Name: experimental quantification of interactions between drug delivery systems and cells in vitro: a guide for preclinical nanomedicine evaluation
Uploaded: 2022-09-28T13:00:00
Description: Watch this Scientific Journal Video about Experimental Quantification of Interactions Between Drug Delivery Systems and Cells In Vitro: A Guide for Preclinical Nanomedicine Evaluation at JoVE.com

This work was supported by the Australian National Health and Medical Research Council (NHMRC; Program Grant No. GNT1149990), the Australian Centre for HIV and Hepatitis Virology Research (ACH2), as well a gift from the estate of R&#233;jane Louise Langlois. F.C. acknowledges the award of a National Health and Medical Research Council (NHMRC) Senior Principal Research Fellowship (GNT1135806). Figure 1 and Figure 2 were created with BioRender.com.

1. Choosing the appropriate stream
<ol>
	<li>Follow the decision tree outlined in Figure 1 to determine the best workflow (stream) (Figure 2) for the experimental setup used. Refer to the discussion for further comments on this choice of stream.</li>
	<li>If following the Cytometer Stream, continue with steps 2.1.1-2.2.7. If following the Bulk Stream, continue with steps 3.1.1.1-3.1.5.7.</li>
</ol>
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<ol>
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J., Crampin, E., Caruso, F. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Bio-nano+science:+Better+metrics+would+accelerate+progress.">Bio-nano science: Better metrics would accelerate progress.</a> Chemistry of Materials. 33 (19), 7613-7619 (2021).</li><li>Shin, H., Kwak, M., Geol Lee, T., Youn Lee, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Quantifying+the+level+of+nanoparticle+uptake+in+mammalian+cells+using+flow+cytometry.">Quantifying the level of nanoparticle uptake in mammalian cells using flow cytometry.</a> Nanoscale. 12 (29), 15743-15751 (2020).</li><li>Lozano-Andr&#233;s, E., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Considerations+for+MESF-bead+based+assignment+of+absolute+fluorescence+values+to+nanoparticles+and+extracellular+vesicles+by+flow+cytometry.">Considerations for MESF-bead based assignment of absolute fluorescence values to nanoparticles and extracellular vesicles by flow cytometry.</a> bioRxiv. , (2021).</li><li>Schwartz, A., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Formalization+of+the+MESF+unit+of+fluorescence+intensity.">Formalization of the MESF unit of fluorescence intensity.</a> Cytometry. Part B, Clinical Cytometry. 57 (1), 1-6 (2004).</li><li>Faria, M., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Revisiting+cell-particle+association+in+vitro:+A+quantitative+method+to+compare+particle+performance.">Revisiting cell-particle association in vitro: A quantitative method to compare particle performance.</a> Journal of Controlled Release. 307, 355-367 (2019).</li><li>Chen, A. K., Cheng, Z., Behlke, M. A., Tsourkas, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Assessing+the+sensitivity+of+commercially+available+fluorophores+to+the+intracellular+environment.">Assessing the sensitivity of commercially available fluorophores to the intracellular environment.</a> Analytical Chemistry. 80 (19), 7437-7444 (2008).</li><li>Comfort, N., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Nanoparticle+tracking+analysis+for+the+quantification+and+size+determination+of+extracellular+vesicles.">Nanoparticle tracking analysis for the quantification and size determination of extracellular vesicles.</a> Journal of Visualized Experiments. (169), e62447 (2021).</li><li>Cui, J., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Immobilized+particle+imaging+for+quantification+of+nano-+and+microparticles.">Immobilized particle imaging for quantification of nano- and microparticles.</a> Langmuir. 32 (14), 3532-3540 (2016).</li><li>Shang, J., Gao, X. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Nanoparticle+counting:+Towards+accurate+determination+of+the+molar+concentration.">Nanoparticle counting: Towards accurate determination of the molar concentration.</a> Chemical Society Reviews. 43 (21), 7267-7278 (2014).</li><li>Thomas, D. 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Characterizing the interactions between drug carriers and cells is becoming increasingly important in the development of novel drug delivery systems. Specifically, to allow the rational evaluation and comparison of various carrier constructs, absolute quantification of the performance of said carrier to interact with target and off-target cells is critical. This protocol describes a two-stream methodology that allows any researcher working with a drug carrier to convert relative, semiquantitative flow cytometry data on c...

