze.</li>
		<li>Click on Image &#62; Type &#62; 8 Bits to convert the image to grayscale to perform the threshold operation.</li>
		<li>Calibrate the distance measurement of pixels to microns. Click on the Straight-Line tool and trace the length of each particle aimed to be measured.</li>
		<li>Click Analyze and then Set Scale. The known distance will be set to the length of the size of the scale bar on the SEM image. The known unit of length will be set to microns. Check Global and press Ok.</li>
		<li>Click on the Straight-Line tool and trace the diameter of the particle, then select Analyze and Measure. Record the length result.</li>
		<li>Repeat for all the collected images. Average all the diameters from at least 60 particles for a suitable statistics evaluation.</li>
	</ol>
	</li>
	<li>EDX
	<ol>
		<li>Average all the weight percentages of each element together from all the collected images (see EDX section above).</li>
		<li>Using a spreadsheet, plot a bar graph of each element on the x-axis and their average elemental weight percentage on the y-axis.</li>
	</ol>
	</li>
	<li>IC50&#8203;
	<ol>
		<li>Average the blank wells and average the dose wells for each replicate.</li>
		<li>Calculate the adjusted blank by subtracting the control blank average from the dose blank average. Calculate the true cell value for each dose by subtracting the adjusted blank from the average dose value.</li>
		<li>Subtract the adjusted blank value for each dose from the average control value. Calculate the cell viability of each dose utilizing the equation: cell viability = (true cell value/(control value - adjusted blank value)) x 100.</li>
		<li>Repeat this for all other replicates.</li>
		<li>Average the cell viability for each replicate together to get the final cell viability for each dose.</li>
		<li>In the software, choose the XY tab on the screen.</li>
		<li>Enter the concentration (dose) values into the X column and the cell viability (%) from each dose into the Y column.</li>
		<li>Transform the X values by clicking Analyze &#62; Transform &#62; Ok, and Transform X = Log(X).</li>
		<li>Normalize the Y values by selecting the Transformed Data sheet, clicking on Analyze, and then selecting Normalize.</li>
		<li>Select the Normalize of Transform data sheet, click Analyze, and select Nonlinear Regression (Curve Fit). Select Dose-Response-Inhibition and click Log(Inhibitor) Vs. Response-Variable Slope (Four Parameters). Click on OK to view the results.</li>
	</ol>
	</li>
	<li>ECIS
	<ol>
		<li>From the spreadsheet, take the resistance (ohm) columns for each replicate (blank wells and dose wells) and average them together from the 4,000 Hz frequency. This frequency allows cell-cell contact evaluation38.</li>
		<li>Calculate the corrected resistance by subtracting the averaged blank from the averaged dose for each replicate. Average the corrected resistance for the replicates for each dose.</li>
		<li>Repeat the same steps for the alpha values to calculate the average alpha parameter. Plot the x-axis as time (h) and the y-axis as the average resistance/alpha values for each dose value.</li>
	</ol>
	</li>
</ol>
11. Statistical analysis
<ol>
	<li>SEM
	<ol>
		<li>Perform a standard deviation in the spreadsheet file where the average diameters of the ZIF-8 particles were calculated.</li>
		<li>Utilizing the STDEV function in the spreadsheet, highlight the data of the 60 particles and click Enter. Graph the standard deviation for each average diameter calculated.</li>
	</ol>
	</li>
	<li>EDX
	<ol>
		<li>Similar to SEM (steps 11.1.1-11.1.2), calculate the standard deviation for each average elemental composition using the STDEV function in the spreadsheet. Graph the standard deviations for each average elemental composition.</li>
	</ol>
	</li>
	<li>IC50&#8203;
	<ol>
		<li>Open the software utilized to calculate the IC50 and click on Grouped Data Sheet.</li>
		<li>Enter the ZIF-8 doses in the rows labeled Group A, Group B, etc. Enter the average cell viability for each dose and replicate in the column corresponding with the ZIF-8 dose.</li>
		<li>Click on Analyze, and under Column Analyses, select One-way ANOVA (and nonparametric or mixed).</li>
		<li>In the Experimental Design tab, select No Matching Or Pairing. Under Gaussian Distribution Of Residuals, select Yes use ANOVA. Finally, select Yes Use Ordinary ANOVA Test under Assume Equal SDs.</li>
		<li>Under the Multiple Comparisons tab, select Compare the Mean of Each Column with the Mean of a Control Column. Click on OK to view the results.</li>
	</ol>
	</li>
</ol>

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

The authors report no conflicts of interest in this work.

