This work was created with financial support from Deutsche Forschungsgemeinschaft (DFG) under grant No. PO413/12-1 and LA 1028/7-1.

<ol>
	<li>Marx, U., 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=Human-on-a-chip+developments:+a+translational+cutting-edge+alternative+to+systemic+safety+assessment+and+efficiency+evaluation+of+substances+in+laboratory+animals+and+man?.">Human-on-a-chip developments: a translational cutting-edge alternative to systemic safety assessment and efficiency evaluation of substances in laboratory animals and man?.</a> ATLA. 40 (5), 235-257 (2012).</li><li>Maschmeyer, I., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Chip-based+human+liver-intestine+and+liver-skin+co-cultures+-+A+first+step+toward+systemic+repeated+dose+substance+testing+in+vitro.">Chip-based human liver-intestine and liver-skin co-cultures - A first step toward systemic repeated dose substance testing in vitro.</a> Eur J Pharm Biopharm. 95, 77-87 (2015).</li><li>Prunieras, M., Regnier, M., Woodley, D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Methods+for+Cultivation+of+Keratinocytes+with+an+Air-Liquid+Interface.">Methods for Cultivation of Keratinocytes with an Air-Liquid Interface.</a> J Invest Dermatol. 81 (1), 28-33 (1983).</li><li>Cannon, C. L., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=New+epidermal+model+for+dermal+irritancy+testing.">New epidermal model for dermal irritancy testing.</a> Toxicol In Vitro. 8 (4), 889-891 (1994).</li><li>Ackermann, K., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+Phenion+Full-Thickness+Skin+Model+for+Percutaneous+Absorption+Testing.">The Phenion Full-Thickness Skin Model for Percutaneous Absorption Testing.</a> Skin Pharmacol Physiol. 23 (2), 105-112 (2010).</li><li>Netzlaff, F., 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=Permeability+of+the+reconstructed+human+epidermis+model+Episkin+in+comparison+to+various+human+skin+preparations.">Permeability of the reconstructed human epidermis model Episkin in comparison to various human skin preparations.</a> Eur J Pharm Biopharm. 66 (1), 127-134 (2007).</li><li>Bran, B., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+New+Discriminative+Criterion+for+the+Development+of+Franz+Diffusion+Tests+for+Transdermal+Pharmaceuticals.">A New Discriminative Criterion for the Development of Franz Diffusion Tests for Transdermal Pharmaceuticals.</a> J Pharm Sci. 13 (2), 218-230 (2010).</li><li>Pineau, 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=In+vitro+study+of+percutaneous+absorption+of+aluminum+from+antiperspirants+through+human+skin+in+the+Franz+diffusion+cell.">In vitro study of percutaneous absorption of aluminum from antiperspirants through human skin in the Franz diffusion cell.</a> J Inorg Biochem. 110, 21-26 (2012).</li><li>Filon, F. L., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=In+vitro+percutaneous+absorption+of+cobalt.">In vitro percutaneous absorption of cobalt.</a> Int Arch Occup Environ Health. 77 (2), 85-89 (2004).</li><li>Ng, S. -. F., 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=Validation+of+a+Static+Franz+Diffusion+Cell+System+for+In+Vitro+Permeation+Studies.">Validation of a Static Franz Diffusion Cell System for In Vitro Permeation Studies.</a> AAPS PharmSciTech. 11 (3), 1432-1441 (2010).</li><li>Bonferoni, M. C., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+Modified+Franz+Diffusion+Cell+for+Simultaneous+Assessment+of+Drug+Release+and+Washability+of+Mucoadhesive+Gels.">A Modified Franz Diffusion Cell for Simultaneous Assessment of Drug Release and Washability of Mucoadhesive Gels.</a> Pharm Dev Tecnol. 4 (1), 45-53 (1999).</li><li>Seiffer, S., Oppermann, W. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Systematic+evaluation+of+FRAP+experiments+performed+in+a+confocal+laser+scanning+microscope.">Systematic evaluation of FRAP experiments performed in a confocal laser scanning microscope.</a> J Microsc. 220 (1), 20-30 (2005).</li><li>Pluen, 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=Diffusion+of+Macromolecules+in+Agarose+Gels:+Comparison+of+Linear+and+Globular+Configurations.">Diffusion of Macromolecules in Agarose Gels: Comparison of Linear and Globular Configurations.</a> Biophys J. 77, 542-552 (1999).</li><li>Cornelissen, L. H., 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=Diffusion+measurements+in+epidermal+tissues+with+fluorescent+recovery+after+photobleaching.">Diffusion measurements in epidermal tissues with fluorescent recovery after photobleaching.</a> Skin Res Technol. 14 (4), 462-467 (2008).</li><li>Pirot, F., 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=Characterization+of+the+permeability+barrier+of+human+skin+in+vivo.">Characterization of the permeability barrier of human skin in vivo.</a> PNAS. 94 (4), 1562-1567 (1997).</li><li>Tetteh, 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=Local+examination+of+skin+diffusion+using+FTIR+spectroscopic+imaging+and+multivariate+target+factor+analysis.">Local examination of skin diffusion using FTIR spectroscopic imaging and multivariate target factor analysis.</a> Anal Chim Acta. 642 (1-2), 246-256 (2009).</li><li>Guldbrand, S., 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=Two-photon+fluorescence+correlation+spectroscopy+as+a+tool+for+measuring+molecular+diffusion+within+human+skin.">Two-photon fluorescence correlation spectroscopy as a tool for measuring molecular diffusion within human skin.</a> Eur J Pharm Biopharm. 84 (2), 430-436 (2013).</li><li>Kehe, K., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Tissue+engineering+with+HaCaT+cells+and+a+fibroblast+cell+line.">Tissue engineering with HaCaT cells and a fibroblast cell line.</a> Arch Dermatol Rech. 291 (11), 600-605 (1999).</li><li>Veronike, 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=Epidermal+Organization+and+Differentiation+of+HaCaT+Keratinocytes+in+Organotypic+Coculture+with+Human+Dermal+Fibroblasts.">Epidermal Organization and Differentiation of HaCaT Keratinocytes in Organotypic Coculture with Human Dermal Fibroblasts.</a> J Invest Dermatol. 112 (3), 343-353 (1999).</li><li>Moraes, C., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Organs-on-a-chip:+a+focus+on+compartmentalized+microdevices.">Organs-on-a-chip: a focus on compartmentalized microdevices.</a> Ann Biomed Eng. 40 (6), 1211-1227 (2012).</li><li>Huh, D., 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=From+Three-Dimensional+Cell+Culture+to+Organs-on-Chips.">From Three-Dimensional Cell Culture to Organs-on-Chips.</a> Trends Cell Biol. 21 (12), 745-754 (2011).</li><li>Schimek, K., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Integrating+biological+vasculature+into+a+multi-organ-chip+microsystem.">Integrating biological vasculature into a multi-organ-chip microsystem.</a> Lab Chip. 13 (18), 3588 (2013).</li><li>Materne, E. -. 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=The+Multi-organ+Chip+-+A+Microfluidic+Platform+for+Long-term+Multi-tissue+Coculture.">The Multi-organ Chip - A Microfluidic Platform for Long-term Multi-tissue Coculture.</a> J Vis Exp. (98), (2015).</li><li>Materne, E. -. 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=A+multi-organ+chip+co-culture+of+neurospheres+and+liver+equivalents+for+long-term+substance+testing.">A multi-organ chip co-culture of neurospheres and liver equivalents for long-term substance testing.</a> J Biotechnology. 205, 36-46 (2015).</li><li>Materne, E. -. M., Tonevitsky, A. G., Marx, U. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Chip-based+liver+equivalents+for+toxicity+testing+-+organotypicalness+versus+cost-efficient+high+throughput.">Chip-based liver equivalents for toxicity testing - organotypicalness versus cost-efficient high throughput.</a> Lab Chip. 13 (18), 3481 (2013).</li><li>Jayakrishna, 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=Diffusion+of+High+Molecular+Weight+Compounds+through+Sclera.">Diffusion of High Molecular Weight Compounds through Sclera.</a> IOVS. 41 (5), 1181-1185 (2000).</li><li>Peck, K., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Hindered+Diffusion+of+Polar+Molecules+Through+and+Effective+Pore+Radii+Estimate+of+Intact+and+Ethanol.">Hindered Diffusion of Polar Molecules Through and Effective Pore Radii Estimate of Intact and Ethanol.</a> Pharm Res. 11 (9), 1309-1314 (1994).</li><li>Ogiso, T., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Mechanism+of+the+Enhancement+Effect+of+n-Octyl-&#946;-D-thioglucoside+on+the+Transdermal+Penetration+of+Fluorescein+Isothiocyanate-Labeled+Dextrans+and+the+Molecular+Weight+Dependence+of+Water-Soluble+Penetrants+through+Stripped+Skin.">Mechanism of the Enhancement Effect of n-Octyl-&#946;-D-thioglucoside on the Transdermal Penetration of Fluorescein Isothiocyanate-Labeled Dextrans and the Molecular Weight Dependence of Water-Soluble Penetrants through Stripped Skin.</a> J Pharm Sci. 83 (12), 1676-1681 (1994).</li><li>Hadgraft, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Skin,+the+final+frontier.">Skin, the final frontier.</a> Int J Pharm. 224 (1-2), 1-18 (2001).</li><li>Asselineau, D., 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=Human+Epidermis+Reconstructed+by+Culture:+Is+It+"Normal"?.">Human Epidermis Reconstructed by Culture: Is It "Normal"?.</a> J Invest Dermatol. 86 (2), 181-186 (1986).</li><li>Casasco, 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=Cell+proliferation+and+differentiation+in+a+model+of+human+skin+equivalent.">Cell proliferation and differentiation in a model of human skin equivalent.</a> Anat Rec. 264 (3), 261-272 (2001).</li><li>Kehe, K., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Tissue+engineering+with+HaCaT+cells+and+a+fibroblast+cell+line.">Tissue engineering with HaCaT cells and a fibroblast cell line.</a> Arch Dermatol Res. 291 (11), 600-605 (1999).</li><li>Laurent, T. C., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Diffusion+of+Dextran+in+Concentrated+Solutions.">Diffusion of Dextran in Concentrated Solutions.</a> Eur J Biochem. 68, 95-102 (1976).</li><li>Metzler, R., Klafter, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+random+walk's+guide+to+anomalous+diffusion:+A+fractional+dynamics+approach.">The random walk's guide to anomalous diffusion: A fractional dynamics approach.</a> Phys Rep. 339 (1), 1-77 (2000).</li></ol>