The design of drug delivery constructs that exhibit specific, designed behavior depending on what cell type they encounter has attracted substantial research interest. Potential drug delivery constructs or &#34;carriers&#34; include lipid formulations, nano-grown inorganics, polymeric assemblies, extracellular vesicles, functionalized bacterial cells, or modified viruses. All of these can exhibit organ, tissue, or cell specificity due to physical properties, surface properties, or engineered chemical functionalizations such as antibody attachment1,2.
A nearly ubiquitous step in in vitro carrier evaluation is to incubate cells with a suspension containing said drug-loaded carrier. Post incubation, carrier performance is measured via a functional readout of the drug cargo&#39;s performance, for example, transfection efficiency or toxicity. Functional readouts are useful, as they are a downstream measure of carrier effectiveness. However, for more complex drug delivery constructs, it is increasingly important to move beyond functional readouts and separately quantify the degree of carrier interaction with the cell of interest. There are a few reasons for this.
First, there is increasing interest in discovering (and iteratively improving) &#34;platform&#34; carrier technologies, which can carry a variety of cargo. For example, lipid nanoparticles (LNPs) designed to encapsulate RNA can exchange one RNA sequence for another with few caveats3. Thus, to iteratively improve the carrier technology, it is critical to quantify its performance independent of the cargo functionality. Second, functional readouts may not be straightforward for the cargo of interest, compromising the ability to rapidly iterate and evaluate carrier formulations. While one could perform in vitro optimization using a model cargo with a straightforward functional readout (for instance, fluorescence), changing the cargo can change the biological response to a carrier4 and may, thus, not yield representative results. Third, many carriers are designed to interact with and be taken up by a specific cell type. Such targeting capability of a carrier can and should be differentiated from the performance of its therapeutic cargo&#160;post targeting. To continue the LNP example, an RNA cargo might be extremely potent, but if the LNP is unable to bind to the cell, be internalized, and release the RNA, no downstream functional effect will be observed. This can be an issue particularly for carriers intended to target hard-to-transfect cell types, such as T cells5. Conversely, an LNP could target extremely effectively, but the RNA cargo might not function. A downstream assay that just measures cargo functionality will be unable to differentiate between these two situations, thus complicating the development and optimization of carrier drug delivery systems.
In this work, how to absolutely quantify carrier association is discussed. Association is a term that refers to the experimentally measured degree of interaction between a carrier and a cell. Association does not differentiate between membrane binding and internalization-a carrier may be associated because it is bound to the cell surface or because the cell has internalized it. Association is commonly measured as part of cell-carrier incubation experiments. Historically, association has been reported either in arbitrary fluorescent units (typically &#34;median fluorescence intensity&#34; or MFI) or as &#34;percent association,&#34; metrics whose limitations have been previously discussed6. In short, these measurements are not comparable between experiments, laboratories, and drug carriers due to differences in experimental protocols, flow cytometer settings, and the labeling intensities of different carriers. Efforts have been made to overcome the former by calibrating the cytometer, thereby converting the relative measure of MFI into an absolutely quantitative measure of fluorescence7. However, this method does not account for the variability in the labeling intensity of various carriers and, thus, does not allow the rational comparison of various carrier performances in a target cell of choice8.
Here, how to practically convert from relative, arbitrary fluorescent units to the absolute quantitative metric of the &#34;number of carriers per cell&#34; is demonstrated by performing a small number of additional characterization experiments. If another metric of carrier concentration is desired (e.g., carrier mass per cell or carrier volume per cell), it is straightforward to convert from carriers per cell, provided carrier characterization has been done. For brevity and to avoid jargon, the word &#34;carrier&#34; is used within this work to refer to the vast assortment of drug delivery constructs. These quantification techniques are equally applicable, whether applied to a nano-engineered gold particle or a bio-engineered bacteria.
A few facts enable the conversion from arbitrary fluorescent units to carriers per cell. First, the measured fluorescence intensity is proportional to the concentration of a fluorophore9 (or a fluorescently labeled carrier), assuming the fluorescence is within the detection limits of the instrument and the instrumentation settings are the same. Thus, if the fluorescence of a carrier and the fluorescence of a sample are known, one can determine how many carriers are present in that sample if all the measurements were performed under the same settings and conditions. However, especially for smaller carriers, it may not be possible to measure carrier fluorescence, cell autofluorescence, and cell-associated-with-carriers fluorescence on the same instrument with the same settings. In this case, there is a second requirement to make it possible to convert between measured fluorescence on one instrument and measured fluorescence on another. To do so, a standard curve of fluorophore concentration can be established to measure the fluorescence intensity on both instruments, taking advantage of the Molecules of Equivalent Soluble Fluorochrome (MESF) standard9. This then allows measurement of the carrier fluorescence in bulk on a non-cytometer, a measurement that can be done on carriers of any size or characteristic. When such bulk quantification is done on a carrier suspension of known concentration, the number of carriers per cell of a sample can, once again, be calculated.
While this work demonstrates the process for measuring carrier association (as determined by measured fluorescence intensity), an analogous protocol could be performed for other measures of cell-carrier interaction (e.g., an experimental protocol that differentiates internalized and membrane-bound carriers). Additionally, this protocol would be largely the same if association was measured through a non-fluorescent assay (for instance, through mass cytometry).