Previous analysis showed that ECIS could be used to assess the behavior of cells exposed to analytes (i.e., carbon nanotubes35, drugs43, or nanoclays16). Furthermore, Stueckle et al. used ECIS to evaluate the toxicity of BEAS-2B cells exposed to nanoclays and their byproducts and found that the cellular behavior and attachment were dependent on the physicochemical characteristics of such materials42. Herein, we proposed to det...

Metal-organic frameworks (MOFs) are hybrids formed through the combination of metal ions and organic linkers1,2 in organic solvents. Due to the variety of such combinations, MOFs possess structural diversity3, tunable porosity, high thermal stability, and high surface areas4,5. Such characteristics make them attractive candidates in a variety of applications, from gas storage6,7 to catalysis8,9, and from contrast agents10,11 to drug delivery units12,13. However, the implementation of MOFs into such applications has raised concerns relative to their safety to both the users and the environment. Preliminary studies have shown, for instance, that cellular function and growth change upon the exposure of cells to metal ions or linkers used for MOF synthesis1,14,15. For instance, Tamames-Tabar et al. demonstrated that ZIF-8 MOF, a Zn-based MOF, was leading to more cellular changes in a human cervical cancer cell line (HeLa) and a mouse macrophage cell line (J774) relative to Zr-based and Fe-based MOFs. Such effects were&#160;presumably due to the metal component of ZIF-8 (i.e., Zn), which could potentially induce cell apoptosis upon framework disintegration and Zn ion release1. Similarly, Gandara-Loe et al. demonstrated that HKUST-1, a Cu-based MOF, caused the highest reduction in mouse retinoblastoma cell viability when used at concentrations of 10 &#181;g/mL or greater. This was presumably due to the Cu metal ion incorporated during the synthesis of this framework, which, once released, could induce oxidative stress in the exposed cells15.
Moreover, analysis showed that the exposure&#160;to MOFs with different physicochemical characteristics could lead to varying responses of exposed cells. For instance, Wagner et al. demonstrated that ZIF-8 and MIL-160 (an Al-based framework), used in the exposure of an immortalized human bronchial epithelial cell, led to cellular responses dependent on frameworks&#39; physicochemical properties, namely hydrophobicity, size, and structural characteristics16. Complementarily, Chen et al. demonstrated that a concentration of 160 &#181;g/mL MIL-100(Fe) exposed to human normal liver cells (HL-7702) caused the largest loss in cellular viability, presumably due to the metal component of this specific framework (i.e., Fe17).
While these studies categorize MOFs&#39; deleterious effects on cellular systems based on their physicochemical characteristics and exposure concentrations, thus raising potential concerns with framework implementation, especially in biomedical fields, most of these evaluations are based on single time point colorimetric assays. For instance, it was shown that when (3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide) tetrazolium (MTT) and water-soluble tetrazolium salt (WST-1) assays were used, these biochemical reagents could lead to false positives upon&#160;their&#160;interactions with the particles that the cells were also exposed to18. The tetrazolium salt and neutral red reagents were&#160;shown to possess a high adsorption or binding affinity onto the surfaces of the particles, resulting to agent signal interference19. Moreover, for other types of assays, such as flow cytometry, which was previously shown to be used for assessing changes in cells exposed to MOFs20,21, it was shown that major issues have to be circumvented if a viable analysis of particles&#39; deleterious effects is to be considered. In particular, detection ranges of the particles&#39; sizes, especially in mixed populations like the ones offered by MOFs or references of the particles used for calibration before cellular changes, have to be addressed22. It was also shown that the dye used during cell labeling for such cytometry assays could also interfere with the nanoparticles that the cells were exposed to23.
The goal of this study was to use a real-time, high-throughput evaluation assay to assess changes in cell behavior upon exposure to a select MOF. Real-time evaluations can help provide insights into time-dependent effects, as related to the windows of exposures16. Further, they provide information on changes in cell-substrate interactions, cell morphology, and cell-cell interactions, as well as how such changes depend on the physicochemical properties of the materials of interest and exposure times24,25 respectively.
To demonstrate the validity and applicability of the proposed approach, human bronchial epithelial (BEAS-2B) cells, ZIF-8 (a hydrophobic framework of zeolitic imidazolate16), and electric cell-substrate impedance sensing (ECIS) were used. BEAS-2B cells represent a model for lung exposure26 and have been previously used to evaluate changes upon the exposure of cells to nanoclays and their thermally degraded byproducts26,27,28,&#160;as well as assess the toxicity of nanomaterials, such as single-walled carbon nanotubes (SWCNTs)18. Furthermore, such cells have been used for more than 30 years as a model for pulmonary epithelial function29. ZIF-8 was chosen due to its wide implementation&#160;in catalysis30 and as contrast agents31 for bioimaging and drug delivery32, and thus for the extended potential for lung exposure during such applications. Lastly, ECIS, the noninvasive, real-time technique, was previously used to evaluate changes in cell adherence, proliferation, motility, and morphology16,26 as a result of a variety of interactions between analytes (both materials and drugs) and exposed cells in real-time16,18,28. ECIS uses an alternating current (AC) to measure the impedance of cells immobilized on gold electrodes, with the impedance changes giving insights into changes in resistance and capacitance at the&#160;cell-gold substrate interface, barrier function as induced by cell-cell interactions, and over-cell layer coverage of such gold electrodes33,34. Using ECIS allows quantitative measurements at a nanoscale resolution in a noninvasive, real-time manner26,34.
This study assesses and compares the simplicity and ease of evaluation of MOF-induced changes in cellular behavior in real-time with single-point assay evaluations. Such a study could be further extrapolated for evaluating cell profiles in response to exposure to other particles of interest, thus allowing for safe-by-design particle testing and subsequent helping with&#160;implementation. Moreover, this study could complement genetic and cellular assays that are single-point evaluations. This could lead to a more informed analysis of the deleterious effects of particles on the cellular population and could be used for screening such particles&#39; toxicity in a high-throughput manner16,35,36.