Uwe Marx is the CEO and a shareholder and Gerd Lindner is a shareholder of TissUse GmbH, a company manufacturing and commercializing the MOC technology. Other authors declare no conflict of interests regarding the publication of this paper.

This study documents a method developed to quantify permeation through a tissue-construct engineered on a membrane. Permeation of substances with varying molecular sizes through agarose gel was first examined to test and validate the method and the corresponding simulation. It is well known that smaller molecules permeate faster through a matrix mesh (with the exception of the effect in gel filtration by permeability chromatography). Similar observations were made with size-exclusion experiments of substances through sclera26, human epidermal membrane27, human skin17, and rat skin28. An inverse correlation between permeability coefficients and the corresponding Stokes radius (the radius of a hard sphere that moves with the same diffusion rate as the molecules described, usually smaller than the effective radius of the molecule) has been shown26,28, and a similar relationship was observed in experiments with substances of different molecular sizes. By plotting the permeability coefficients over 1/Stokes radius, a linear correlation over the four groups with the smallest molecular size was found (R2 = 0.93) (Figure 6). This indicates that simulated permeability coefficients with the method suggested are in a realistic range.
The error of 46.15% in the experiments is slightly larger than reported for permeability experiments with the Franz diffusion cell system10. One possible explanation could be the size distribution of fluorescein-isothiocyanate-dextran, which is discussed later.
The method described has important advantages compared with methods using the Franz diffusion cell system. Firstly, the setup is more compact; the experiments are executed directly in a membrane insert system, which has the scale of a commercial well plate (&#8764; 13 cm x 8.5 cm). This enables multiple samples to be run simultaneously, whereas a separate Franz diffusion cell is needed for each sample. Secondly, the permeability of a skin model can be directly measured in the membrane insert, where the cultivation takes place. Using Franz diffusion cells, the samples have to be taken out and mounted on the system, which is more cumbersome for small samples and is also more time-consuming.
Permeation experiments with collagen cell matrices showed that this method can be applied successfully to cell-seeded systems. The model presented here was verified for skin models; however, the method can be applied to other types of organic cell cultures, e.g., kidney or liver.
In this study, a collagen-cell model was used in which the HaCaT cells completely covered the model surface (see Figure 5). This led to a reduction of permeability coefficient, demonstrating that the method is sensitive enough to distinguish the permeability coefficient between a collagen-cell model with and without a layer of HaCaT. Ideally, a skin model should build up a barrier, which approaches the epidermis of a real skin29, and it is therefore important to verify the quality (e.g., building of dermis, epidermis) of the skin model before actual use. The development of a skin model can be visualized with staining techniques and quantified from the detection of skin protein and collagen30,31,32. The permeability coefficient may also be an important factor for assessing the development of the skin model, but further experiments are required to confirm this. As previously mentioned, this method enables running multiple samples in parallel. It is also possible to take samples during the cultivation to measure permeability, and thereby observe the development of this parameter of the skin model.
It should be noted that permeability is measured through a gel/collagen-cell-model and a membrane simultaneously. The detected permeability coefficient is system-specific, whereby the results of different skin models can only be compared when using the same membrane insert. Furthermore, the skin model needs to cover the entire cultivation area in order to ensure that the test substance will permeate only through the model and not adjacent to it, which would induce errors in the permeability measured. Another aspect that should be considered in future experiments is the natural environment surrounding the skin. Normally, the temperature of the skin surface is lower in comparison to the inner region, which can influence permeation conditions.
In order to align lab experiments with computer simulations, a method which enables parameter optimization for applied simulation was presented. Simulations were found to coincide well with experimental data for substances with small molecular sizes. However, deviations between simulation and experimental data were observed for substances with larger molecular sizes. Large polysaccharide molecules can increase friction and slow down the diffusion process in a gel. This effect causes abnormal diffusion, which is a possible reason for the deviation between experimental and simulation values33,34. Another explanation might be the presence of smaller or larger particles in fluorescein-isothiocyanate-dextran. The manufacturer specifies the molecular weight of the substance as the mean size with a given range, which allows smaller and larger particles to be present. It is also unclear how dispersed these substances are, as the smaller particles permeate faster through the gel and the fluid channel. It is possible to extend the simulation to consider these diffusion and friction effects.
The permeability experiment and simulation were developed for use in a 2-OC. With the help of the simulation, this experimental method can be directly transferred to more sophisticated experimental setups. For example, the membrane insert system simulation can easily be transferred to the geometry of a 2-OC or to other systems with similar set-ups. This option of modulating the simulation can be used to support the design of future experiments. In addition, side effects such as evaporation, abnormal diffusion, and membrane effects can be integrated to enhance the simulation, thereby improving accuracy. The simulation program gives the opportunity to change or enhance the simulation equation, as well as to integrate other physical modules in order to investigate other aspects of skin model development. One example is the simulation of glucose consumption and lactate production in a collagen cell model.
A particularly interesting aspect in the testing of medical substances is how the substances are distributed in an organ-on-a-chip system. The simulation and permeability parameter my help to answer questions such as how fast a substance permeates into the system as well as which concentration will be available for other tissues in a multi-organ-chip. This method can support and enhance the development and testing of such organ-on-chip systems.

Organo-typical 3D cultures have become powerful tools for drug development and substance testing1. In this respect, human skin models are of special interest due to regulatory requirements, such as those in the cosmetics industry. They have subsequently led to the development of numerous 3D skin models, for use either on their own as single-organ cultures in multi-well plates, or in multi-organ-chips in combination with additional organ models, e.g., the liver2.
With respect to cultivation of a skin equivalent, the air-liquid interface (ALI) is an essential element for proper epidermal differentiation3. Cell culture inserts composed of a vessel with a liquid-permeable membrane at the bottom are typically used to establish an ALI. ALIs are widely utilized in commercially available skin models such as EpiDerm4, Phenion5, and Episkin6, for the culture of skin models with sizes from 96-well (4.26 mm in diameter) up to 12-well (12.2 mm in diameter) plates. The method described here determines the permeation of substances in a membrane insert system.
The permeability coefficient is a significant parameter for evaluating the quality of any cultured skin-model compared to native skin5, and is used to assess how quickly active substances migrate through the skin. Especially if drugs or cosmetics products need to be applied to the skin, this parameter is essential to understand when precisely the active agents pass through it. A simulation can further help to predict the behavior of the system and to subsequently reduce the necessary time-consuming experimental effort, especially when a large set of substances is involved.
The Franz diffusion cell is state-of-the-art for permeation experiments with skin and skin models5,6,7,8,9. This device consists of two compartments with a fixed sample (diffusion barrier) in between. The substance to be tested is applied directly to the top of the sample (donor compartment) and the concentration of the permeating compound can be detected on the opposite (acceptor) compartment. On the acceptor side, constant temperature and homogeneous substance concentration are ensured through a temperature chamber and a magnetic stirrer. Samples can be taken from a sampling arm on the acceptor side of the Franz cell. With a height range between 19 cm and 179 cm, this system is relatively large10,11. Another method for determination of diffusion coefficients in gel-like substances and tissues is FRAP. This technique uses the principle of bleaching fluorescently labeled particles in the gel and then determining the recovery time of the bleached area to calculate the diffusion coefficient12,13,14.
Furthermore, Fourier-transform-infrared (FTIR) spectroscopy can be used to detect particle movement with infrared light absorbance in order to determine the permeation process of substances in skin15,16. However, these or other imaging methods (e.g., two-photon fluorescence correlation spectroscopy17) need cost intensive instruments.
In this article, a method is presented to directly measure the permeability of a barrier within a membrane insert system, where a skin model can be cultivated. This method enables permeability experiments to be run with a large number of small samples (well size up to 4.26 mm) in a compact system. This is in contrast to the Franz diffusion cell, where a separate device is needed for each probe, which has to be mounted on the device and is difficult to realize for small samples (size of 4.26 mm). Furthermore, since the method does not require major instrumentation (e.g., a confocal or multiphoton microscope), a reduction in both time and cost is achieved.
All the experiments were performed in microporous membrane insert systems with a sample (barrier) consisting of agarose gel or a collagen cell model established on the membrane. Fluorescent substances (donor) with varying molecular sizes were applied to the top of the sample, and the concentration of permeated substance was detected on the bottom (acceptor) using a fluorescence plate reader (see Figure 1). In order to validate the method and test the accuracy of this simulation, agarose gels were produced and used as a barrier. Hydrogels are generally used for the investigation of diffusion and permeation processes in porous medium in the biological sciences13. The method was then tested in a cell-seeded system consisting of a collagen matrix of primary fibroblasts and Human adult low Calcium high Temperature keratinocytes (HaCaT) cells (cell-matrix model), which is a simplified skin model18,19.
Additionally, the permeation process was simulated by means of flow simulations with computational fluid dynamics. It was found that, by means of parameter optimization, the diffusion coefficient could be calculated from the experimental data. In general, this simulation offers different applications; for instance, it is possible to predict a permeation process based on short experiments and the simulation can significantly reduce the number of experiments.
Experimental method and simulation were designed for application to an organ-on-a-chip system1,20,21, specifically the 2-organ-chip (2-OC) developed commercially1,22,23,24,25. In principle, the permeation process of any organ model based on membrane insert systems can be described in this way.