<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>Alexa Fluor 647 C2 Maleimide</td>
			<td>Invitrogen</td>
			<td>A20347</td>
			<td>pH-stable dye used to label 150 nm, 235 nm, or 633 nm PMASH carriers; example of good dye to use in cell-carrier association studies</td>
		</tr>
		<tr>
			<td>Apogee A50 Microflow</td>
			<td>Apogee</td>
			<td></td>
			<td>Sensitive flow cytometer capable of detecting small carriers for counting</td>
		</tr>
		<tr>
			<td>CytoFLEX S Flow Cytometer</td>
			<td>Beckman Coulter</td>
			<td></td>
			<td>Sensitive flow cytometer capable of detecting small carriers for counting and read out for final cell-barrier experiments</td>
		</tr>
		<tr>
			<td>FCS Express</td>
			<td>De Novo Software</td>
			<td></td>
			<td>Software used to analyze flow cytometry data, i.e., perform gating and derive median fluorescence intensity values of populations of choice. Alternatives include FlowJo, OMIQ, Python</td>
		</tr>
		<tr>
			<td>Infinite 200 PRO</td>
			<td>Tecan Lifesciences</td>
			<td></td>
			<td>Standard microplate reader instrument used for bulk fluorescence measurements of carriers in solution</td>
		</tr>
		<tr>
			<td>LSRFortessa Cell Analyzer</td>
			<td>BD Biosciences</td>
			<td></td>
			<td>Less sensitive flow cytometer, but one more generally available to researchers. Can be used to read out final cell-carrier experiment</td>
		</tr>
		<tr>
			<td>NanoSight NS300</td>
			<td>Malvern Panalytical</td>
			<td></td>
			<td>Instrument used for Nanoparticle Tracking Analysis</td>
		</tr>
		<tr>
			<td>Prism 8</td>
			<td>GraphPad</td>
			<td></td>
			<td>Software used to graph and calculate standard curves. Alternatives include Microsoft Excel, Origin, Minitab, Python amongst many others</td>
		</tr>
		<tr>
			<td>Quantum MESF kits Alexa Fluor 647</td>
			<td>Bangs Laboratories</td>
			<td>647</td>
			<td>Absolute quantitation beads for flow cytometery. Used to convert fluorescence intensities measured in bulk on a microplate reader to fluorescence intensities measured on a flow cytometer using the MESF standard</td>
		</tr>
	</tbody>
</table>

experimental quantification of interactions between drug delivery systems and cells in vitro: a guide for preclinical nanomedicine evaluation

A major component of designing drug delivery systems concerns how to amplify or attenuate interactions with specific cell types. For instance, a chemotherapeutic might be functionalized with an antibody to enhance binding to cancer cells (&#34;targeting&#34;) or functionalized with polyethylene glycol to help evade immune cell recognition (&#34;stealth&#34;). Even at a cellular level, optimizing the binding and uptake of a drug carrier is a complex biological design problem. Thus, it is valuable to separate how strongly a new carrier interacts with a cell from the functional efficacy of a carrier&#39;s cargo once delivered to that cell.
To continue the chemotherapeutic example, &#34;how well it binds to a cancer cell&#34; is a separate problem from &#34;how well it kills a cancer cell&#34;. Quantitative in vitro assays for the latter are well established and usually rely on measuring viability. However, most published research on cell-carrier interactions is qualitative or semiquantitative. Generally, these measurements rely on fluorescent labeling of the carrier and, consequently, report interactions with cells in relative or arbitrary units. However, this work can be standardized and be made absolutely quantitative with a small number of characterization experiments. Such absolute quantification is valuable, as it facilitates rational, inter- and intra-class comparisons of various drug delivery systems-nanoparticles, microparticles, viruses, antibody-drug conjugates, engineered therapeutic cells, or extracellular vesicles.
Furthermore, quantification is a prerequisite for subsequent meta-analyses or in silico modeling approaches. In this article, video guides, as well as a decision tree for how to achieve in vitro quantification for carrier drug delivery systems, are presented, which take into account differences in carrier size and labeling modality. Additionally, further considerations for the quantitative assessment of advanced drug delivery systems are discussed. This is intended to serve as a valuable resource to improve rational evaluation and design for the next generation of medicine.

As discussed previously, different drug carrier types require the use of different techniques for the absolute quantification of cell-carrier association. For example, 633 nm disulfide-stabilized poly(methacrylic acid) (PMASH) core-shell particles are large and dense enough for detection using a sensitive flow cytometer. As such, these particles were labeled fluorescently, then gated and counted using side-angle light scattering (SALS, analogous to SSC), as well as the appropriate fluorescent channel (<strong ...

