REVIEW
published: 22 March 2021
doi: 10.3389/fmats.2021.631373
Frontiers in Materials | www.frontiersin.org 1 March 2021 | Volume 8 | Article 631373
Edited by:
Weihua Li,
University of Wollongong, Australia
Reviewed by:
Martin Stelzle,
University of Tübingen, Germany
Pinar Yilgor Huri,
Ankara University, Turkey
*Correspondence:
Stephanie M. Willerth
willerth@uvic.ca
Specialty section:
This article was submitted to
Biomaterials,
a section of the journal
Frontiers in Materials
Received: 19 November 2020
Accepted: 01 March 2021
Published: 22 March 2021
Citation:
Lawko N, Plaskasovitis C, Stokes C,
Abelseth L, Fraser I, Sharma R,
Kirsch R, Hasan M, Abelseth E and
Willerth SM (2021) 3D Tissue Models
as an Effective Tool for Studying
Viruses and Vaccine Development.
Front. Mater. 8:631373.
doi: 10.3389/fmats.2021.631373
3D Tissue Models as an Effective
Tool for Studying Viruses and
Vaccine Development
Nathan Lawko1,2
, Charlie Plaskasovitis1,2
, Carling Stokes2,3
, Laila Abelseth2
, Ian Fraser3
,
Ruchi Sharma3
, Rebecca Kirsch4
, Misha Hasan5
, Emily Abelseth3
and
Stephanie M. Willerth2,3,5,6
*
1
Department of Electrical and Computer Engineering, University of Victoria, Victoria, BC, Canada, 2
Centre for Biomedical
Research, University of Victoria, Victoria, BC, Canada, 3
Department of Mechanical Engineering, University of Victoria, Victoria,
BC, Canada, 4
Department of Chemistry, University of Victoria, Victoria, BC, Canada, 5
Biomedical Engineering Program,
University of Victoria, Victoria, BC, Canada, 6
Division of Medical Sciences, University of Victoria, Victoria, BC, Canada
The recent SARS-CoV-2 outbreak has researchers working tirelessly to understand
the virus’ pathogenesis and develop an effective vaccine. The urgent need for rapid
development and deployment of such a vaccine has illustrated the limitations of current
practices, and it has highlighted the need for alternative models for early screening of
such technologies. Traditional 2D cell culture does not accurately capture the effects
of a physiologically relevant environment as they fail to promote appropriate cell-cell
and cell-environment interactions. This inability to capture the intricacies of the in vivo
microenvironment prevents 2D cell cultures from demonstrating the necessary properties
of native tissues required for the standard infection mechanisms of the virus, thus
contributing the high failure rate of drug discovery and vaccine development. 3D cell
culture models can bridge the gap between conventional cell culture and in vivo models.
Methods such as 3D bioprinting, spheroids, organoids, organ-on-chip platform, and
rotating wall vessel bioreactors offer ways to produce physiologically relevant models
by mimicking in vivo microarchitecture, chemical gradients, cell–cell interactions and
cell–environment interactions. The field of viral biology currently uses 3D cell culture
models to understand the interactions between viruses and host cells, which is crucial
knowledge for vaccine development. In this review, we discuss how 3D cell culture
models have been used to investigate disease pathologies for coronaviruses and other
viruses such as Zika Virus, Hepatitis, and Influenza, and how they may apply to drug
discovery and vaccine development.
Keywords: COVID-19, biomaterials, tissue engineering, organoids, antigen, microenvironment
INTRODUCTION
Viruses, infectious agents, can only replicate in a host organism (Lodish et al., 2000). Prior to
infection of a host, viruses exist as independent particles called virions. Virions contain nucleic
acids, most commonly DNA or RNA, that allow them to mutate and evolve. A coat consisting
of proteins or lipids called a capsid protects their genetic material. Viral infection occurs when
proteins on the surface of a virion bind to specific receptor proteins on the surface of host cells.
After infection, a virus will hijack the machinery of the host cell to produce and release copies of
Lawko et al. 3D Tissue Models for Vaccine Development
the virus to infect nearby cells. If a person has not encountered
this virus before, their immune system undergoes a process to
identify these viral particles as being foreign and then remove
them from the body. The immune system then retains memory
of that virus. A vaccine is a biological agent that elicits a
protective immune response targeting a particular pathogen
without requiring the host to acquire the disease (Vetter et al.,
2018). There are several types of vaccines, each with different
ways of inducing different adaptive immune mechanisms. Liveattenuated
vaccines are composed of pathogens that have
been adapted to be less virulent than the functional virus.