<table><tbody><tr><td>Agarose</td><td>Carl Roth</td><td>K297.2</td><td>High Resolution Powder</td></tr><tr><td>Collagen</td><td>Serva</td><td>47256.01</td><td>Collagen R solution 0.4 %</td></tr><tr><td>DMEM</td><td>Lonza (Biozym Scientific GmbH)</td><td>880010-12</td><td>High Glucose with L-Glutamine</td></tr><tr><td>FCS</td><td>Biochrom GmbH</td><td>S0615 0114F</td><td>Fetal Calf Serum</td></tr><tr><td>Fluorescein Sodium Salt</td><td>Sigma-Aldrich</td><td>46960-25G-F</td><td></td></tr><tr><td>Fluorescein Isothiocyanate-dextran</td><td>Sigma-Aldrich</td><td>46944-500MG</td><td>4000 g/mol</td></tr><tr><td>Fluorescein Isothiocyanate-dextran</td><td>Sigma-Aldrich</td><td>FD10S-250MG</td><td>10 000 g/mol</td></tr><tr><td>Fluorescein Isothiocyanate-dextran</td><td>Sigma-Aldrich</td><td>FD20S-250MG</td><td>20 000 g/mol</td></tr><tr><td>Fluorescein Isothiocyanate-dextran</td><td>Sigma-Aldrich</td><td>FD40S-250MG</td><td>40 000 g/mol</td></tr><tr><td>HBSS</td><td>ThermoFisher Scientific</td><td>14170120</td><td>no calcium, no magnesium , with phenol red</td></tr><tr><td>NaOH</td><td>Merck</td><td>1.06467.9010</td><td>granulated</td></tr><tr><td>PBS</td><td>Gibco</td><td>18912-014</td><td>tablets</td></tr><tr><td>Transwell Cell Culture Inserts</td><td>Corning</td><td>3391</td><td>96 well, 0.4 &amp;micro;m pore size</td></tr><tr><td>Transwell Cell Culture Inserts</td><td>Corning (VWR)</td><td>734-1563</td><td>12 well, 0.4 &amp;micro;m pore size</td></tr><tr><td>Trypsin</td><td>Biochrom GmbH</td><td>L2143</td><td>with EDTA</td></tr></tbody></table>

a method for determination and simulation of permeability and diffusion in a 3d tissue model in a membrane insert system for multi-well plates

In vitro cultivated skin models have become increasingly relevant for pharmaceutical and cosmetic applications, and are also used in drug development as well as substance testing. These models are mostly cultivated in membrane-insert systems, their permeability toward different substances being an essential factor. Typically, applied methods for determination of these parameters usually require large sample sizes (e.g., Franz diffusion cell) or laborious equipment (e.g., fluorescence recovery after photobleaching (FRAP)). This study presents a method for determining permeability coefficients directly in membrane-insert systems with diameter sizes of 4.26 mm and 12.2 mm (cultivation area). The method was validated with agarose and collagen gels as well as a collagen cell model representing skin models. The permeation processes of substances with different molecular sizes and permeation through different cell models (consisting of collagen gel, fibroblast, and HaCaT) were accurately described.
Moreover, to support the above experimental method, a simulation was established. The simulation fits the experimental data well for substances with small molecular size, up to 14 x 10-10 m Stokes radius (4,000 MW), and is therefore a promising tool to describe the system. Furthermore, the simulation can considerably reduce experimental efforts and is robust enough to be extended or adapted to more complex setups.