Watch this Scientific Journal Video about Experimental Quantification of Interactions Between Drug Delivery Systems and Cells In Vitro: A Guide for Preclinical Nanomedicine Evaluation at JoVE.com

Experimental Quantification of Interactions Between Drug Delivery Systems and Cells In Vitro: A Guide for Preclinical Nanomedicine Evaluation

A workflow is demonstrated for the absolute quantification of drug carrier-cell interactions using flow cytometry to allow better rational evaluation of novel drug delivery systems. This workflow is applicable to drug carriers of any type.

Experimental Quantification of Interactions Between Drug Delivery Systems and Cells In Vitro: A Guide for Preclinical Nanomedicine Evaluation

A major component of designing drug delivery systems concerns how to amplify or attenuate interactions with specific cell types. For instance, a ...

This protocol provides quantitative data on how carrier systems interact with cells. Quantitative data is key for engineering and optimization. It allows us to move from yes or no biological questions, to how much questions.This technique is useful to convert results from preclinical drug carrier performance, which were qualitative, into quantitative results. And this works even when you characterize your carrier on a different system than you characterize your cells. It can take a few iterations to find the optimal carrier dilution that fall within the linear or quantitative ranges of the nano side.Take your time for finding the right conditions. To begin, mount the flow cell onto the laser module. Slowly flush the flow cell at the rate of 0.1 milliliter per second with one milliliter of distilled water.If bubbles form within the flow cell, partially retract the suspension to merge the bubble with the air-liquid interface before proceeding. Then lock the entire laser module in place inside the instrument. Start the camera roughly halfway through flushing.Be sure to confirm that the carrier debris is washed out. Select capture to open the capture settings tab and click start camera. Drive the system with one milliliter of air.If any static carriers are visible on the screen, clean the flow cell according to the manufacturer's instructions. Prepare the carriers for nanoparticle tracking analysis, by ensuring the carriers are well suspended via sonication or vortexing, depending on the carrier system involved. Dilute the carriers in water to prepare at least 0.6 to one milliliter of each sample with a carrier concentration between 1x10 to the seventh and 1x10 to the ninth carriers per milliliter.Take out the laser module and place it upright. Drop the first carrier sample into a one milliliter syringe and attach the syringe to the tube inlet. Then carefully load the sample into the flow cell.If bubbles form within the flow cell, retract the suspension partially to merge the bubble with the air-liquid interface before proceeding. Ensure the entire flow cell is filled with liquid, then pause the loading. Adjust the camera focus if needed to visualize individual carriers.Make coarse focus adjustments with the rotating knob on the right hand side of the instrument. Make finer adjustments by selecting the hardware tab. Change the focus by adjusting the focus slider.To ensure there is no oversaturation, select the optimal camera level by adjusting the slider within the capture tab. If the instrument is equipped with this accessory, load the syringe containing the carrier sample into the syringe pump. Under the SOP tab, select standard measurement to take five captures of 30 seconds each.Enter base file name, and if desired, add additional sample information by clicking the advanced button which will open a modal dialogue with various choices. Press create and run script and wait for a pop-up to appear asking to please advance sample. If using the syringe pump, select the hardware tab and then syringe pump tab.Set the desired infusion rate and press infuse. If not using the syringe pump, manually advance the sample. In the popup window, select OK to start capturing.After each of the five captures, when the please advanced sample pop up reappears, check that the sample is still moving through the flow cell. Then select OK to proceed with the next capture. In the process tab, adjust the detection threshold slider between four and eight to correctly identify distinct carriers visible on the screen.You can adjust the screen gain to aid visualization, it will not affect the downstream analysis. In the pop-up, press okay to initiate tracking analysis. Monitor the analysis progress by clicking on the analysis in single analysis tab.Once the analysis is finished, look for an export settings prompt to appear. Confirm that the include PDF and include experiment summary is selected. Select any other export formats as desired.In the results section of the PDF data export, to ensure the concentration measured is reliable, verify that the measured carrier concentration is between 1x10 to the seventh and 1x10 to the ninth carriers per milliliter and check for any error messages or messages of caution underneath the concentration measurement result. Repeat the procedure two or more times with different dilutions from the stock, and ensure that each sample's concentration falls within the instrument's linear range. Calculate the stock carrier concentration as described in the text manuscript.Prepare the free or antibody conjugated fluorochrome solution as described in the text manuscript. Calculate the concentration of the stock solution from the concentration, the molecular weight, and Avogadro's number as shown in the equation. Then perform a serial dilution of the dye in the carrier diluent to generate standard curve samples.Then add the carrier sample to the measurement plate and measure fluorescence using a microplate reader. Generate the standard curve as described in the text manuscript. Calculate the absolute fluorescence intensity per carrier by dividing the bulk fluorescence by the carrier concentration.Set up the flow cytometer for the final carrier cell experiment by determining optimal PMT voltage settings in the relevant channels. Run a negative control sample where the cells are not incubated with carriers to determine the background fluorescence. Prepare and re-suspend the flow cytometry quantitation beads.Use the same buffer as used for the cell samples. If the bead populations are provided separately, pull them together. Run the flow cytometry quantitation bead and the carrier cell samples to determine the fluorescence intensity per cell.Run the flow cytometer quantitation beads to generate a standard curve, converting the absolute fluorescent intensity into MFI. Use this to calculate the theoretical MFI of the carriers as described in the text manuscript. Run the cell carrier samples to determine the fluorescent intensity per cell of each sample.Finally, calculate the number of carriers per cell for each sample by subtracting the background fluorescence from the measured fluorescence of the sample, and then dividing by the fluorescence per particle. For 633 nanometer Polymethacrylic acid core shell particles, the concentration and fluorescent intensity per carrier were directly quantifiable using the cytometer stream. In contrast, 100 nanometer super paramagnetic iron oxide nanoparticles were too small to detect individually and were analyzed using the bulk stream.Labeled quantitation beads were used on multiple days to generate standard curves on a flow cytometer. The correlation between the measured MFI and the MESF value of the quantitation beads was linear and broadly similar between the measured dates. Time course experiments using fluorescent labeled HeLa cells with 235 nanometer polymethacrylic acid capsules from zero to 24 hours showed an increase in the MFI over time, indicating the capsules were associating with HeLa cells.The difference in the apparent cellular response to carriers was stark, depending on relative or absolute quantification. The absolute quantification was independent of labeling intensity and thus more comparable. These techniques are the foundation for deeper analysis and comparison of particle performance.We're excited about using these techniques to parameterize mathematical models which will allow us to characterize particle performance independent of any particular experiment.