Healthy vaccine recipients develop long-term immunity similar
to having recovered from the viral infection (Vetter et al.,
2018). Inactivated vaccines use deactivated pathogens that are
incapable of causing infection. While inactivation destroys the
ability of the virus to replicate, its immunogenicity is retained
to allow the immune system to target the pathogen. Subunit and
conjugate vaccines use select fragments of a pathogen, such as
proteins, polysaccharides, or parts of a virus that may form viruslike
particles, to incite an immune response. Toxoid vaccines
utilize inactivated toxins that, while no longer harmful, preserve
their ability to induce toxin-neutralizing antibodies (Vetter
et al., 2018). Modern vaccine designs have been introduced to
address limitations of current vaccine types. These technologies
include nucleic-acid based vaccines that insert DNA or RNA
encoded with antigenic proteins into cells, and recombinant
vector vaccines use non-pathogenic vectors, such as a virus or
bacterium, to introduce the foreign genetic material into cells
(Vetter et al., 2018; NIAID, 2020).
A potential vaccine must be assessed for toxicity, induced
immunogenic response, efficacy, and impact on public health
while meeting guidelines of regulatory health agencies before
being approved for use in humans (Singh and Mehta, 2016). The
development process can be divided into the preclinical stages
(in vitro and in vivo animal tests) followed by the three clinical
stages using human subjects. Only a select few vaccines currently
in development will successfully complete the transition from
laboratory to clinical trials. The development timeline of vaccines
can take anywhere from 5 years at an accelerated rate to upwards
of 15 years (Bregu et al., 2011). It was found that only 16.2% of
vaccines were able to advance from preclinical trials to Food and
Drug Administration approval in the United States from 2006
to 2015 (Thomas et al., 2016). The associated cost of vaccine
development from discovery to licensure can come to billions
of dollars (Gouglas et al., 2018). With over 100 million people
and counting diagnosed worldwide, the COVID-19 pandemic
has catalyzed an international effort to produce a vaccine
aiming to provide immunity against the severe acute respiratory
syndrome coronavirus 2 (SARS-CoV-2) virus, resulting in some
promising results.
SARS-CoV-2 has affected millions of people globally, resulting
in a shift of research toward drug and vaccine development
(Draft Landscape of COVID-19 Candidate Vaccines, 2020). On
January 11th, 2020 the genetic sequence of the novel coronavirus
was identified, catalyzing the search for a suitable vaccine
against the virus (Thanh Le et al., 2020). There are currently
66 candidate vaccines against SARS-CoV-2 in clinical trials,
and over 100 in preclinical evaluation (Draft Landscape and
Tracker of COVID-19 Candidate Vaccines, 2021). The use of
2D cell culture can facilitate drug discovery and optimize the
vaccine development process. The process of cell culture grows
and maintains living cells in an artificial environment. Cell
culture has proved useful in understanding the fundamental
molecular and physical processes that allow cells to assemble
into tissues and organs, how tissues to function, and how
tissues respond to diseases and treatment with drugs (Duval
et al., 2017; Kapałczy´nska et al., 2018). Life science research
often uses mammalian cell culture as a tool for drug discovery,
including manufacturing viral vaccines (Hu, 2020; Ryan, 2020).
In comparison to traditional 2D cell culture systems, threedimensional
(3D) cell culture can serve as a better model system
for vaccine development by providing a microenvironment that
replicates the physiological setting of real cells, enabling better
identification of toxicity and other unwanted issues earlier in
drug development (Ravi et al., 2015). 2D cell cultures only
partially exhibit the morphology and biochemical behavior
necessary for viral infection while being unable to imitate the
intricacies of microenvironment of in vivo (Rosellini et al.,
2019). These limitations can be addressed by 3D cultures
that create a tissue-specific microenvironment that mimics in
vivo microarchitecture, oxygen, nutrient and metabolic waste
gradients, cell–cell interactions and cell–extracellular matrix
(ECM) interactions. 3D cell culture generates physiologically
relevant models that can be used for drug discovery and highthroughput
screening (Langhans, 2018), and can thus serve as an
alternative technique for studying viral replication, bridging the
differences between conventional cell culture and in vivo models
(D’Aiuto et al., 2018; Rosellini et al., 2019). A comparison of
studies between 2D cell monolayers and 3D cellular aggregates
showed that the latter were better predictors of drug responses
in vivo (He et al., 2016). Such preclinical models can more
accurately predict clinical outcomes, saving both time and cost
during the vaccine development process (Peng et al., 2017; Zhu
and Ding, 2017; Cairns et al., 2020; Takayama, 2020). Thus, the
substitution of 2D cultures by 3D cultures in drug screening
requires swift, robust technologies amenable to analysis in a
reliable manner (Zhu and Ding, 2017; Bhowmick et al., 2018;
Cairns et al., 2020). 3D tissue models can provide insight and
understanding into the complex interactions between viruses and
their host cells that can be useful in the vaccine development
process. 2D and 3D cell culture images are shown in Figure 1
to illustrate the differences between these culture methods. This
review will discuss the progress made in the field of viral biology
using 3D cell culture methods on various viral infections, such
as Zika Virus, Hepatitis, Influenza, and Coronaviruses, as well as
outline its potential for the development of viral vaccines with a
particular focus on SARS-CoV-2.