Permeability experiments in a 96-well membrane insert system with 2% agarose gel as a barrier were conducted in order to evaluate the accuracy of a simulation. Fluorescein sodium salt (NaFl) and fluorescein isothiocyanate-dextranes (FD) were used to verify the impact of the molecular size of the diffusing substance from 5 x 10-10 m up to 45 x 10-10 m Stokes radius (376.27-40,000 mol wt). The simulation&#39;s native parameter optimization was used to fit the simulation to experimental data.
To that end, slopes of only the linear parts of the simulated permeability were compared to the experimental outcomes. For small molecular sizes, simulation and experimental data were in good agreement with 99.2% for NaFl and 80.2% for FD 4,000 (see Figure 4a and Figure 4b). Larger molecular size generated higher deviations showing correlations of 50.5% for FD 10,000, 79.7% for FD 20,000, and 53.6% for FD 40,000. Curve progression in the simulations showed a delay at the beginning and a stronger rise in the further course of the graphs (see Figure 4c-4e).
Permeability coefficients and simulated diffusion coefficients are shown in Table 4. The permeation coefficient decreases with increasing molecular size. Standard deviation was between 0.08 x 10-8 m/s and 0.47 x 10-8 m/s (N = 7), which corresponded to an absolute error of between 4.18% and 46.15%. Experiments with larger molecules showed a larger absolute error. The simulated diffusion coefficients behaved very similarly to experimental permeability coefficients. Substances with larger Stokes radii showed decreasing diffusion coefficients, and the absolute error ranged between 9.09% and 18.46% (N = 3).
In additional permeation experiments, four different collagen cell model types were used as barriers in a 12-well membrane insert system. These models comprise a cell-free model and a cell model with different combinations of primary fibroblasts in the collagen gel and HaCaT on the surface. The following combinations were used: Collagen (Col.) as a cell-free model, Collagen + Fibroblasts (Col.+F.), Collagen + HaCaT (Col.+H.), and Collagen + Fibroblasts + HaCaT (Col.+F.+H.). Fluorescein sodium salt with DMEM + 10% FCS was used as donor substance. For image analysis of the collagen cell model, staining with hematoxylin and eosin (HE) was used. This staining was done using the manufacturer&#39;s protocol. In Figure 5, such a stain with a representative Col.+F.+H. model is shown. The HE slightly stains the tissue structure of the collagen matrix. The fibroblasts are located in the matrix, and the nuclei of the fibroblast and HaCaT cells are stained in dark violet. On top of the collagen matrix, there is a layer containing many nuclei, which should be the nuclei of the HaCaTs, building an enclosing layer on the top of the model.
In Table 5, experimental permeation coefficients and simulated diffusion coefficients are listed. A trend can be seen for most of the models with HaCaT, which have lower permeation/diffusion coefficients in comparison to the models without HaCaT. The absolute error of the permeation coefficients is 10.9-24.4%, and for the diffusion coefficients 5.2%-12.9%.
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/56412/56412fig1.jpg" /> 
Figure 1: Side view of the permeability experiment in a membrane insert system. <a href="https://cloudflare.jove.com/files/ftp_upload/56412/56412fig1large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 2" class="xfigimg" src="/files/ftp_upload/56412/56412fig2.jpg" /> 
Figure 2: Exemplary graph of a permeability experiment. The concentration of the acceptor is plotted over time. Two dashed lines bracket the nearly linear part of the graph. The slope of the linear part is used to determine the permeability coefficient. <a href="https://cloudflare.jove.com/files/ftp_upload/56412/56412fig2large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 3" class="xfigimg" src="/files/ftp_upload/56412/56412fig3.jpg" /> 
Figure 3: Geometry and mesh of the membrane insert system in the simulation. (a) Geometry of the 96-well membrane insert system. (b) Geometry of the 12-well membrane insert system. (c) Mesh of the 96-well membrane insert system. (d) Mesh of the 12-well membrane insert system. (e) Cross-section and parameters of the membrane insert system. <a href="https://cloudflare.jove.com/files/ftp_upload/56412/56412fig3large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 4" class="xfigimg" src="/files/ftp_upload/56412/56412fig4.jpg" /> 
Figure 4: Comparison of the experimental data from a permeation experiment to the optimized simulation. (a) fluorescein sodium salt, (b) fluorescein isothiocyanate-dextran 4,000 mol wt., (c) 10,000 mol wt., (d) 20,000 mol wt., and (e) 40,000 mol wt. <a href="https://cloudflare.jove.com/files/ftp_upload/56412/56412fig4large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 5" class="xfigimg" src="/files/ftp_upload/56412/56412fig5.jpg" /> 