<table><tbody><tr><td>&amp;nbsp;4-[3-(4-idophenyl)-2-(4-nitrophenyl)-2H-5-tetrazolio]-1,3-benzene disulfonate (WST-1 assay)&amp;nbsp;</td><td>Roche</td><td>5015944001</td><td></td></tr><tr><td>0.25% Trypsin-EDTA (1x)</td><td>Gibco</td><td>25255-056</td><td></td></tr><tr><td>100 mm plates</td><td>Corning</td><td>430167</td><td></td></tr><tr><td>1300 Series A2 biofume hood</td><td>Thermo Scientific</td><td>323TS</td><td></td></tr><tr><td>2510 Branson bath sonicator</td><td>Process Equipment &amp;amp; Supply, Inc.&amp;nbsp;</td><td>251OR-DTH</td><td></td></tr><tr><td>2-methylimidazole, 97%</td><td>Alfa Aesar</td><td>693-98-1</td><td></td></tr><tr><td>5 mL sterile microtube</td><td>Argos Technologies</td><td>T2076S-CA</td><td></td></tr><tr><td>50 mL&amp;nbsp; tubes&amp;nbsp;</td><td>Falcon</td><td>352098</td><td></td></tr><tr><td>96W10idf well plates</td><td>Applied Biophysics&amp;nbsp;</td><td>96W10idf PET</td><td></td></tr><tr><td>96-well plates</td><td>Fisherbrand</td><td>FB012931</td><td></td></tr><tr><td>Biorender</td><td>Biorender</td><td>N/A</td><td></td></tr><tr><td>Countess cell counting chamber slides</td><td>Invitrogen</td><td>C10283</td><td></td></tr><tr><td>Countess II FL automated cell counter</td><td>Life Technologies</td><td>C0916-186A-0303</td><td></td></tr><tr><td>Denton Desk V sputter and carbon coater</td><td>Denton Vacuum</td><td>N/A</td><td></td></tr><tr><td>Dimethly sulfoxide&amp;nbsp;</td><td>Corning</td><td>25-950-CQC</td><td></td></tr><tr><td>DPBS/Modified</td><td>Cytiva</td><td>SH30028.02</td><td></td></tr><tr><td>Dulbecco&#039;s modified Eagle medium</td><td>Corning</td><td>10-014-CV</td><td></td></tr><tr><td>ECIS-Z&amp;Theta;</td><td>Applied Biophysics&amp;nbsp;</td><td>ABP 1129</td><td></td></tr><tr><td>Excel</td><td>Microsoft</td><td>Version 2301</td><td></td></tr><tr><td>Falcon tubes (15 mL)</td><td>Corning</td><td>352196</td><td></td></tr><tr><td>Fetal bovine serum</td><td>Gibco</td><td>16140-071</td><td></td></tr><tr><td>FLUOstar OPTIMA plate reader</td><td>BMG LABTECH</td><td>413-2132</td><td></td></tr><tr><td>GraphPad Prism Software (9.0.0)</td><td>GraphPad Software, LLC</td><td>Version 9.0.0</td><td></td></tr><tr><td>HERAcell 150i CO&lt;sub&gt;2&lt;/sub&gt; Incubator</td><td>Thermo Scientific</td><td>50116047</td><td></td></tr><tr><td>Hitachi S-4700 Field emission scanning electron microscope equipped with energy dispersive X-ray&amp;nbsp;</td><td>Hitachi High-Technologies Corporation</td><td>S4700 and EDAX TEAM analysis software</td><td></td></tr><tr><td>ImageJ software</td><td>National Institutes of Health</td><td>N/A</td><td></td></tr><tr><td>Immortalized human bronchial epithelial cells</td><td>American Type Culture Collection</td><td>CRL-9609</td><td></td></tr><tr><td>Isotemp freezer</td><td>Fisher Scientific&amp;nbsp;</td><td></td><td></td></tr><tr><td>Methanol, 99%</td><td>Fisher Chemical</td><td>67-56-1</td><td></td></tr><tr><td>Parafilm sealing film</td><td>The Lab Depot</td><td>HS234526A</td><td></td></tr><tr><td>Penicillin/Steptomycin</td><td>Gibco</td><td>15140-122</td><td></td></tr><tr><td>Sorvall Legend X1R Centrifuge&amp;nbsp;</td><td>Thermo Scientific</td><td>75004220</td><td></td></tr><tr><td>Sorvall T 6000B</td><td>DU PONT</td><td>&amp;nbsp;T6000B</td><td></td></tr><tr><td>Trypan blue, 0.4% solution in PBS</td><td>MP Biomedicals, LLC</td><td>1691049</td><td></td></tr><tr><td>Vacuum Chamber</td><td>Belart</td><td>999320237</td><td></td></tr><tr><td>Zinc Nitrate Hexahydrate, 98% extra pure</td><td>Acros Organic</td><td>101-96-18-9</td><td></td></tr></tbody></table>