3D Cell Culture
3D cell culture can be accomplished by using either a scaffold, cell
supporting matrix, or non-scaffold-based culture method (Costa
et al., 2016). A variety of 3D culture methods have been used
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Lawko et al. 3D Tissue Models for Vaccine Development
FIGURE 1 | SEM (scanning electron microscope) images of 2D and 3D cell cultures that illustrate the difference in cell morphology for three different breast cancer
lines. Both BT474 and HCC1954 cells form tightly packed spheroids when grown in 3D, while EFM192A cells form a less organized 3D structure under the same
conditions. Scale bars are shown on the images. This figure is reprinted under the terms of the Creative Commons Attribution License from Breslin and O’Driscoll
(2016).
to study viral biology, such as 3D hydrogels, 3D bioprinting,
spheroids, organoids, rotating wall vessel (RWV) bioreactors, and
organ-on-a-chip (OOAC) platforms (Figure 2). Hydrogels are
3D networks composed of hydrophilic polymer chains that retain
their structure due to crosslinking of individual polymer chains
(Bahram et al., 2016). With a wide range of natural and synthetic
hydrogels, the versatility of hydrogels makes them suitable for
designing scaffolds with predefined physiological and mechanical
properties that effectively mimic the extracellular matrix, making
them useful in the field of tissue engineering and drug discovery
(Tibbitt and Anseth, 2009; Ruedinger et al., 2015).
3D bioprinting is the additive manufacturing of biological
structures that allows for the precise recreation of complex
tissue microenvironment. The high resolution obtained by
3D bioprinting is due to the layer-by-layer positioning of
biological materials, biochemicals and living cells to fabricate
tissues structures (Murphy and Atala, 2014; Ozbolat, 2015).
Consequently, 3D bioprinting techniques, with their capability
to automate the creation of 3D tissue structures, stands out
amongst the different methods for producing biomimetic tissue
(Berg et al., 2018; de la Vega et al., 2019). 3D bioprinted
models can overcome most of the drawbacks in a 2D in
vitro cell model. For instance, in a 2D model where the
growth substrate is attached to a hard-plastic surface, cells
can lose their characteristics due to limited cell-cell or cellECM
interaction. However, the 3D structural model allows the
cell culture to grow in the same way as within the human
body, maintaining single-cell characteristics and analogously
replicating the complex structures and physiological functions.
The reliability of results from using these tissues is far higher than
that of the 2D cell culture models (Peng et al., 2017; Centeno et al.,
2018).
Spheroids are micro-sized cellular aggregates that are widely
used in the field of oncology (Ryu et al., 2019). They mimic the
characteristics of solid tumors from various cancer types in vitro,
making them highly suitable for in vitro oncological drug testing.
Liquid overlay, hanging drop, microfluidic-based assembly, and
spinner flasks can all be used to produce spheroids. Spheroids
simulate the communication between cells and interactions
between the cells and the ECM better than 2D cell models
(Rosellini et al., 2019; Ryu et al., 2019). Cellular spheroids can
overcome limitations related to conventional in vitro systems
for viral isolation (Rosellini et al., 2019). The sensitivity and
efficiency of isolation of three existing viral species, Adenovirus,
CMV, and HSV-1, in 2D have been studied in spheroids
composed of susceptible cells (Rosellini et al., 2019; Cairns et al.,
2020). The results indicate that 3D culture systems allow for
earlier and more sensitive virus isolation than in traditional
2D systems, proving the importance of 3D culture systems in
the virologic field for the improvement and evolution of more
efficient and accurate virus isolation protocols (He et al., 2016).
Organoids, mini tissues modeling simplified versions of an
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Lawko et al. 3D Tissue Models for Vaccine Development
FIGURE 2 | Different methods of 3D cell culture, including 3D hydrogels, spheroids, organoids, 3D bioprinted tissues, organ-on-a-chip (OOAC), and rotating wall
vessel (RWV) bioreactors.
organ that are produced in vitro, can replicate the properties
of the target tissue. Derived from primary tissues or stem
cells, organoids self-organize into a 3D structure due to their
differentiation capacity (Yin et al., 2016). With their realistic
microanatomy and physiological relevance, organoids have
gained attention for their potential in developmental biology,
disease pathology, cell biology, regenerative mechanisms,
precision medicine, and drug toxicity and efficacy testing
(Rossi et al., 2018).
Bioreactors are mechanical devices with the means to
influence biological and/or biochemical processes (Plunkett and
O’Brien, 2011). With the ability to closely monitor and enable
controlled and reproducible changes of specific environmental
factors, bioreactors are suitable for the in vitro development of
tissue by providing regulatory biological, chemical, and physical
cellular signals (Martin et al., 2004; Plunkett and O’Brien, 2011).