Figure 5: Representative HE staining of a collagen cell model (Collagen + Fibroblasts + HaCaT). <a href="https://cloudflare.jove.com/files/ftp_upload/56412/56412fig5large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 6" class="xfigimg" src="/files/ftp_upload/56412/56412fig6.jpg" /> 
Figure 6: Permeability coefficient as a function of the 1/Stokes radius using fluorescein sodium salt and fluorescein isothiocyanate-dextran in a 96-well membrane insert system. <a href="https://cloudflare.jove.com/files/ftp_upload/56412/56412fig6large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>Name</td>
			<td>Experession for 96 well System in mm</td>
			<td>Experssion for 12-well System in mm</td>
			<td>Description</td>
		</tr>
		<tr>
			<td>d_tran</td>
			<td>5.65 [mm]</td>
			<td>14.7 [mm]</td>
			<td>Diameter of the well</td>
		</tr>
		<tr>
			<td>d_a</td>
			<td>4.26 [mm]</td>
			<td>12.1 [mm]</td>
			<td>Diameter of the Membrane</td>
		</tr>
		<tr>
			<td>d_w</td>
			<td>8.79 [mm]</td>
			<td>21.97 [mm]</td>
			<td>Diameter of the Acceptor</td>
		</tr>
		<tr>
			<td>h_b</td>
			<td>2 [mm]</td>
			<td>2 [mm]</td>
			<td>Heigh of the Barrier</td>
		</tr>
		<tr>
			<td>h_sp</td>
			<td>1 [mm]</td>
			<td>1 [mm]</td>
			<td>Distance between well and Bottom</td>
		</tr>
		<tr>
			<td>h_a</td>
			<td>4.73 [mm]</td>
			<td>5.24 [mm]</td>
			<td>High of the Acceptor</td>
		</tr>
		<tr>
			<td>b</td>
			<td>h_b/2</td>
			<td>-</td>
			<td>Immersion Depth</td>
		</tr>
		<tr>
			<td>r</td>
			<td>((d_a)^2+4*b^2)/(8*b)</td>
			<td>-</td>
			<td>Radius of Immersion Ball+</td>
		</tr>
		<tr>
			<td>r_z</td>
			<td>r+h_b</td>
			<td>-</td>
			<td>z-Position of the Immersion Ball+</td>
		</tr>
	</tbody>
</table>
Table 1: Geometry parameters for &#34;Chemical Species Transport&#34; simulation. +Only to be used for the simulation of agarose gel in 96 well membrane insert system.
<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>Name</td>
			<td>Expression</td>
			<td>Value</td>
			<td>Description</td>
		</tr>
		<tr>
			<td>C_fl</td>
			<td>0.1 [mg/ml]/376.28 [g/mol]</td>
			<td>0.26576 mol/m2</td>
			<td>Concentration of Fl.So.</td>
		</tr>
		<tr>
			<td>C_4</td>
			<td>2 [mg/ml]/4000 [g/mol]</td>
			<td>0.5 mol/m2</td>
			<td>Concentration of FD 4.000</td>
		</tr>
		<tr>
			<td>C_10</td>
			<td>2 [mg/ml]/10000 [g/mol]</td>
			<td>0.2 mol/m2</td>
			<td>Concentration of FD 10.000</td>
		</tr>
		<tr>
			<td>C_20</td>
			<td>2 [mg/ml]/20000 [g/mol]</td>
			<td>0.1 mol/m2</td>
			<td>Concentration of FD 20.000</td>
		</tr>
		<tr>
			<td>C_40</td>
			<td>2 [mg/ml]/40000 [g/mol]</td>
			<td>0.05 mol/m2</td>
			<td>Concentration of FD 40.000</td>
		</tr>
		<tr>
			<td>Dif_w</td>
			<td>1e-9 [m^2/s]</td>
			<td>1E-9m2/s</td>
			<td>Diffusion Coefficient of mixing water</td>
		</tr>
	</tbody>
</table>
Table 2: Physical parameters for &#34;Chemical Species Transport&#34; simulation.
<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>Name</td>
			<td>Expression</td>
			<td>Description</td>
		</tr>
		<tr>
			<td>C</td>
			<td>Acceptor(c)</td>
			<td>Definition of the acceptor concentration</td>
		</tr>
		<tr>
			<td>D</td>
			<td>D_search*1e-10</td>
			<td>Factor change for D</td>
		</tr>
	</tbody>
</table>
Table 3: Parameters for &#34;Optimization&#34; simulation.
<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>Permeate</td>
			<td>Permeability coefficient (m/s)x10-8</td>
			<td>Diffusion coefficient (m/s2)x10-10</td>
			<td>Stokes radius of permeate (m)x10-10</td>
		</tr>
		<tr>
			<td>Fl.So.</td>
			<td>4.79 &#177; 0.20</td>
			<td>1.94 &#177; 0.34</td>
			<td>5</td>
		</tr>
		<tr>
			<td>FD 4,000</td>
			<td>2.37 &#177; 0.31</td>
			<td>0.65 &#177; 0.12</td>
			<td>14</td>
		</tr>
		<tr>
			<td>FD10,000</td>
			<td>1.67 &#177; 0.47</td>
			<td>0.22 &#177; 0.02</td>
			<td>23</td>
		</tr>
		<tr>
			<td>FD 20,000</td>
			<td>0.65 &#177; 0.30</td>
			<td>0.29 &#177; 0.04</td>
			<td>33</td>
		</tr>
		<tr>
			<td>FD 40,000</td>
			<td>0.27 &#177; 0.08</td>
			<td>0.14 &#177; 0.02</td>
			<td>45</td>
		</tr>
	</tbody>
</table>
Table 4: Permeability and diffusion coefficient of substances with different Stokes radius through 2% Agarose gel + membrane in a 96-well membrane insert system. (fluorescein sodium salt = Fl. So., fitc dextran = FD).
<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>Model</td>
			<td>Permeability coefficient (m/s)x10-8</td>
			<td>Diffusion coefficient (m/s2)x10-10</td>
		</tr>
		<tr>
			<td>Col.</td>
			<td>2.18 &#177; 0.29</td>
			<td>1.22 &#177; 0.06</td>
		</tr>
		<tr>
			<td>Col.+F.</td>
			<td>1.77 &#177; 0.38</td>
			<td>0.93 &#177; 0.12</td>
		</tr>
		<tr>
			<td>Col.+H.</td>
			<td>1.64 &#177; 0.40</td>
			<td>0.96 &#177; 0.05</td>
		</tr>
		<tr>
			<td>Col.+F.+H.</td>
			<td>1.65 &#177; 0.18</td>
			<td>0.88 &#177; 0.11</td>
		</tr>
	</tbody>
</table>
Table 5: Permeability and diffusion coefficient of fluorescein sodium salt through a collagen cell model in a 12-well membrane insert system (Col. = Collagen, F. = Fibroblast, H. = HaCaT).