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.

Using a common in vitro model cell line39 (BEAS-2B), this study aimed to demonstrate the feasibility and applicability of ECIS to assess changes in cell behavior upon exposure to a lab-synthesized MOF. These changes assessment was&#160;complemented by analysis through&#160;conventional colorimetric assays.
The physicochemical characteristics of the framework were first evaluated to ensure the reproducibility of the methods employed, the validity of the obtained...

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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.

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 ...

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Bioengineering

899 Views.  West Virginia University. 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. 

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

Preparation and Testing of Impedance-based Fluidic Biochips with RTgill-W1 Cells for Rapid Evaluation of Drinking Water Samples for Toxicity

This manuscript describes how to prepare fluidic biochips with Rainbow trout gill epithelial (RTgill-W1) cells for use in a field portable water toxicity sensor. A monolayer of RTgill-W1 cells forms on the sensing electrodes enclosed within the biochips. The biochips are then used for testing in a field portable electric cell-substrate impedance sensing (ECIS) device designed for rapid toxicity testing of drinking water. The manuscript further describes how to run a toxicity test using the prepared biochips. A control water sample and the test water sample are mixed with pre-measured powdered media and injected into separate channels of the biochip. Impedance readings from the sensing electrodes in each of the biochip channels are measured and compared by an automated statistical software program. The screen on the ECIS instrument will indicate either "Contamination Detected" or "No Contamination Detected" within an hour of sample injection. Advantages are ease of use and rapid response to a broad spectrum of inorganic and organic chemicals at concentrations that are relevant to human health concerns, as well as the long-term stability of stored biochips in a ready state for testing. Limitations are the requirement for cold storage of the biochips and limited sensitivity to cholinesterase-inhibiting pesticides. Applications for this toxicity detector are for rapid field-portable testing of drinking water supplies by Army Preventative Medicine personnel or for use at municipal water treatment facilities.

This manuscript describes how to prepare fluidic biochips with Rainbow trout gill epithelial cells for use in a field portable electric cell-substrate impedance sensor. The protocol for running a rapid drinking water toxicity test with the sensor is also described.

This manuscript describes how to prepare fluidic biochips with Rainbow trout gill epithelial (RTgill-W1) cells for use in a field portable water toxicity ...

