1. Introduction
As researchers have attempted to better replicate in vivo cell biology
using in vitro systems, 3D cell culture systems have developed
rapidly.(Baker & Chen, 2012; Edmondson, Broglie, Adcock, & Yang, 2014)
One of the key goals of 3D cell cultures is to reproduce the spatial
organization and function of cells in the human body. There are a
variety of formats including spheroids, organoids and engineered
tissues. In 2D a cell becomes polarized as surface integrins enable it
to attach to the substrate. In 3D, the cell surface integrins are
distributed more randomly as the cell attaches to the scaffold/matrix in
multiple directions. The physiological differences induced by the
different attachment modes and the resulting cell/media interactions
mean that cellular functions such as proliferation, differentiation,
survival and mechanical signaling vary between 2D and 3D cell culture.
The details of these variations have been reviewed extensively,(Duval et
al., 2017) and many studies have shown variations in metabolism between
2D and 3D systems(Brajša, Trzun, Zlatar, & Jelić, 2016; Verjans,
Doijen, Luyten, Landuyt, & Schoofs, 2017) leading to a focus of these
systems for early stage drug testing and disease progression.
As experiments migrate from 2D to 3D models, traditional monitoring
techniques need to evolve to accommodate the needs of researchers and
the specific questions being asked of the 3D models. Currently, it may
take up to 30 days to grow a fully differentiated and mature 3D tissue
such as skin.(Carlson, Alt-Holland, Egles, & Garlick, 2008; V. Lee et
al., 2014) During this time and after it has matured, researchers need
to ensure the tissue has grown correctly and is biologically sound for
experimental use. However, at this point in time, there are few
convenient, bench-top platforms to monitor this process without
physically disrupting the model. In 2D culture, bright field microscopy
is often used in real‑time to monitor cell growth, but this is generally
not possible with non-transparent 3D tissues. To date, the most common
techniques used to visualize and validate 3D models are end-point
histology and fluorescence microscopy.(Dmitriev, 2017) Even though these
techniques are gold standards, they are time consuming and in most cases
requires the destruction of the sample for sectioning and staining.
While live cell approaches abound, reporter constructs and stains have a
limited lifespan and are not targeted to 3D cultures.(Walker-Daniels,
2012) Introducing new standardized methodologies to monitor 3D cultures
in real-time would save time, reducing research cost and providing a
quality assurance pathway for manufacturing.
Cell visualization is the most intuitive way of identifying cell health,
but a range of other methods have been developed to indirectly assess
cells in culture. Physical and chemical probes that measure the levels
of oxygen, glucose, CO2 and pH of cell culture media can
determine cell metabolism and health status.(Bavli et al., 2016; Hossein
Mahfouzi, Amoabediny, Doryab, Hamid Safiabadi-Tali, & Ghanei, 2018;
Jenkins, Dmitriev, Morten, McDermott, & Papkovsky, 2015; Shaibani,
Etayash, Naicker, Kaur, & Thundat, 2016; Weltin et al., 2014; Weyand et
al., 2015) Traditional techniques that measure parameters such as
glucose and oxygen concentrations take advantage of ion permeable
membranes and selective enzymes to determine concentration
levels.(Oliver, Toumazou, Cass, & Johnston, 2009) However, a broad
range of transducers can also be used to indirectly measure these
parameters of cell health.(Modena, Chawla, Misun, & Hierlemann, 2018)
Field effect transistors (FET) and light-addressable potentiometric
sensors (LAPs) have emerged as useful sensors capable of detecting
cellular metabolic products and provide effective spatial resolution
within 2D cell culture systems.(Dantism, Takenaga, Wagner, Wagner, &
Schöning, 2015; Poghossian, Ingebrandt, Offenhäusser, & Schöning, 2009)
Most of these culture characteristics are measured in the media
downstream of cells and they give real-time information without
destruction of the culture or tissue. These sensors are commercially
available and are usually incorporated within bioreactor systems that
are used to grow and monitor spheroids or cells in suspension over
time.(Alexander, Eggert, & Wiest, 2018; Weyand et al., 2015) This
approach assumes that the media is reflecting the behavior inside the
tissue. With 3D cultures such as spheroids, this approach may become
problematic as spheroids display diffusion limits to nutrients leading
to cell death at the center of the culture.(Mehta, Hsiao, Ingram, Luker,
& Takayama, 2012) Further, co-culture systems can lead to local
variations in behavior(Goers, Freemont, & Polizzi, 2014) which are
difficult to detect in the whole system by media sampling.