Watch this Scientific Journal Video about A Method for Determination and Simulation of Permeability and Diffusion in a 3D Tissue Model in a Membrane Insert System for Multi-well Plates at JoVE.com

A Method for Determination and Simulation of Permeability and Diffusion in a 3D Tissue Model in a Membrane Insert System for Multi-well Plates

A method for determination of permeability in a membrane insert system for multi-well plates and in silico parameter optimization for the calculation of diffusion coefficients using simulation are presented.

In vitro cultivated skin models have become increasingly relevant for pharmaceutical and cosmetic applications, and are also used in drug development as ...

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Research

JoVE Journal

Bioengineering

25.1K Views.  Hamburg University of Technology. A method for determination of permeability in a membrane insert system for multi-well plates and in silico parameter optimization for the calculation of diffusion coefficients using simulation are presented.

Video: A Method for Determination and Simulation of Permeability and Diffusion in a 3D Tissue Model in a Membrane Insert System for Multi-well Plates

A Mimic of the Tumor Microenvironment: A Simple Method for Generating Enriched Cell Populations and Investigating Intercellular Communication

Understanding the early heterotypic interactions between cancer cells and the surrounding non-cancerous stroma is important in elucidating the events leading to stromal activation and establishment of the tumor microenvironment (TME). Several in vitro and in vivo models of the TME have been developed; however, in general these models do not readily permit isolation of individual cell populations, under non-perturbing conditions, for further study. To circumvent this difficulty, we have employed an in vitro TME model using a cell growth substrate consisting of a permeable microporous membrane insert that permits simple generation of highly enriched cell populations grown intimately, yet separately, on either side of the insert&#39;s membrane for extended co-culture times. Through use of this model, we are capable of generating greatly enriched cancer-associated fibroblast (CAF) populations from normal diploid human fibroblasts following co-culture (120 hr) with highly metastatic human breast carcinoma cells, without the use of fluorescent tagging and/or cell sorting. Additionally, by modulating the pore-size of the insert, we can control for the mode of intercellular communication (e.g., gap-junction communication, secreted factors) between the two heterotypic cell populations, which permits investigation of the mechanisms underlying the development of the TME, including the role of gap-junction permeability. This model serves as a valuable tool in enhancing our understanding of the initial events leading to cancer-stroma initiation, the early evolution of the TME, and the modulating effect of the stroma on the responses of cancer cells to therapeutic agents.

We adapted a permeable microporous membrane insert to mimic the tumor microenvironment (TME). The model consists of a mixed cell culture, allows simplified generation of highly enriched individual cell populations without using fluorescent tagging or cell sorting, and permits studying intercellular communication within the TME under normal or stress conditions.

Understanding the early heterotypic interactions between cancer cells and the surrounding non-cancerous stroma is important in elucidating the events ...

Cancer Research

Three-dimensional Cell Culture Model for Measuring the Effects of Interstitial Fluid Flow on Tumor Cell Invasion

The growth and progression of most solid tumors depend on the initial transformation of the cancer cells and their response to stroma-associated signaling in the tumor microenvironment 1. Previously, research on the tumor microenvironment has focused primarily on tumor-stromal interactions 1-2. However, the tumor microenvironment also includes a variety of biophysical forces, whose effects remain poorly understood. These forces are biomechanical consequences of tumor growth that lead to changes in gene expression, cell division, differentiation and invasion3. Matrix density 4, stiffness 5-6, and structure 6-7, interstitial fluid pressure 8, and interstitial fluid flow 8 are all altered during cancer progression.
Interstitial fluid flow in particular is higher in tumors compared to normal tissues 8-10. The estimated interstitial fluid flow velocities were measured and found to be in the range of 0.1-3 &mu;m s-1, depending on tumor size and differentiation 9, 11. This is due to elevated interstitial fluid pressure caused by tumor-induced angiogenesis and increased vascular permeability 12. Interstitial fluid flow has been shown to increase invasion of cancer cells 13-14, vascular fibroblasts and smooth muscle cells 15. This invasion may be due to autologous chemotactic gradients created around cells in 3-D 16 or increased matrix metalloproteinase (MMP) expression 15, chemokine secretion and cell adhesion molecule expression 17. However, the mechanism by which cells sense fluid flow is not well understood. In addition to altering tumor cell behavior, interstitial fluid flow modulates the activity of other cells in the tumor microenvironment. It is associated with (a) driving differentiation of fibroblasts into tumor-promoting myofibroblasts 18, (b) transporting of antigens and other soluble factors to lymph nodes 19, and (c) modulating lymphatic endothelial cell morphogenesis 20.
The technique presented here imposes interstitial fluid flow on cells in vitro and quantifies its effects on invasion (Figure 1). This method has been published in multiple studies to measure the effects of fluid flow on stromal and cancer cell invasion 13-15, 17. By changing the matrix composition, cell type, and cell concentration, this method can be applied to other diseases and physiological systems to study the effects of interstitial flow on cellular processes such as invasion, differentiation, proliferation, and gene expression.