Initially designed to model microgravity, National Aeronautics
and Space Administration’s (NASA’s) RWV bioreactor has been
found to provide an accurate physiological representation of
human tissues in vivo. The low-shear environment promotes
cell-cell interactions, a more homogenous cell distribution in
comparison to 2D culture, the induction of differentiation,
and the effects on intracellular signal transduction and gene
expression due to the randomized gravitational vectors (Plunkett
and O’Brien, 2011; Qian et al., 2016), thus allowing for the
formation of complex 3D tissue-like aggregates. These aggregates
express cellular architectural and structural features that are
vital in analyzing virus-host interactions, such as tight junction
proteins, mucus and microvilli, and thus can potentially be used
to screen therapeutic agents and antiviral drugs in preclinical
studies (Gardner and Herbst-Kralovetz, 2016).
While single-cell microfluidics have been instrumental in
developing an understanding of the molecular and cellular
basis of virus–host interactions, the platform does not allow
for the study of cell-to-cell spread of a viral infection (Liu
et al., 2020). Recently, microfluidic OOAC systems, such as
liver and lung chips, have been used to reproduce viral
infections such as Influenza and Hepatitis (Tang et al., 2020).
OOAC is a biomimetic, microfluidic system that regulates
concentration gradients, shear force, cell patterning, tissueboundaries,
and tissue–organ interactions to simulate the
physiological environment of an organ or organ system (Wu
et al., 2020). OOACs have applications in preclinical drug
testing and screening, as well as in drug discovery (Zhang
et al., 2018). While there have been limited studies conducted
using microfluidics for 3D viral culturing, the combination of
a microfluidic OOAC platform and 3D cell culture can better
mimic organ-specific responses and create more physiologically
relevant models that can be applied to viral studies for vaccine
development (Simpson et al., 2018; Tang et al., 2020). Each
of the 3D cell culture techniques discussed can and has been
employed in the study of various viruses, allowing more accurate
modeling of viral behavior in an animal system. The following
sections discuss applications of these techniques for specific
viruses and models, and how they could be applied to the novel
SARS-CoV-2 virus.
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Lawko et al. 3D Tissue Models for Vaccine Development
Coronaviruses
The scientific and medical communities and vaccine industry
are rapidly trying to develop a vaccine to address the recent
outbreak of the novel coronavirus SARS-CoV-2. Previous
experience with vaccines for H1N1 influenza have highlighted
the need for novel design and manufacturing platforms (Tatara,
2020). Coronaviruses, or Orthocoronavirinae, are enveloped
viruses with a single-stranded RNA genome. They are generally
characterized by five major components: the envelope protein,
membrane glycoprotein, spike protein, nucleocapsid protein and
a single stranded RNA genome (Tatara, 2020). As a positive
single-stranded virus, SARS-CoV-2 replicates in the cytoplasm
and does not depend on RNA polymerase for transcription
(Tatara, 2020). SARS-CoV-2 is thought to be spread primarily
through aerosolized droplets due to coughing, sneezing and
talking. The virus primarily affects the epithelial tissue of the
lungs and causes acute respiratory distress syndrome in 5–10%
of infected individuals (Tatara, 2020). Given the severity of
the morbidity and mortality rates associated with SARS-CoV-
2, there is an urgent need for a deeper understanding of the
viral mechanisms of the virus-host interactions of SARS-CoV-
2, and more comprehensive and prompter screening of potential
vaccines and other therapeutic strategies.
Although animal models have been instrumental in studying
disease and the human lung, given the physiological differences
between human and animal lungs, it is unsurprising that animal
models cannot effectively model the complete pathophysiology of
the human lung. Up to 80% of drug therapies that pass preclinical
animal trials fail to treat human diseases during clinical trials
(Miller and Spence, 2017). One way to better characterize
the host-virus interactions and infection mechanisms and
screen therapeutics is with the use of in vitro modeling with
human cells. In vitro modeling of viral diseases can assist
in identifying and profiling biomarkers and understanding
host-virus interactions and mechanisms for transmission—two
crucial pieces in the pursuit of hypothesis-based diagnostic and
therapeutic objectives. Currently, in vitro antiviral modeling,
specifically of Zika and Ebola virus, relies on a monolayer
cell culture of Vero cells - kidney epithelial cells isolated
from the African green monkey (Johansen et al., 2015; Adcock
et al., 2017). These monocultures of Vero cells lack interferon,
making them highly susceptible to viral infection and replication.
However, interferon plays an important role in host binding for
proteins involved in SARS-CoV-2 (Ziegler et al., 2020). Thus,
it provides a major challenge when using these cell cultures
to model the virus and screen potential therapies for SARSCoV-2.
A drug’s usefulness in inhibiting an infection in a
primate kidney cell that does not produce interferon will not
necessarily provide the appropriate and definitive therapeutic
options needed for humans (Tatara, 2020). In general, these static
xenograft animal cell cultures cannot always replicate the specific
conditions and architectural features of human in vivo tissues that
viruses encounter.