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Bioengineering

Models and Methods to Evaluate Transport of Drug Delivery Systems Across Cellular Barriers

Sub-micrometer carriers (nanocarriers; NCs) enhance efficacy of drugs by improving solubility, stability, circulation time, targeting, and release. Additionally, traversing cellular barriers in the body is crucial for both oral delivery of therapeutic NCs into the circulation and transport from the blood into tissues, where intervention is needed. NC transport across cellular barriers is achieved by: (i) the paracellular route, via transient disruption of the junctions that interlock adjacent cells, or (ii) the transcellular route, where materials are internalized by endocytosis, transported across the cell body, and secreted at the opposite cell surface (transyctosis). Delivery across cellular barriers can be facilitated by coupling therapeutics or their carriers with targeting agents that bind specifically to cell-surface markers involved in transport. Here, we provide methods to measure the extent and mechanism of NC transport across a model cell barrier, which consists of a monolayer of gastrointestinal (GI) epithelial cells grown on a porous membrane located in a transwell insert. Formation of a permeability barrier is confirmed by measuring transepithelial electrical resistance (TEER), transepithelial transport of a control substance, and immunostaining of tight junctions. As an example, ~200&#160;nm polymer NCs are used, which carry a therapeutic cargo and are coated with an antibody that targets a cell-surface determinant. The antibody or therapeutic cargo is labeled with 125I for radioisotope tracing and labeled NCs are added to the upper chamber over the cell monolayer for varying periods of time. NCs associated to the cells and/or transported to the underlying chamber can be detected. Measurement of free 125I allows subtraction of the degraded fraction. The paracellular route is assessed by determining potential changes caused by NC transport to the barrier parameters described above. Transcellular transport is determined by addressing the effect of modulating endocytosis and transcytosis pathways.

Many therapeutic applications require safe and efficient transport of drug carriers and their cargoes across cellular barriers in the body. This article describes an adaptation of established methods to evaluate the rate and mechanism of transport of drug nanocarriers (NCs) across cellular barriers, such as the gastrointestinal (GI) epithelium.

Sub-micrometer carriers (nanocarriers; NCs) enhance efficacy of drugs by improving solubility, stability, circulation time, targeting, and release. ...

Eye Irritation Test (EIT) for Hazard Identification of Eye Irritating Chemicals using Reconstructed Human Cornea-like Epithelial (RhCE) Tissue Model

To comply with the Seventh Amendment to the EU Cosmetics Directive and EU REACH legislation, validated non-animal alternative methods for reliable and accurate assessment of ocular toxicity in man are needed. To address this need, we have developed an eye irritation test (EIT) which utilizes a three dimensional reconstructed human cornea-like epithelial (RhCE) tissue model that is based on normal human cells. The EIT is able to separate ocular&#160;irritants and corrosives (GHS Categories 1 and 2 combined) and those that do not require labeling (GHS No Category). The test utilizes two separate protocols, one designed for liquid chemicals and a second, similar protocol for solid test articles. The EIT prediction model uses a single exposure period (30 min for liquids, 6 hr for solids) and a single tissue viability cut-off (60.0% as determined by the MTT assay). Based on the results for 83 chemicals (44 liquids and 39 solids) EIT achieved 95.5/68.2/ and 81.8% sensitivity/specificity and accuracy (SS&#38;A) for liquids, 100.0/68.4/ and 84.6% SS&#38;A for solids, and 97.6/68.3/ and 83.1% for overall SS&#38;A. The EIT will contribute significantly to classifying the ocular irritation potential of a wide range of liquid and solid chemicals without the use of animals to meet regulatory testing requirements. The EpiOcular EIT method was implemented in 2015 into the OECD Test Guidelines as TG 492.