Environment

Imaging Approaches to Assessments of Toxicological Oxidative Stress Using Genetically-encoded Fluorogenic Sensors

While oxidative stress is a commonly cited toxicological mechanism, conventional methods to study it suffer from a number of shortcomings, including destruction of the sample, introduction of potential artifacts, and a lack of specificity for the reactive species involved. Thus, there is a current need in the field of toxicology for non-destructive, sensitive, and specific methods that can be used to observe and quantify intracellular redox perturbations, more commonly referred to as oxidative stress. Here, we present a method for the use of two genetically-encoded fluorogenic sensors, roGFP2 and HyPer, to be used in live-cell imaging studies to observe xenobiotic-induced oxidative responses. roGFP2 equilibrates with the glutathione redox potential (EGSH), while HyPer directly detects hydrogen peroxide (H2O2). Both sensors can be expressed into various cell types via transfection or transduction, and can be targeted to specific cellular compartments. Most importantly, live-cell microscopy using these sensors offers high spatial and temporal resolution that is not possible using conventional methods. Changes in the fluorescence intensity monitored at 510 nm serves as the readout for both genetically-encoded fluorogenic sensors when sequentially excited by 404 nm and 488 nm light. This property makes both sensors ratiometric, eliminating common microscopy artifacts and correcting for differences in sensor expression between cells. This methodology can be applied across a variety of fluorometric platforms capable of exciting and collecting emissions at the prescribed wavelengths, making it suitable for use with confocal imaging systems, conventional wide-field microscopy, and plate readers. Both genetically-encoded fluorogenic sensors have been used in a variety of cell types and toxicological studies to monitor cellular EGSH and H2O2 generation in real-time. Outlined here is a standardized method that is widely adaptable across cell types and fluorometric platforms for the application of roGFP2 and HyPer in live-cell toxicological assessments of oxidative stress.

This manuscript describes the use of genetically-encoded fluorogenic reporters in an application of live-cell imaging for the examination of xenobiotic-induced oxidative stress. This experimental approach offers unparalleled spatiotemporal resolution, sensitivity, and specificity while avoiding many of the shortcomings of conventional methods used for the detection of toxicological oxidative stress.

While oxidative stress is a commonly cited toxicological mechanism, conventional methods to study it suffer from a number of shortcomings, including ...

Cancer Research

Regeneration of Arrayed Gold Microelectrodes Equipped for a Real-Time Cell Analyzer

The label-free cell-based assay is advantageous for biochemical study because of it does not require the use of experimental animals. Due to its ability to provide more dynamic information about cells under physiological conditions than classical biochemical assays, this label-free real-time cell assay based on the electric impedance principle is attracting more attention during the past decade. However, its practical utilization may be limited due to the relatively expensive cost of measurement, in which costly consumable disposable gold microchips are used for the cell analyzer. In this protocol, we have developed a general strategy to regenerate arrayed gold microelectrodes equipped for a commercial label-free cell analyzer. The regeneration process includes trypsin digestion, rinsing with ethanol and water, and a spinning step. The proposed method has been tested and shown to be effective for the regeneration and repeated usage of commercial electronic plates at least three times, which will help researchers save on the high running cost of real-time cell assays.

This protocol describes a general strategy to regenerate commercial arrayed gold microelectrodes equipped for a label-free cell analyzer aimed at saving on the high running costs ofmicrochip-based assays. The regeneration process includes trypsin digestion, rinsing with ethanol and water, and a spinning step, which enables repeated usage of microchips.

The label-free cell-based assay is advantageous for biochemical study because of it does not require the use of experimental animals. Due to its ability ...

Biochemistry

Sensing of Barrier Tissue Disruption with an Organic Electrochemical Transistor

The gastrointestinal tract is an example of barrier tissue that provides a physical barrier against entry of pathogens and toxins, while allowing the passage of necessary ions and molecules. A breach in this barrier can be caused by a reduction in the extracellular calcium concentration. This reduction in calcium concentration causes a conformational change in proteins involved in the sealing of the barrier, leading to an increase of the paracellular flux. To mimic this effect the calcium chelator ethylene glycol-bis(beta-aminoethyl ether)-N,N,N&#39;,N&#39;-tetra acetic acid (EGTA) was used on a monolayer of cells known to be representative of the gastrointestinal tract. Different methods to detect the disruption of the barrier tissue already exist, such as immunofluorescence and&#160;permeability assays. However, these methods are time-consuming and costly and not suited to dynamic or high-throughput measurements. Electronic methods for measuring barrier tissue integrity also exist for measurement of the transepithelial resistance (TER), however these are often costly and complex. The development of rapid, cheap, and sensitive methods is urgently needed as the integrity of barrier tissue is a key parameter in drug discovery and pathogen/toxin diagnostics. The organic electrochemical transistor (OECT) integrated with barrier tissue forming cells has been shown as a new device capable of dynamically monitoring barrier tissue integrity. The device is able to measure minute variations in ionic flux with unprecedented temporal resolution and sensitivity, in real time, as an indicator of barrier tissue integrity. This new method is based on a simple device that can be compatible with high throughput screening applications and fabricated at low cost.