In the study of severe acute respiratory syndrome
coronavirus (SARS-CoV-1), Suderman et al. engineered 3D
tissue assemblies with a RWV bioreactor as a co-culture
of human broncho-tracheal cell lines, with a mesenchymal
component as the matrix and human broncho-epithelial cells
(BEAS-2B) (Goodwin, 2006). Figure 3A shows the NASA
designed RWV bioreactor used in the aforementioned study
(Gardner and Herbst-Kralovetz, 2016) and 3B shows its different
applications. Although no infectious virions were detected in the
cell culture over the course of the infection, there was evidence of
cross-reactivity between antibodies and viral spike and nuclear
proteins in the SARS-CoV-1 infected tissue (Gardner and
Herbst-Kralovetz, 2016). However, during the 10-day study of
the tissue, cytoplasmic vacuolization, mitochondria loss, and
endoplasmic reticula disturbance were also observed, indicating
clear signs of infection. Although no virions were observed,
these other host response mechanisms indicate a viral infection,
suggesting that these cell cultures could provide important
information about SARS-CoV-1 pathogenesis and infection.
These initial experiments with 3D respiratory tissues could
provide valuable information for new novel respiratory viruses,
such as SARS-Cov-2 (Gardner and Herbst-Kralovetz, 2016).
In February of 2020, Monteil et al. isolated the SARS-CoV-
2 from a sample from patient in Sweden to study therapeutic
options for COVID-19 (Monteil et al., 2020). The study
investigated whether inhibiting the interaction of angiotensin
converting enzyme 2 (ACE2), the key receptor for the spike
glycoprotein of SARS-CoV-2, and SARS-CoV-2 may be a viable
option for treating patients of COVID-19. The report concluded
that clinical grade-human recombinant soluble ACE2 (hrsACE2)
can reduce viral load in Vero cells by a factor of between
1,000 and 5,000. After culturing Vero E6 cells, the virus was
sequenced using next-generation sequencing. It was determined
that hrsACE2 both inhibits the attachment of the virus to the cells
and that this inhibition is dose dependent. The primary infection
site of COVID-19 is the lungs, which may be the source of the
spread of infection to other tissues like the kidney and intestine
(Monteil et al., 2020). The researcher hypothesized that to infect
larger local tissues, capillaries must first be infected. Human
capillary organoids were established from induced pluripotent
stem cells (iPSCs) (Figure 4A) and infected with SARS-CoV-2.
The experiment demonstrated that viral RNA could be detected
in the blood vessel organoids and that the viral RNA increased
from day 3 to day 6, suggesting active replication of the virus
(Figure 4B). A similar experiment was run on human kidney
organoids. In both experiments, the infected organoids were then
used to successfully infect Vero E6 cells, showing that the infected
blood vessel and kidney organoids could produce infections in
other tissues (Figure 4C). When hrsACE2 was added, infections
in the human organoids were reduced in a dose-dependent way
(Figure 4D). The data from this research shows that human
engineered organoids can be infected with SARS-CoV-2, and
during early stages, the infection can be inhibited significantly
by hrsACE2 (Monteil et al., 2020). Thus, these engineered tissue
models provide important insight in virus interactions.
Another useful resource in determining the pathophysiology
of coronavirus infections and providing potential for drug
screenings are the development of 3D in vitro human engineered
lung tissue models. In recent years, primary human lung cells
have been cultured into 3D tissue arrangements resembling
multiple structures of the human lung. Although many of
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Lawko et al. 3D Tissue Models for Vaccine Development
FIGURE 3 | The RWV bioreactor used to engineer 3D tissues for the co-culture of human broncho-tracheal cell lines and human broncho-epithelial cells. (A)
Confluent cells grown in 2D are combined with media and microcarrier beads in the bioreactor (B) The RWV was used in other studies to form tissue aggregates. It is
kept in continuous rotation to prevent detachment and accumulation of cells at the bottom of the bioreactor. This figure is reprinted under the terms of the Creative
Commons Attribution License from Gardner and Herbst-Kralovetz (2016).
FIGURE 4 | (A) Vascular capillary organoids imaged using light microscopy (upper) and blood vessel organoids using imaged with immunostaining to detect
endothelial cells and pericytes (lower). (B) Viral RNA recovered from organoids at day 3 and 6 after SARS-CoV-2 infection. (C) The supernatant from SARS-CoV-2
infected organoids 6 days after infection were used to infect Vero E6 cells. (D) Effect of hrsACE2 on vascular organoids infected with SARS-CoV-2 after organoids
were infected with 106
infectious particles and hrsACE2 for 1 h 3 days after SARS-CoV-2 infection. Results were measured using qPCR. Scale bars are 500 and
50 mm. This figure is reprinted under the terms of the Creative Commons Attribution License from Monteil et al. (2020). ** indicates a significant difference between
the conditions.
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Lawko et al. 3D Tissue Models for Vaccine Development
these models have not been used to study coronaviruses
directly, they provide insight into various tissue-engineered
technologies can be leveraged to study respiratory viruses and
viral infections. For example, a 3D environment of human
“bronchospheres” has been developed from a population of
primary human bronchiolar epithelial cells (Rock et al., 2009).