Eye Irritation Test EIT for Hazard Identification of Eye Irritating Chemicals using Reconstructed Human Cornea-like Epithelial RhCE Tissue Model

We have developed an eye irritation test which utilizes a three dimensional reconstructed human cornea-like epithelial (RhCE) tissue model. The test is able to discriminate between ocular irritant and corrosive materials (GHS Categories 1 and 2 combined) and those that do not require labeling (GHS No Category).

To comply with the Seventh Amendment to the EU Cosmetics Directive and EU REACH legislation, validated non-animal alternative methods for reliable and ...

Adapting the Electrospinning Process to Provide Three Unique Environments for a Tri-layered In Vitro Model of the Airway Wall

Electrospinning is a highly adaptable method producing porous 3D fibrous scaffolds that can be exploited in in vitro cell culture. Alterations to intrinsic parameters within the process allow a high degree of control over scaffold characteristics including fiber diameter, alignment and porosity. By developing scaffolds with similar dimensions and topographies to organ- or tissue-specific extracellular matrices (ECM), micro-environments representative to those that cells are exposed to in situ can be created. 
The airway bronchiole wall, comprised of three main micro-environments, was selected as a model tissue. Using decellularized airway ECM as a guide, we electrospun the non-degradable polymer, polyethylene terephthalate (PET), by three different protocols to produce three individual electrospun scaffolds optimized for epithelial, fibroblast or smooth muscle cell-culture. Using a commercially available bioreactor system, we stably co-cultured the three cell-types to provide an in vitro model of the airway wall over an extended time period.
This model highlights the potential for such methods being employed in in vitro diagnostic studies investigating important inter-cellular cross-talk mechanisms or assessing novel pharmaceutical targets, by providing a relevant platform to allow the culture of fully differentiated adult cells within 3D, tissue-specific environments.

Adapting the Electrospinning Process to Provide Three Unique Environments for a Tri-layered In Vitro Model of the Airway Wall

Advancements in biomaterial technologies enable the development of three-dimensional multi-cell-type constructs. We have developed electrospinning protocols to produce three individual scaffolds to culture the main structural cells of the airway to provide a 3D in vitro model of the airway bronchiole wall.

Electrospinning is a highly adaptable method producing porous 3D fibrous scaffolds that can be exploited in in vitro cell culture. Alterations to ...

Sandwich-like Microenvironments to Harness Cell/Material Interactions

Cell culture has been traditionally carried out on bi-dimensional (2D) substrates where cells adhere using ventral receptors to the biomaterial surface. However in vivo, most of the cells are completely surrounded by the extracellular matrix (ECM), resulting in a three-dimensional (3D) distribution of receptors. This may trigger differences in the outside-in signaling pathways and thus in cell behavior.
This article shows that stimulating the dorsal receptors of cells already adhered to a 2D substrate by overlaying a film of a new material (a sandwich-like culture) triggers important changes with respect to standard 2D cultures. Furthermore, the simultaneous excitation of ventral and dorsal receptors shifts cell behavior closer to that found in 3D environments. Additionally, due to the nature of the system, a sandwich-like culture is a versatile tool that allows the study of different parameters in cell/material interactions, e.g., topography, stiffness and different protein coatings at both the ventral and dorsal sides. Finally, since sandwich-like cultures are based on 2D substrates, several analysis procedures already developed for standard 2D cultures can be used normally, overcoming more complex procedures needed for 3D systems.

The following protocol describes the procedure to assemble sandwich-like cultures to be used as an intermediate stage between bi-dimensional (2D) and three-dimensional (3D) cellular environments. The engineered systems can have applications in microscopy, biomechanics, biochemistry and cell biology assays.

Cell culture has been traditionally carried out on bi-dimensional (2D) substrates where cells adhere using ventral receptors to the biomaterial surface. ...