An alternative approach involves the characterization of electrical
properties of cells in culture. Trans‑epithelial electrical resistance
(TEER) measurements are widely used in biology and tissue engineering to
determine epithelial and endothelial cell health and membrane integrity.
These measurements give an indirect, non-invasive assessment of the
permeability of cellular tight junctions and ultimately the barrier
function of a cellular monolayer or 3D tissues.(Chen, Einspanier, &
Schoen, 2015; Schmitz et al., 2018) There are several variables known to
affect the final readout including electrode size, measurement
temperature, media formulation, time in culture and cell passage number,
making it difficult to standardize measurements.(Elbrecht, Long, &
Hickman, 2018; Srinivasan et al., 2015) A detailed review of TEERs and a
guide to laboratory standardization is presented by Srinivasan and
colleagues.(Srinivasan et al., 2015)
Derived from the same principles as TEER, electrical impedance
spectroscopy (EIS), is a well-established tool for monitoring 2D cell
cultures. EIS measurements are acquired with electrodes positioned
beneath the culture and changes in current/voltage through the cells are
measured as a frequency sweep is undertaken. This process allows the
electrical resistance and capacitance of cells to be monitored.(Benson,
Cramer, & Galla, 2013; Groeber et al., 2015) While TEER measures
currents at one frequency, sweeping the frequency allows EIS to obtain
more detailed information about cellular health status over time.
Currently, there are a range of commercially available TEER and EIS
devices used for assessing cell barrier function, integrity and cell
proliferation in real time. These include OrganoTEER (MIMETAS, Leiden,
The Netherlands), xCELLigence Real Time Cell Analysis (ACEA Biosciences,
Inc., CA, USA), EVOM2 (World Precision Instruments, FL, USA) and
Millicell‑ERS2 (EMD Millipore Corporation Billerica, MA, USA). However,
these devices are mainly designed for monitoring adherent cells grown in
2D or transwell based co-culture systems. Electrodes have also been
integrated into a range of different 3D cell culture models and
microfluidic platforms for EIS monitoring.(V. F. Curto, Ferro, Mariani,
Scavetta, & Owens, 2018; S.-M. Lee et al., 2016; Lei, Liu, & Tsang,
2018a). In particular, cell proliferation within spheroids have been
successfully monitored using this technique.(Bü, Diener, Frey, Kim, &
Hierlemann, 2016; Lei, Lin, & Tsang, 2017; Lei, Liu, & Tsang, 2018b;
Pan et al., 2019)
Additionally, EIS has also been incorporated into 3D culture systems for
multi-parametric monitoring including bioelectrical sensing and the
detection of cell metabolites. Despite the need for the integration of
in-line sensing and optical monitoring tools for real time and rapid
biological readouts, little research exists where these have been
successfully integrated. This is especially evident with highly modular,
sensor-based organ-on-chip systems that are difficult to integrate with
current microscopy approaches due to design incompatibilities.(Vincenzo
F. Curto et al., 2017; Esch, Ueno, Applegate, & Shuler, 2016; Zhang et
al., 2017) Multi-parametric approaches incorporating sensing systems,
optical readouts and techniques that can provide better spatial
resolution are currently needed. This review focuses on the varied
methods that have been used, the challenges and limitations associated
with different strategies and the factors that need to still be
addressed to enable real time, quantifiable results from these systems.