The Organic Electrochemical Transistor is integrated with live cells and used to monitor ion flux across the gastrointestinal epithelial barrier. In this study, an increase in ion flux, related to disruption of tight junctions, induced by the presence of the calcium chelator EGTA (ethylene glycol-bis(beta-aminoethyl ether)-N,N,N',N'-tetra acetic acid), is measured.

The gastrointestinal tract is an example of barrier tissue that provides a physical barrier against entry of pathogens and toxins, while allowing the ...

A High-throughput Assay for the Prediction of Chemical Toxicity by Automated Phenotypic Profiling of Caenorhabditis elegans

Applying toxicity testing of chemicals in higher order organisms, such as mice or rats, is time-consuming and expensive, due to their long lifespan and maintenance issues. On the contrary, the nematode Caenorhabditis elegans (C. elegans) has advantages to make it an ideal choice for toxicity testing: a short lifespan, easy cultivation, and efficient reproduction. Here, we describe a protocol for the automatic phenotypic profiling of C. elegans in a 384-well plate. The nematode worms are cultured in a 384-well plate with liquid medium and chemical treatment, and videos are taken of each well to quantify the chemical influence on 33 worm features. Experimental results demonstrate that the quantified phenotype features can classify and predict the acute toxicity for different chemical compounds and establish a priority list for further traditional chemical toxicity assessment tests in a rodent model.

A High-throughput Assay for the Prediction of Chemical Toxicity by Automated Phenotypic Profiling of Caenorhabditis elegans

A quantitative method has been developed to identify and predict the acute toxicity of chemicals by automatically analyzing the phenotypic profiling of Caenorhabditis elegans. This protocol describes how to treat worms with chemicals in a 384-well plate, capture videos, and quantify toxicological related phenotypes.

Applying toxicity testing of chemicals in higher order organisms, such as mice or rats, is time-consuming and expensive, due to their long lifespan and ...

Real-Time Impedance-based Cell Analyzer as a Tool to Delineate Molecular Pathways Involved in Neurotoxicity and Neuroprotection in a Neuronal Cell Line

Many brain-related disorders have neuronal cell death involved in their pathophysiology. Improved in vitro models to study neuroprotective or neurotoxic effects of drugs and downstream pathways involved would help gain insight into the molecular mechanisms of neuroprotection/neurotoxicity and could potentially facilitate drug development. However, many existing in vitro toxicity assays have major limitations &#8211; most assess neurotoxicity and neuroprotection at a single time point, not allowing to observe the time-course and kinetics of the effect. Furthermore, the opportunity to collect information about downstream signaling pathways involved in neuroprotection in real-time would be of great importance. In the current protocol we describe the use of a real-time impedance-based cell analyzer to determine neuroprotective effects of serotonin 2A (5-HT2A) receptor agonists in a neuronal cell line under label-free and real-time conditions using impedance measurements. Furthermore, we demonstrate that inhibitors of second messenger pathways can be used to delineate downstream molecules involved in the neuroprotective effect. We also describe the utility of this technique to determine whether an effect on cell proliferation contributes to an observed neuroprotective effect. The system utilizes special microelectronic plates referred to as E-Plates which contain alternating gold microelectrode arrays on the bottom surface of the wells, serving as cell sensors. The impedance readout is modified by the number of adherent cells, cell viability, morphology, and adhesion. A dimensionless parameter called Cell Index is derived from the electrical impedance measurements and is used to represent the cell status. Overall, the real-time impedance-based cell analyzer allows for real-time, label-free assessment of neuroprotection and neurotoxicity, and the evaluation of second messenger pathways involvement, contributing to more detailed and high-throughput assessment of potential neuroprotective compounds in vitro, for selecting therapeutic candidates.

Improved in vitro neurotoxicity assays would aid the identification of new neuroprotective compounds. The utility of a real-time impedance-based cell analyzer to determine cytotoxicity and cytoprotection in neuronal cell lines and to delineate the involvement of second messenger pathways, thus gaining insight in the mechanism of neuroprotection is presented.

Many brain-related disorders have neuronal cell death involved in their pathophysiology. Improved in vitro models to study neuroprotective or neurotoxic ...