This in vitro clonal sphere-forming assay isolated mouse basal
stem cells and human epithelial tissue and embedded them into
a 3D ECM gel (Rock et al., 2009). These experiments looked
at cell behavior, primarily regeneration and differentiation,
and found that the mouse basal stem cells were capable of
self-renewal and generation of differentiated daughter cells.
The assays developed in these experiments revealed potential
mechanisms that regulate basal cells and allowed for comparison
to other epithelial stem cells, they can also facilitate the study
of the development, maintenance, and repair of epithelial
airways and the mechanisms that regulate them (Rock et al.,
2009). Bronchiolar epithelial cells have also been co-cultured
with lung microvascular endothelial cells and lung fibroblasts
in a 3D culture to create airway organoids (Tan et al.,
2018). The study demonstrated that the randomly mixed
cell populations underwent rapid self-organization and cell
condensation into epithelial and endothelial structures. The
structures remained stable and mechanically robust over the
long-term culture. Interestingly, despite the proximal source
of epithelium, both proximal and distal epithelial properties
were observed, demonstrating the high-level plasticity of the
organoid. The results demonstrated that the 3D airway organoid
culture offers a new tool for the study of lung-based diseases
and cell-based therapy (Tan et al., 2018). Biological scaffolds
can also be used to generate 3D cell models. These consist of
ECM from decellularized rodent and human lungs reseeded with
human lung cells (Booth et al., 2012; Gilpin and Ott, 2015).
Researchers have also bioengineered structural scaffolds to mimic
the human lung environment (Miller and Spence, 2017). Many
studies have succeeded in seeding primary murine lung cells onto
natural ECM material, such Matrigel (Andrade et al., 2007) or
collagen (Mondrinos et al., 2007), and synthetic materials, such as
polylactic-co-glycolic acid (PGLA) and polyglycolic acid (PGA)
(Cortiella et al., 2006). All of these approaches provide significant
advantages over 2D monolayer cell cultures.
Using 3D Culture Models to Study the
Influenza A Virus
Influenza is a major cause of death worldwide, claiming between
250,000 and 50,000 lives per year globally (Bhowmick et al.,
2018). More specifically, the influenza A virus (IAV) is one of
the leading causes of severe respiratory diseases worldwide (Berg
et al., 2018). IAV infections are associated with high morbidity
and mortality worldwide (Berg et al., 2018; Bhowmick et al.,
2018). Influenza A, B, and C are characterized by negativestrand
segmented RNA genomes then further categorized by
the antigenicity of two surface glycoproteins, the hemagglutinin
(HA) and neuraminidase (NA) subtypes (Bouvier and Palese,
2008; Bhowmick et al., 2018). Although there are many
distinctive genetic subtypes, nine subtypes for NA and 16
subtypes for HA, only two NA (N1 and N2) and three HA
(H1, H2, and H3) have led to widespread, epidemic-like personto-person
transmission in humans (Bouvier and Palese, 2008).
The H1N1 IAV strain that emerged in 2009 marked the first
influenza pandemic of the 21st century, with over 61 million
people falling ill in the United States alone (Bhowmick et al.,
2018). Additionally, the CDC estimates that between 151,700 and
575,400 people died worldwide during the first year of H1N1
circulation (CDC, 2021). The segmented genome in the influenza
virus supports antigenic shift, allowing influenza virus strains
to obtain HA and NA segments from an influenza virus of
different subtype. Step-wise mutations yield periodic changes in
the amino acid substitutions in the RNA segments and therefore
the antigenic characteristics of the HA and NA called antigenic
drift (Radigan et al., 2015). When two viruses infect a single host,
the antigenic shift of these segments can lead to the formation
of novel strains of influenza that encode antigenic proteins to
which immune systems are unable to fight (Bouvier and Palese,
2008; Radigan et al., 2015). Influenza viruses target human
epithelial cells throughout both the upper and lower respiratory
tracts (Radigan et al., 2015). Currently, there are several models
available to study the immunopathology of IAV including animal
models, ex vivo human tissue models, 2D cell culture models, and
more recently, 3D cell culture models.
A study conducted in 2018 by Bhowmick et al. marked the
first step in designing and creating a complete 3D-Human TissueEngineering
Lung Model (3D-HTLM) (Bhowmick et al., 2018).
The study described the 3D culture of primary human small
airway epithelial cells (HSAEpCs) on a 3D chitosan-collagen
scaffold (Figure 5C) to determine the immunophenotype of
the IAV infection in response to two IAV strains, H1N1 and
H3N2 (Figure 5A) (Bhowmick et al., 2018). When compared to
2D cultures of HSAEpCs (Figure 5B) in terms of viability, cell
differentiation, morphology, and cell marker protein expression,
the results confirmed that the 3D cultured HSAEpCs yielded a
higher number of viable cells (25.6% higher than in 2D cultures;
Figure 5D), closely resembled and displayed characteristics of the
in vivo airway epithelium in morphology and marker protein
expression. When taken together, the results show that the 3D
cultured HSAEpCs provide an adequate environment for 3DHTLM
development (Bhowmick et al., 2018). This study takes
the first step in developing a complete 3D-HTLM that could have
broad applicability in the study of the pathology of respiratory
diseases and the development of vaccines or other therapies.
