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Technische Universität München

Upscaling Assays on 3D Cell Models

Organoids derived from a pancreatic tumor cell line, growing as 3D entities in a dome of basement membrane extract (bme). The organoid cell mass may contribute up to 50% of the total volume of bme.

In a collaborative project with Nanion Technologies (https://www.nanion.de/) and the Max Reichert group at TUM hospital (https://www.med2.mri.tum.de/de/team/cv/reichert_cv.php) we investigate Printed Circuit Board (PCB) technologies for their suitability to achieve a sensor-based readout of 3D cell models such as spheroids or organoids (Projektträger Bayern, PBN-LSM-2104-0003).

One of the most beneficial features of a sensor-based, kinetic data readout is the ability to monitor the condition of 3D cell models individually and throughout the entire growth and drug incubation period. In contrast to endpoint measurements this allows additional longitudinal observations.

Photograph image of a 96 well test plate with a PCB bottom featuring gold-plated electrodes (in cooperation with Nanion Technologies)

Multilayer PCB technology offers high-density integration of electrode structures for electric impedance recordings, industrial upscaling with low product costs and biocompatible assemblies.

Finite Element Modelling of spatial distributions of electric potentials and currents in heterogeneous 3D geometries is used to optimize geometries with respect to their sensitivity towards the detection of impedance alterations in specified objects under test.

The planning of PCB design usually starts with virtual prototyping, where different kinds of electrode setups and geometries are tested as finite element models.

With an altered electric field distribution due to an active “guardring electrode” adjacent to the working electrode, an increased share of working electrode current lines (in red) passes through the 3D object of interest to the counter electrode. Depending on the geometry of measurement, the result is an enhanced sensitivity of detecting biological changes.

One of the challenges of measuring the electric impedance of 3D culture objects is to guide electric currents through the 3D objects of interest and to avoid bypassing of high-impedance volumes. To achieve that we use “guardring electrodes” equipotential to the measuring working electrodes. 
 

While high frequency currents (blue arrows) cross the tissue without being affected by cellular structures, the electric impedance to lower frequency (<10 – 100 kHz) currents (red arrows) is sensitive to such changes.

Electric impedance measured in-vitro on 3D cellular structures in the 10 kHz frequency range will respond to changes of bulk electrical conductivity and structural changes related to alterations of cell-cell connections and cell membrane integrity or to increasing cell mass. 

 

Schematic of a water-in-water droplet microfluidic device to encapsulate cell samples; A cell suspension in the NaCS- (sodium cellulose sulfate-) containing disperse phase forms droplets of ≈ 350 µm size in the first step which are stabilized by polyelectrolyte complexation in the second step. DEX: dextrane in the disperse phase, PEG: polyethyleneglycol in the continuous phase; PDADMAC: poly (diallyl dimethyl ammonium chloride, the positively charged polyelectrolyte), PBS: phosphate buffered saline

For clinical translation, the processing of small-sized patient-derived cell samples is paramount. One of the options to transform small cell samples into a screening-compatible format is the encapsulation of cells by adapting an FDA-approved workflow (http://www.austrianova.com) to a microfluidic aqueous-two-phase system.

Cell droplets arrive at the microfluidic junction where polyelectrolyte complexation takes place by inflow of PDADMAC. After washing the resulting core-shell capsules are transferred into test plates for cell assays.

3D cell models prepared e.g. from cancer patient-derived cells can be packaged and used as “in vitro avatars” (e.g. representing a tumor) for functional “precision oncology” assays as a part of clinical trials – with the aim to better define personalized cancer treatments. Practical screening workflows must account for aspects such as throughput, costs and diagnostic accuracy. 

 

Contact: Dr. Martin Brischwein, brischwein@tum.de

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