Smart Cell Culture Systems: Integration of Sensors and Actuators into Microphysiological Systems

Abstract

Technological advances in microfabrication techniques in combination with organotypic cell and tissue models have enabled the realization of microphysiological systems capable of recapitulating aspects of human physiology in vitro with great fidelity. Concurrently, a number of analysis techniques has been developed to probe and characterize these model systems. However, many assays are still performed off-line, which severely compromises the possibility of obtaining real-time information from the samples under examination, and which also limits the use of these platforms in high-throughput analysis. In this review, we focus on sensing and actuation schemes that have already been established or offer great potential to provide in situ detection or manipulation of relevant cell or tissue samples in microphysiological platforms. We will first describe methods that can be integrated in a straightforward way and that offer potential multiplexing and/or parallelization of sensing and actuation functions. These methods include electrical impedance spectroscopy, electrochemical biosensors, and the use of surface acoustic waves for manipulation and analysis of cells, tissue, and multicellular organisms. In the second part, we will describe two sensor approaches based on surface-plasmon resonance and mechanical resonators that have recently provided new characterization features for biological samples, although technological limitations for use in high-throughput applications still exist.

Figure 1

Schematic representation of an integrated microphysiological system. Multiple interconnected organotypic microtissue models can be co-cultured in the platform to enable tissue-to-tissue interactions. The pumping and related flow mimics physiological shear stress on the tissues. The integrated sensors and actuators enable in situ monitoring, characterization and manipulation of the tissue models and of potentially circulating cells.

Figure 2

EIS-based sensors. (a) An Iimpedance cytometer by featuring a flow-focusing region (A), measurement electrodes (B), and sorting electrodes (C). Adapted with permission from Cheung et al., Cytometry A 65, 124-132. Copyright 2005. (b) Integrated microfluidic device with an ECIS-sensor for studying single-cancer-cell migration in a 3D matrix. Adapted with permission from Nguyen et al., Anal. Chem. 85, 11068-11076. Copyright 2013. (c) Microfluidic chip with integrated parallelized EIS monitoring of the size of multiple cancer spheroids (adapted with permission from Bürgel et al., Anal. Chem 88, 10876-10883. Copyright 2016) Microtissues rolling over the electrodes generate a peak, whose amplitude is proportional to the size of the spheroids.

Figure 3

Electrochemical biosensors. (a) Schematic view and photograph of sensors integrated in the hanging-drop device for measuring the metabolism of 3D microtissues. The device has been assembled by inserting sensor modules directly into the microfluidic substrate. Adapted with permission from Misun et al., Microsystems and Nanoeng. 2, 16022. Copyright 2016. (b) Schematic view showing the location of the biosensor electrode at the ceiling of the hanging drop substrate and the position of the 3D microtissues at the liquid-air interface of the hanging drop. The inset shows the functional enzyme layer on the electrode and the working principle of an enzyme-based biosensor. Adapted with permission from Misun et al. (c) Schematic view and photograph of a transparent, integrated microfluidic sensor chip, which features multiple electrochemical sensors. Adapted from Weltin et al. with permission from the Royal Society of Chemistry. (d) Separate biosensor module for glucose and lactate detection (1). Bioreactor for a liver-on-chip culture, which is connected to the sensor unit and to a microfluidic switchboard (2). The microfluidic switchboard, containing flow channels (red) and control channels (blue) (3). Adapted with permission from Bavli et al., PNAS, E2232-E2240. (e) Schematic view of the modular MPS by Zhang et al. featuring several fluidically interconnected components, including two cell-culturing chambers, a peristaltic pump, a bubble trap, a control breadboard, medium reservoirs and different electrochemical sensors. The photograph shows the complete MPS. (f) Example of electrode functionalization, electrochemical readout and sensor regeneration of an electrochemical immunosensor. Adapted with permission from Zhang et al., PNAS, E2293-E2302.

Figure 4

SAW-based particle or cell manipulation. a) Saw-based single particle/cell patterning. Particles are trapped at the node of the acoustic wave. (i) If the wavelength is much larger than the particle/cell diameter, multiple particles are driven to the force minima. (ii) By tuning the wavelength of the acoustic wave, single particle patterning can be achieved. Adapted with permission from Collins et al., Nat. Communications 6, 8686. Copyright 2015. b) Acoustic-tweezer-based formation of spheroids. Suspended cells are aggregated at the trapping positions, defined by the acoustic force, the induced streaming force, gravity and the buoyant force. The photographs at the bottom show the formation of spheroids of different size, which were obtained by using cell suspensions of different cell densities. Adapted from Chen et al. with permission from the Royal Society of Chemistry.

Figure 5

SPR-based sensors. a) A SPR fiber sensor for real-time monitoring of cellular responses, cultured in standard cell-culture flasks. The schematic shows the working principle of the sensor. Cells are cultured on the gold-patterned fiber surface. Light traveling through the waveguide interacts with the adherent cells on the fiber. The photograph shows the integration of the sensor in a cell-culture flask. Adapted with permission from Shevchenko et al., Biosens. Bioelectron. 56, 359-367. Copyright 2014. b) LSPR-based detection of cytokine (TNF-α) secretion by immune cells isolated from human blood. Functionalized beads bind to the target cells. (1) The sample then flows through a microfluidic chamber featuring a sieve structure to selectively retain the cells that are bound to beads. (2) Cells are then stimulated to induce cytokine secretion. (3) Cytokine secretion is quantified by the on-chip LSPR sensor functionalized with target-specific antibodies. The insets at the bottom show the LSPR-sensor surface at different analysis stages. Reprinted with permission from Oh et al., ACS Nano 8, 2667-2676. Copyright 2014.

Figure 6

Mechanical sensors. a) Cantilever structure for detecting the contraction of cardiac tissue. The cantilevers feature an engineered surface for formation of a laminar cardiac tissue on the sensor surface and integrated strain sensors for measuring the cantilever deflection. Adapted with permission from Lind et al., Nat. Mater. 16, 303-308. Copyright 2016. b) An array of SMR cantilevers is used to detect mass changes of cells as they travel through the array. Cells passing through an SMR cantilever induce a transient frequency shift in the resonance frequency of the cantilever, whose magnitude is proportional to the cell buoyant mass. Measuring the shift amplitudes as the cells travel through the array enables the detection of mass variations at different times. Adapted with permission from Cermak et al., Nat. Biotechnol. 34, 1052-1059. Copyright 2016.