Another study performed in 2018 by Berg et al. looked at how
efficiently different 3D bioprinted cultures were infected by IAV
and compared the results to a natural lung and a conventional 2D
cell culture model (Berg et al., 2018). Researchers used optimized
3D printed cell-laden alginate, gelatin and Matrigel hydrogels
(Figure 6) to print human alveolar epithelial (A549) cells into a
spatially controlled model. The study drew comparisons between
the 2D and 3D models, highlighting that 2D cultures adhere to
a flat surface, limiting the physiological condition of the cells.
Additionally, they noted that infection of a homogenous 2D
culture is unlike an IAV infection in the human respiratory
tract because in the respiratory tract, not all alveolar cells are
homogeneously affected by the IAV (Berg et al., 2018). The
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Lawko et al. 3D Tissue Models for Vaccine Development
FIGURE 5 | 3D tissue engineering lung model and comparative analysis of 2D and 3D culturing of HSAEpCs (A) 3D culturing of HSAEpCs on chitosan-collagen
scaffolds. (B) 2D culturing of HSAEpCs on membrane inserts. (C) SEM images showing the thickness (i) and pores (ii) of the chitosan-collagen scaffolds. (D) Cell
viability of HSAEpCs from 2D and 3D culturing. This figure is reprinted under the terms of the Creative Commons Attribution License from Bhowmick et al. (2018). *
indicates a significant difference was detected between conditions.
suitability for infection was assessed by infecting the bioink
models with the IAV strain H3N2, a strain of seasonal influenza.
Overall, the study concluded that, although both 2D and 3D
culture types productively infected the A549 cells, the clustered
infection pattern of the 3D culture more closely resembles the
natural biological condition observed in the cells of the human
lung than the evenly distributed infection seen in the 2D culture.
Additionally, the 3D printed cells produced an immune response
by releasing the antiviral IL-29. Overall, the results of this study
can be used to help develop a powerful model that is suitable for
studying IAV infections, but may also help study other viruses
and the development of new therapies and antiviral strategies.
Using 3D Culture Models to Study the Zika
Virus
Since the effects of SARS-CoV-2 fetal development and the brain
are still being researched, the ZIKV study models can be directly
translated to study the effects of SARS-CoV-2 infection in the
brain, pregnancies, and fetal development. During pregnancy,
hormonal levels and immune system function are changed to
reduce the potential of fetal rejection, allowing fetal development.
This causes higher mortality rates and complications due to
viral infection in pregnant women compared to the general
population (Alberca et al., 2020). The specific effects of SARSCoV-2
on pregnancies and fetal development are currently
largely unknown. It is important to investigate the effects of
SARS-CoV-2 on this population as pregnant women are more
susceptible to viral infection. Evidence has also shown that SARSCoV-2
can invade cells through the angiotensin-converting
enzyme 2 (ACE2) receptor (Baig et al., 2020; Cheng et al., 2020;
DosSantos et al., 2020; Hoffmann et al., 2020; Ni et al., 2020). The
lungs, kidney, prostate, liver, pancreas, intestines, heart, and brain
(predominantly in neurons) all express the ACE2 receptor, which
has been thought to contribute to multiple organ system failure
with SARS-CoV-2 infection (Ni et al., 2020). With several reports
showing that SARS-CoV-2 induces neurological manifestations
such as headaches, dizziness, anosmia, and ageusia, as well as
more severely stroke, seizure, encephalopathy, and encephalitis
(Baig et al., 2020), more research must be conducted to better
understand the underlying neurological mechanisms that occur
with infection of SARS-CoV-2. Zika virus (ZIKV), a mosquitoborne
flavivirus that has been documented to infect humans
since 1954. Since a major outbreak in 2007 in the Western
Pacific Island of Yap, additional outbreaks have been reported
worldwide, with 59 countries and territories having reported
ZIKV cases since 2015. Areas worst affected by the virus have
warm, humid climates in which the Aedes mosquitos that spread
the virus thrive (Agumadu and Ramphul, 2018). The symptoms
of the viral infection in humans are often relatively mild such
as fever, joint pain, red eyes, headache, and a maculopapular
rash usually lasting less than a week with most cases showing
no symptoms at all (Musso et al., 2014). Although no mortality
has been recorded as a result of ZIKV exposure, infection
in pregnant women poses significant developmental risks to
the fetus and has been linked to major teratogenic effects
such as microcephaly, cerebral calcifications, ventriculomegaly,
cerebellar hypoplasia, arthrogryposis, diaphragm paralysis, and
visual and hearing impairments (Meneses et al., 2017). The
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Lawko et al. 3D Tissue Models for Vaccine Development
FIGURE 6 | 3D printed cultures of A549 cells. (A) Various shapes of constructs made through extrusion printing. (B) Illustration of 3D printing setup. (C) Viscosity of
uncrosslinked bioinks at a shear rate sweep of 1–100 s−1
at 24◦
C. (D) Storage and loss modulus of bioink formulas at 1 Hz, 24◦
C, and 1% shear strain after the
addition of CaSO4. This figure is reprinted under the terms of the Creative Commons Attribution License from Berg et al. (2018).
severity of these conditions has made ZIKV a global focal point
in recent years and there is increasing motivation to understand
the mechanism through which the ZIKV affects developing
brain structures.