Synthesis of Functionalized 10-nm Polymer-coated Gold Particles for Endothelium Targeting and Drug Delivery

Gold nanoparticles (AuNPs) have been used extensively in medical research due to their size, biocompatibility, and modifiable surface. Specific targeting and drug delivery are some of the applications of these AuNPs, but endothelial extracellular matrices&#39; defensive properties hamper particle uptake. To address this issue, we describe a synthesis method for ultrasmall gold nanoparticles to improve vascular delivery, with customizable functional groups and polymer lengths for further adjustments. The protocol yields 2.5 nm AuNPs that are capped with tetrakis(hydroxymethyl)phosphonium chloride (THPC). The replacement of THPC with hetero-functional polyethylene glycol (PEG) on the surface of the AuNP increases the hydrodynamic radius to 10.5 nm while providing various functional groups on the surface. The last part of the protocol includes an optional addition of a fluorophore to allow the AuNPs to be visualized under fluorescence to track nanoparticle uptake. Dialysis and lyophilization were used to purify and isolate the AuNPs. These fluorescent nanoparticles can be visualized in both in vitro and in vivo experiments due to the biocompatible PEG coating and fluorescent probes. Additionally, the size range of these nanoparticles render them an ideal candidate for probing the glycocalyx without disrupting normal vasculature function, which may lead to improved delivery and therapeutics.

We describe a method of synthesizing biocompatible 10-nm gold nanoparticles, functionalized by coating poly-ethylene glycol onto the surface. These particles can be used in vitro and in vivo for delivering therapeutics to nanoscale cellular and extracellular spaces that are difficult to access with conventional nanoparticle sizes.

Gold nanoparticles (AuNPs) have been used extensively in medical research due to their size, biocompatibility, and modifiable surface. Specific targeting ...

Comprehensive Evaluation of the Effectiveness and Safety of Placenta-Targeted Drug Delivery Using Three Complementary Methods

No effective treatments currently exist for placenta-associated pregnancy complications, and developing strategies for the targeted delivery of drugs to the placenta while minimizing fetal and maternal side effects remains challenging. Targeted nanoparticle carriers provide new opportunities to treat placental disorders. We recently demonstrated that a synthetic placental chondroitin sulfate A binding peptide (plCSA-BP) could be used to guide nanoparticles to deliver drugs to the placenta. In this protocol, we describe in detail a system for assessing the efficiency of drug delivery to the placenta by plCSA-BP that employs three separate methods used in combination: in vivo imaging, high-frequency ultrasound (HFUS), and high-performance liquid chromatography (HPLC). Using in vivo imaging, plCSA-BP-guided nanoparticles were visualized in the placentas of live animals, while HFUS and HPLC demonstrated that plCSA-BP-conjugated nanoparticles efficiently and specifically delivered methotrexate to the placenta. Thus, a combination of these methods can be used as an effective tool for the targeted delivery of drugs to the placenta and development of new treatment strategies for several pregnancy complications.

We describe a system that utilizes three methods to evaluate the safety and effectiveness of placenta-targeted drug delivery: in vivo imaging to monitor nanoparticle accumulation, high-frequency ultrasound to monitor placental and fetal development, and HPLC to quantify drug delivery to tissue.

No effective treatments currently exist for placenta-associated pregnancy complications, and developing strategies for the targeted delivery of drugs to ...

Use of High-Throughput Automated Microbioreactor System for Production of Model IgG1 in CHO Cells

Automated microscale bioreactors (15 mL) can be a useful tool for cell culture engineers. They facilitate the simultaneous execution of a wide variety of experimental conditions while minimizing potential process variability. Applications of this approach include: clone screening, temperature and pH shifts,&#160;media and supplement optimization. Furthermore, the small reactor volumes are conducive to large Design of Experiments that investigate a wide range of conditions. This allows upstream processes to be significantly optimized before scale-up where experimentation is more limited in scope due to time and economic constraints. Automated microscale bioreactor systems offer various advantages over traditional small scale cell culture units, such as shake flasks or spinner flasks. However, during pilot scale process development&#160;significant care must be taken to ensure that these advantages are realized. When run with care, the system can enable high level automation, can be programmed to run DOE&#39;s with a higher number of variables&#160;and can reduce sampling time when integrated with a nutrient analyzer or cell counter. Integration of the expert-derived heuristics presented here, with current automated microscale bioreactor experiments can minimize common pitfalls that hinder meaningful results. In the extreme, failure to adhere to the principles laid out here can lead to equipment damage that requires expensive repairs. Furthermore, the microbioreactor systems have small culture volumes&#160;making characterization of cell culture conditions difficult. The number and amount of samples taken in-process in batch mode culture is limited as operating volumes cannot fall below 10 mL. This method will discuss the benefits and drawbacks of microscale bioreactor systems.

A detailed protocol for the concurrent operation of 48 parallel cell cultures under varied conditions in a microbioreactor system is presented. Cell culture process, harvest and subsequent antibody titer analysis are described.

Automated microscale bioreactors (15 mL) can be a useful tool for cell culture engineers. They facilitate the simultaneous execution of a wide variety of ...