Interstitial fluid flow is elevated in solid tumors and can modulate tumor cell invasion. Here we describe a technique to apply interstitial fluid flow to cells embedded in a matrix and then measure its effects on cell invasion. This technique can be easily adapted to study other systems.

The growth and progression of most solid tumors depend on the initial transformation of the cancer cells and their response to stroma-associated signaling ...

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. ...

Improved Method for the Preparation of a Human Cell-based, Contact Model of the Blood-Brain Barrier

The blood-brain barrier (BBB) comprises impermeable but adaptable brain capillaries which tightly control the brain environment. Failure of the BBB has been implied in the etiology of many brain pathologies, creating a need for development of human in vitro BBB models to assist in clinically-relevant research. Among the numerous BBB models thus far described, a static (without flow), contact BBB model, where astrocytes and brain endothelial cells (BECs) are cocultured on the opposite sides of a porous membrane, emerged as a simplified yet authentic system to simulate the BBB with high throughput screening capacity. Nevertheless the generation of such model presents few technical challenges. Here, we describe a protocol for preparation of a contact human BBB model utilizing a novel combination of primary human BECs and immortalized human astrocytes. Specifically, we detail an innovative method for cell-seeding on inverted inserts as well as specify insert staining techniques and exemplify how we use our model for BBB-related research.

Establishment of human models of the blood-brain barrier (BBB) can benefit research into brain conditions associated with BBB failure. We describe here an improved technique for preparation of a contact BBB model, which permits coculturing of human astrocytes and brain endothelial cells on the opposite sides of a porous membrane.

The blood-brain barrier (BBB) comprises impermeable but adaptable brain capillaries which tightly control the brain environment. Failure of the BBB has ...

Implementation of a Permeable Membrane Insert-based Infection System to Study the Effects of Secreted Bacterial Toxins on Mammalian Host Cells

Many bacterial pathogens secrete potent toxins to aid in the destruction of host tissue, to initiate signaling changes in host cells or to manipulate immune system responses during the course of infection. Though methods have been developed to successfully purify and produce many of these important virulence factors, there are still many bacterial toxins whose unique structure or extensive post-translational modifications make them difficult to purify and study in in vitro systems. Furthermore, even when pure toxin can be obtained, there are many challenges associated with studying the specific effects of a toxin under relevant physiological conditions. Most in vitro cell culture models designed to assess the effects of secreted bacterial toxins on host cells involve incubating host cells with a one-time dose of toxin. Such methods poorly approximate what host cells actually experience during an infection, where toxin is continually produced by bacterial cells and allowed to accumulate gradually during the course of infection. This protocol describes the design of a permeable membrane insert-based bacterial infection system to study the effects of Streptolysin S, a potent toxin produced by Group A Streptococcus, on human epithelial keratinocytes. This system more closely mimics the natural physiological environment during an infection than methods where pure toxin or bacterial supernatants are directly applied to host cells. Importantly, this method also eliminates the bias of host responses that are due to direct contact between the bacteria and host cells. This system has been utilized to effectively assess the effects of Streptolysin S (SLS) on host membrane integrity, cellular viability, and cellular signaling responses. This technique can be readily applied to the study of other secreted virulence factors on a variety of mammalian host cell types to investigate the specific role of a secreted bacterial factor during the course of infection.

Here, a method using a permeable membrane insert-based infection system to study the effects of Streptolysin S, a secreted toxin produced by Group A Streptococcus, on keratinocytes is described. This system can be readily applied to the study of other secreted bacterial proteins on various host cell types during infection.

Many bacterial pathogens secrete potent toxins to aid in the destruction of host tissue, to initiate signaling changes in host cells or to manipulate ...

Immunology and Infection

Analyzing the Permeability of the Blood-Brain Barrier by Microbial Traversal through Microvascular Endothelial Cells

The human blood-brain barrier (BBB) is characterized by a very low permeability for biomolecules in order to protect and regulate the metabolism of the brain. The BBB is mainly formed out of endothelial cells embedded in collagen IV and fibronectin-rich basement membranes. Several pathologies result from dysfunction of the BBB followed by microbial traversal, causing diseases such as meningitis. In order to test the effect of multiple parameters, including different drugs and anesthetics, on the permeability of the BBB we established a novel human cell culture model mimicking the BBB with human brain microvascular endothelial cells. The endothelial cells are grown on collagen IV and fibronectin-coated filter units until confluence and can then be treated with different compounds of interest. In order to demonstrate a microbial traversal, the upper chamber with the apical surface of the endothelial cells is inoculated with bacteria. After an incubation period, samples of the lower chamber are plated on agar plates and the obtained colonies are counted, whereby the number of colonies correlate with the permeability of the BBB. Endogenous cellular factors can be analyzed in this experimental set-up in order to elucidate basic cellular mechanisms of the endothelial cells contributing to the BBB. In addition, this platform allows performing a screen for compounds that might affect the permeability of the endothelial cells. Finally, bacterial traversal can be studied and linked to different pathologies, such as meningitis. It might be possible to extend the model and analyze the pathways of the bacteria through the BBB. In this article, we provide a detailed protocol of the described method to investigate the permeability of the BBB.

The human blood-brain barrier selectively prevents penetration of hydrophilic molecules and pathogens into the brain. Several pathologies, including meningitis and postoperative delirium, are associated with an increased permeability of the blood-brain barrier. Here, we describe an endothelial cell culture model to test the barrier permeability by microbial traversal.

The human blood-brain barrier (BBB) is characterized by a very low permeability for biomolecules in order to protect and regulate the metabolism of the ...

Analysis of Blood-Brain Barrier Models via Immunofluorescence Staining

Use of the MicroSiM (&#181;SiM) Barrier Tissue Platform for Modeling the Blood-Brain Barrier

The microSiM (&#181;SiM) is a membrane-based culture platform for modeling the blood-brain barrier (BBB). Unlike conventional membrane-based platforms, the&#160;&#181;SiM provides experimentalists with new capabilities, including live cell imaging, unhindered paracrine signaling between &#39;blood&#39; and &#39;brain&#39; chambers, and the ability to directly image immunofluorescence without the need for the extraction/remounting of membranes. Here we demonstrate the basic use of the platform to establish monoculture (endothelial cells) and co-culture (endothelial cells and pericytes) models of the BBB using ultrathin nanoporous silicon-nitride membranes. We demonstrate compatibility with both primary cell cultures and human induced pluripotent stem cell (hiPSC) cultures. We provide methods for qualitative analysis of BBB models via immunofluorescence staining and demonstrate the use of the &#181;SiM for the quantitative assessment of barrier function in a small molecule permeability assay. The methods provided should enable users to establish their barrier models on the platform, advancing the use of tissue chip technology for studying human tissues.