Neuroscience

Magnetometric Characterization of Redox-Active MOFs Solid-State Electrochemistry

Magnetometric Characterization of Intermediates in the Solid-State Electrochemistry of Redox-Active Metal-Organic Frameworks

Electrochemical energy storage has been a widely discussed application of redox-active metal-organic frameworks (MOFs) in the past 5 years. Although MOFs show outstanding performance in terms of gravimetric or areal capacitance and cyclic stability, unfortunately their electrochemical mechanisms are not well understood in most cases. Traditional spectroscopic techniques, such as X-ray photoelectron spectroscopy (XPS) and X-ray absorption fine structure (XAFS), have only provided vague and qualitative information about valence changes of certain elements, and the mechanisms proposed based on such information are often highly disputable. In this article, we report a series of standardized methods, including the fabrication of solid-state electrochemical cells, electrochemistry measurements, the disassembly of cells, the collection of MOF electrochemical intermediates, and physical measurements of the intermediates under the protection of inert gases. By using these methods for quantitatively clarifying the electronic and spin state evolution within a single electrochemical step of redox-active MOFs, one can provide clear insight into the nature of electrochemical energy storage mechanisms not only for MOFs, but also for all other materials with strongly correlated electronic structures.

Author Spotlight: Magnetometric Characterization of Intermediates in the Solid-State Electrochemistry of Redox-Active Metal-Organic Frameworks  

Ex situ magnetic surveys can directly provide bulk and local information on a magnetic electrode to reveal its charge storage mechanism step by step. Herein, electron spin resonance (ESR) and magnetic susceptibility are demonstrated to monitor the evaluation of paramagnetic species and their concentration in a redox-active metal-organic framework (MOF).

Electrochemical energy storage has been a widely discussed application of redox-active metal-organic frameworks (MOFs) in the past 5 years. Although MOFs ...

Chemistry

High Throughput, Real-time, Dual-readout Testing of Intracellular Antimicrobial Activity and Eukaryotic Cell Cytotoxicity

Traditional measures of intracellular antimicrobial activity and eukaryotic cell cytotoxicity rely on endpoint assays. Such endpoint assays require several additional experimental steps prior to readout, such as cell lysis, colony forming unit determination, or reagent addition. When performing thousands of assays, for example, during high-throughput screening, the downstream effort required for these types of assays is considerable. Therefore, to facilitate high-throughput antimicrobial discovery, we developed a real-time assay to simultaneously identify inhibitors of intracellular bacterial growth and assess eukaryotic cell cytotoxicity. Specifically, real-time intracellular bacterial growth detection was enabled by marking bacterial screening strains with either a bacterial lux operon (1st generation assay) or fluorescent protein reporters (2nd generation, orthogonal assay). A non-toxic, cell membrane-impermeant, nucleic acid-binding dye was also added during initial infection of macrophages. These dyes are excluded from viable cells. However, non-viable host cells lose membrane integrity permitting entry and fluorescent labeling of nuclear DNA (deoxyribonucleic acid). Notably, DNA binding is associated with a large increase in fluorescent quantum yield that provides a solution-based readout of host cell death. We have used this combined assay to perform a high-throughput screen in microplate format, and to assess intracellular growth and cytotoxicity by microscopy. Notably, antimicrobials may demonstrate synergy in which the combined effect of two or more antimicrobials when applied together is greater than when applied separately. Testing for in vitro synergy against intracellular pathogens is normally a prodigious task as combinatorial permutations of antibiotics at different concentrations must be assessed. However, we found that our real-time assay combined with automated, digital dispensing technology permitted facile synergy testing. Using these approaches, we were able to systematically survey action of a large number of antimicrobials alone and in combination against the intracellular pathogen, Legionella pneumophila.

A high throughput, real-time assay was developed to simultaneously identify (1) eukaryotic cell-penetrant antimicrobials targeting an intracellular bacterial pathogen, and (2) assess eukaryotic cell cytotoxicity. A variation on the same technology was thereafter combined with digital dispensing technology to enable facile, high-resolution, dose-response, and two- and three-dimensional synergy studies.

Traditional measures of intracellular antimicrobial activity and eukaryotic cell cytotoxicity rely on endpoint assays. Such endpoint assays require ...