Purification and Analytics of a Monoclonal Antibody from Chinese Hamster Ovary Cells Using an Automated Microbioreactor System

Monoclonal antibodies (mAbs) are one of the most popular and well-characterized biological products manufactured today. Most commonly produced using Chinese hamster ovary (CHO) cells, culture and process conditions must be optimized to maximize antibody titers and achieve target quality profiles. Typically, this optimization uses automated microscale bioreactors (15 mL) to screen multiple process conditions in parallel. Optimization criteria include culture performance and the critical quality attributes (CQAs) of the monoclonal antibody (mAb) product, which may impact its efficacy and safety. Culture performance metrics include cell growth and nutrient consumption, while the CQAs include the mAb's N-glycosylation and aggregation profiles, charge variants, and molecular weight. This detailed protocol describes how to purify and subsequently analyze HCCF samples produced by an automated microbioreactor system to gain valuable performance metrics and outputs. First, an automated protein A fast protein liquid chromatography (FPLC) method is used to purify the mAb from harvested cell culture samples. Once concentrated, the glycan profiles are analyzed by mass spectrometry using a specific platform (refer to the Table of Materials). Antibody molecular weights and aggregation profiles are determined using size exclusion chromatography-multiple angle light scattering (SEC-MALS), while charge variants are analyzed using microchip capillary zone electrophoresis (mCZE). In addition to the culture performance metrics captured during the bioreactor process (i.e., culture viability, cell counts, and common metabolites including glutamine, glucose, lactate, and ammonia), spent media is analyzed to identify limiting nutrients to improve the feeding strategies and overall process design. Therefore, a detailed protocol for the absolute quantification of amino acids by liquid chromatography-mass spectrometry (LC-MS) of spent media is also described. The methods used in this protocol take advantage of high-throughput platforms that are compatible for large numbers of small-volume samples.

A detailed protocol for the purification and subsequent analysis of a monoclonal antibody from harvested cell culture fluid (HCCF) of automated microbioreactors has been described. Use of analytics to determine critical quality attributes (CQAs) and maximizing limited sample volume to extract vital information is also presented.

Monoclonal antibodies (mAbs) are one of the most popular and well-characterized biological products manufactured today. Most commonly produced using ...

A Quantitative Fluorescence Microscopy-based Single Liposome Assay for Detecting the Compositional Inhomogeneity Between Individual Liposomes

Most research employing liposomes as membrane model systems or drug delivery carriers relies on bulk read-out techniques and thus intrinsically assumes all liposomes of the ensemble to be identical. However, new experimental platforms able to observe liposomes at the single-particle level have made it possible to perform highly sophisticated and quantitative studies on protein-membrane interactions or drug carrier properties on individual liposomes, thus avoiding errors from ensemble averaging. Here we present a protocol for preparing, detecting, and analyzing single liposomes using a fluorescence-based microscopy assay, facilitating such single-particle measurements. The setup allows for imaging individual liposomes in a massive parallel manner and is employed to reveal intra-sample size and compositional inhomogeneities. Additionally, the protocol describes the advantages of studying liposomes at the single liposome level, the limitations of the assay, and the important features to be considered when modifying it to study other research questions.

This protocol describes the fabrication of liposomes and how these can be immobilized on a surface and imaged individually in a massive parallel manner using fluorescence microscopy. This allows for the quantification of the size and compositional inhomogeneity between single liposomes of the population.

Most research employing liposomes as membrane model systems or drug delivery carriers relies on bulk read-out techniques and thus intrinsically assumes ...

Preparing Protein Producing Synthetic Cells using Cell Free Bacterial Extracts, Liposomes and Emulsion Transfer

The bottom-up assembly approach for construction of synthetic cells is an effective tool for isolating and investigating cellular processes in a cell mimicking environment. Furthermore, the development of cell-free expression systems has demonstrated the ability to reconstitute the protein production, transcription and translation processes (DNA&#8594;RNA&#8594;protein) in a controlled manner, harnessing synthetic biology. Here we describe a protocol for preparing a cell-free expression system, including the production of a potent bacterial lysate and encapsulating this lysate inside cholesterol-rich lipid-based giant unilamellar vesicles (GUVs) (i.e., stable liposomes), to form synthetic cells. The protocol describes the methods for preparing the components of the synthetic cells including the production of active bacterial lysates, followed by a detailed step-by-step preparation of the synthetic cells based on a water-in-oil emulsion transfer method. These facilitate the production of millions of synthetic cells in a simple and affordable manner with a high versatility for producing different types of proteins. The obtained synthetic cells can be used to investigate protein/RNA production and activity in an isolated environment, in directed evolution, and also as a controlled drug delivery platform for on-demand production of therapeutic proteins inside the body.

This protocol describes the method, materials, equipment and steps for bottom-up preparation of RNA and protein producing synthetic cells. The inner aqueous compartment of the synthetic cells contained the S30 bacterial lysate encapsulated within a lipid bilayer (i.e., stable liposomes), using a water-in-oil emulsion transfer method.

The bottom-up assembly approach for construction of synthetic cells is an effective tool for isolating and investigating cellular processes in a cell ...