Author Spotlight: Advancing the Use of Tissue Chip Technology for Studying Human Tissues 

This report provides protocols for assembly, cell culture, and assays on the &#181;SiM platform for the construction of blood-brain barrier models.

The microSiM (&#181;SiM) is a membrane-based culture platform for modeling the blood-brain barrier (BBB). Unlike conventional membrane-based platforms, ...

A Reconfigurable Barrier Tissue Platform with Open-Well and Microfluidic Modes

Transforming Static Barrier Tissue Models into Dynamic Microphysiological Systems

Microphysiological systems are miniaturized cell culture platforms used to mimic the structure and function of human tissues in a laboratory setting. However, these platforms have not gained widespread adoption in bioscience laboratories where open-well, membrane-based approaches serve as the gold standard for mimicking tissue barriers, despite lacking fluid flow capabilities. This issue can be primarily attributed to the incompatibility of existing microphysiological systems with standard protocols and tools developed for open-well systems.
Here, we present a protocol for creating a reconfigurable membrane-based platform with an open-well structure, flow enhancement capability, and compatibility with conventional protocols. This system utilizes a magnetic assembly approach that enables reversible switching between open-well and microfluidic modes. With this approach, users have the flexibility to begin an experiment in the open-well format using standard protocols and add or remove flow capabilities as needed. To demonstrate the practical usage of this system and its compatibility with standard techniques, an endothelial cell monolayer was established in an open-well format. The system was reconfigured to introduce fluid flow and then switched to the open-well format to conduct immunostaining and RNA extraction. Due to its compatibility with conventional open-well protocols and flow enhancement capability, this reconfigurable design is expected to be adopted by both engineering and bioscience laboratories.

Author Spotlight: Developing a Unique Modular Microphysiological System to Mimic Human Barrier Tissue

This protocol describes a reconfigurable membrane-based cell culture platform that integrates the open-well format with fluid flow capabilities. This platform is compatible with standard protocols and allows for reversible transitions between open-well and microfluidic culture modes, accommodating the needs of both engineering and bioscience laboratories.

Microphysiological systems are miniaturized cell culture platforms used to mimic the structure and function of human tissues in a laboratory setting. ...

3D Bioprinting for Rapid Vascular Network Fabrication Using Vessels-on-a-Plate

High-Throughput Bioprinting Method for Modeling Vascular Permeability in Standard Six-well Plates with Size and Pattern Flexibility

Vascular permeability is a key factor in developing therapies for disorders associated with compromised endothelium, such as endothelial dysfunction in coronary arteries and impaired function of the blood-brain barrier. Existing fabrication techniques do not adequately replicate the geometrical variation in vascular networks in the human body, which substantially influences disease progression; moreover, these techniques often involve multi-step fabrication procedures that hinder the high-throughput production necessary for pharmacological testing. This paper presents a bioprinting protocol for creating multiple vascular tissues with desired patterns and sizes directly on standard six-well plates, overcoming existing resolution and productivity challenges in bioprinting technology. A simplified fabrication approach was established to construct six hollow, perfusable channels within a hydrogel, which were subsequently lined with human umbilical vein endothelial cells to form a functional and mature endothelium. The computer-controlled nature of 3D bioprinting ensures high reproducibility and requires fewer manual fabrication steps than traditional methods. This highlights VOP's potential as an efficient high-throughput platform for modeling vascular permeability and advancing drug discovery.

Author Spotlight: Automated Bioprinting for High-Throughput Vascular Model Fabrication

We present a protocol for high-throughput production of vascular channels with flexible sizes and desired patterns on a standard six-well plate using 3D bioprinting technology, referred to as vessels-on-a-plate (VOP). This platform has the potential to advance the development of therapeutics for the disorders associated with compromised endothelium.

Vascular permeability is a key factor in developing therapies for disorders associated with compromised endothelium, such as endothelial dysfunction in ...

Construction of a 3D Intestinal Mucosa Model with Paraffin Embedding

Basic Three-Dimensional (3D) Intestinal Model System with an Immune Component

There has been an increase in the use of in vivo and in vitro intestinal models to study the pathophysiology of inflammatory intestinal diseases, for the pharmacological screening of potentially beneficial substances, and for toxicity studies on potentially harmful food components. Of relevance, there is a current demand for the development of cell-based in vitro models to substitute animal models. Here, a protocol for a basic, &#8220;healthy tissue&#8221; three-dimensional (3D) intestinal equivalent model using cell lines is presented with the dual benefit of providing both experimental simplicity (standardized and easily repeatable system) and physiological complexity (Caco-2 enterocytes with a supporting immune component of U937 monocytes and L929 fibroblasts). The protocol also includes paraffin embedding for light microscopic evaluation of fixed intestinal equivalents, thereby providing the advantage of analyzing multiple visual parameters from a single experiment. Hematoxylin and eosin (H&#38;E) stained sections showing the Caco-2 columnar cells forming a tight and regular monolayer in control treatments are used to verify the efficacy of the model as an experimental system. Using gluten as a pro-inflammatory food component, parameters analyzed from sections include reduced monolayer thickness, as well as disruption and detachment from the underlying matrix (H&#38;E), decreased tight junction protein expression as shown from occludin staining (quantifiable statistically), and immune-activation of migrating U937 cells as evidenced from the cluster of differentiation 14 (CD14) staining and CD11b-related differentiation into macrophages. As shown by using lipopolysaccharide to simulate intestinal inflammation, additional parameters that can be measured are increased mucus staining and cytokine expression (such as midkine) that can be extracted from the medium prior to fixation. The basic three-dimensional (3D) intestinal mucosa model and fixed sections can be recommended for inflammatory status and barrier integrity studies with the possibility of analyzing multiple visual quantifiable parameters.

Author Spotlight: Investigating the Effects of Compounds on Intestinal Tissue Using 3D Human Cell Line Models 

Here we describe constructing a basic three-dimensional (3D) intestinal cell line model system and a paraffin embedding protocol for light microscopic evaluation of fixed intestinal equivalents. Staining of selected proteins permits the analysis of multiple visual parameters from a single experiment for potential use in preclinical drug screening studies.

There has been an increase in the use of in vivo and in vitro intestinal models to study the pathophysiology of inflammatory intestinal diseases, for the ...

A Method for Determination and Simulation of Permeability and Diffusion in a 3D Tissue Model in a Membrane Insert System for Multi-well Plates

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