Immunology and Infection

Finite Element Modelling of a Cellular Electric Microenvironment

Clinical studies show electrical stimulation (ES) to be a potential therapy for the healing and regeneration of various tissues. Understanding the mechanisms of cell response when exposed to electrical fields can therefore guide the optimization of clinical applications. In vitro experiments aim to help uncover those, offering the advantage of wider input and output ranges that can be ethically and effectively assessed. However, the advancements in in vitro experiments are difficult to reproduce directly in clinical settings. Mainly, that is because the ES devices used in vitro differ significantly from the ones suitable for patient use, and the path from the electrodes to the targeted cells is different. Translating the in vitro results into in vivo procedures is therefore not straightforward. We emphasize that the cellular microenvironment's structure and physical properties play a determining role in the actual experimental testing conditions and suggest that measures of charge distribution can be used to bridge the gap between in vitro and in vivo. Considering this, we show how in silico finite element modelling (FEM) can be used to describe the cellular microenvironment and the changes generated by electric field (EF) exposure. We highlight how the EF couples with geometric structure to determine charge distribution. We then show the impact of time dependent inputs on charge movement. Finally, we demonstrate the relevance of our new in silico model methodology using two case studies: (i) in vitro fibrous Poly(3,4-ethylenedioxythiophene) poly(styrenesulfonate) (PEDOT-PSS) scaffolds and (ii) in vivo collagen in extracellular matrix (ECM).

This paper presents a strategy for building finite element models of fibrous conductive materials exposed to an electric field (EF). The models can be used to estimate the electrical input that cells seeded in such materials receive and assess the impact of changing the scaffold's constituent material properties, structure or orientation.

Clinical studies show electrical stimulation (ES) to be a potential therapy for the healing and regeneration of various tissues. Understanding the ...

In Vitro Multiparametric Cellular Analysis by Micro Organic Charge-modulated Field-effect Transistor Arrays

Modern electrophysiology has been constantly fueled by the parallel development of increasingly sophisticated tools and materials. In turn, discoveries in this field have driven technological progress in a back-and-forth process that ultimately determined the impressive achievements of the past 50 years. However, the most employed devices used for cellular interfacing (namely, the microelectrode arrays and microelectronic devices based on transistors) still present several limitations such as high cost, the rigidity of the materials, and the presence of an external reference electrode. To partially overcome these issues, there have been developments in a new scientific field called organic bioelectronics, resulting in advantages such as lower cost, more convenient materials, and innovative fabrication techniques.
Several interesting new organic devices have been proposed during the past decade to conveniently interface with cell cultures.&#160;This paper presents the protocol for the fabrication of devices for cellular interfacing based on the organic charge-modulated field-effect transistor (OCMFET). These devices, called micro OCMFET arrays (MOAs), combine the advantages of organic electronics and the peculiar features of the OCMFET to prepare transparent, flexible, and reference-less tools with which it is possible to monitor both the electrical and the metabolic activities of cardiomyocytes and neurons in vitro, thus allowing a multiparametric evaluation of electrogenic cell models.

In Vitro Multiparametric Cellular Analysis by Micro Organic Charge-modulated Field-effect Transistor Arrays

Here, we present the fabrication protocol of an organic charge-modulated field-effect transistor (OCMFET)-based device for in vitro cellular interfacing. The device, called a micro OCMFET array, is a flexible, low-cost, and reference-less device, which will enable the monitoring of the electrical and metabolic activities of electroactive cell cultures.

Modern electrophysiology has been constantly fueled by the parallel development of increasingly sophisticated tools and materials. In turn, discoveries in ...

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

Summary

Explore More Videos

Preparation and Testing of Impedance-based Fluidic Biochips with RTgill-W1 Cells for Rapid Evaluation of Drinking Water Samples for Toxicity

Imaging Approaches to Assessments of Toxicological Oxidative Stress Using Genetically-encoded Fluorogenic Sensors

Regeneration of Arrayed Gold Microelectrodes Equipped for a Real-Time Cell Analyzer

Sensing of Barrier Tissue Disruption with an Organic Electrochemical Transistor

A High-throughput Assay for the Prediction of Chemical Toxicity by Automated Phenotypic Profiling of Caenorhabditis elegans

Real-Time Impedance-based Cell Analyzer as a Tool to Delineate Molecular Pathways Involved in Neurotoxicity and Neuroprotection in a Neuronal Cell Line

Magnetometric Characterization of Intermediates in the Solid-State Electrochemistry of Redox-Active Metal-Organic Frameworks

High Throughput, Real-time, Dual-readout Testing of Intracellular Antimicrobial Activity and Eukaryotic Cell Cytotoxicity

Finite Element Modelling of a Cellular Electric Microenvironment

In Vitro Multiparametric Cellular Analysis by Micro Organic Charge-modulated Field-effect Transistor Arrays