In 2016, Tang et al. linked ZIKV exposure to microcephaly
by confirming its inhibitory action in the formation and growth
of Neuronal Progenitor Cells (NPCs) derived from induced
Pluripotent Stem Cells (iPSCs) in 2D cell cultures (Hengli Tang
et al., 2016). This landmark study mobilized the world health
authorities to recognize the link between brain defects and
fetal exposure to ZIKV, and subsequent studies have made use
of 2D cultures for their ease of manipulation and isolation
of experimental variables to determine which cells are most
susceptible to infection by the virus (Chan et al., 2016). Despite
these successes, 2D cell cultures offer little insight into the
development of complex structures in the brain due to the fact
that the organization of progenitor layers and neuronal layers in
the developing cortex cannot be appropriately modeled using 2D
monolayer or neurosphere cultures. 3D brain organoids derived
from iPSCs are well-suited to this task, and Lancaster et al.
(2013) showed they mimic human brain organization, properties
and molecular signatures with high fidelity. Dang et al. (2016)
were able to demonstrate that developing organoids created
using the Lancaster et al. method could be analyzed for their
phenotypic and transcriptomic responses to ZIKV exposure,
allowing for parallels to be drawn between the stunted growth
of the infected organoids and TLR3-mediated dysregulation of
neurogenesis and axon guidance. In recent years, techniques for
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Lawko et al. 3D Tissue Models for Vaccine Development
FIGURE 7 | (A) Design of spinning bioreactor used to produce brain organoids. (B) diagram of the organoid protocol and images at the different stages of
development (scale bars are 200 mm). (C,D) Organoids after immunostaining (scale bars are 100 mm). This figure is reprinted under the terms of the Creative
Commons Attribution License from Qian et al. (2016).
creating 3D whole brain organoids have greatly improved, with
a 2016 study by Qian et al. (2016) notably outlining a novel
method involving a 3D printed spinning bioreactor (“Spin ”)
that can produce brain region specific organoids cheaply and in
an easily reproduced manner (Figure 7). In the study, cultures
were formed from iPSCs treated with dual SMAD inhibitors for
7 days, followed by 7 days embedded in Matrigel after which
the organoids were either left in stationary cultures, spun in a
Spin bioreactor or in an orbital shake bioreactor under similar
rotation to the Spin . At day 42, organoids in the stationary
culture and in the orbital shaker showed significant neuronal
cell death, whereas the spun organoids exhibited increased cell
viability. In addition to demonstrating the effectiveness of the
spinning reactor method for creating 3D forebrain organoids,
the Qian et al. group was able to miniaturize the reactor design
allowing for significantly reduced culture medium and incubator
space over existing spinning reactor designs. Aside from reducing
costs, which allows for scalability and more efficient use of
media and growth factors, the design allows for several reactors
to be easily set up simultaneously for examining multiple
conditions in parallel. The Qian et al. study used these methods
to compare the effects of ZIKV exposure at various stages in
organoids development to assess the danger at various stages of
pregnancy. They found that ZIKV exposure for only 1 day at
early stages of organoid development caused many detrimental
effects consistent with microcephaly, such as decreased neuronal
layer thickness and enlarged lumen/ventricles as well as increased
cell death and suppressed proliferation of infected NPCs. The
same ZIKV exposure to organoids at day 80 (which are more
complex and resemble second trimester fetal development) also
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Lawko et al. 3D Tissue Models for Vaccine Development
showed preferential infection of SOX2 NPCs. The results suggest
that it is the preferential infection of NPCs by ZIKV that leads
to the characteristic features of microcephaly in the developing
brain. The study demonstrates the usefulness of 3D organoids,
particularly when cultures can be produced large scale under
consistent conditions. It also highlights the state of current
technology that allows such work to be done at comparatively low
cost compared to animal studies.
Although 3D culture techniques have greatly improved when
accurately recapitulating in vivo cell-cell and cell-extracellular
matrix interactions by more closely approximating living tissue,
generation and study of complex and organized structures
has remained difficult until recent technological advancements.
The most prominent challenges with prior methods involve
the death of inner cells in larger organoids due to the lack
of vascularization (blood vessel formation) (Zhuang et al.,
2018). Spinning bioreactors facilitate better nutrient exchange,
which allows for organoids up to a few millimeters in size.
Accordingly, Takebe et al. (2013) demonstrated that co-culture
with endothelial cells can create vascular-like networks, but
more progress is needed for the creation of viable organoids of
significant size or complexity. While the issue of vascularization
has not yet been solved for creating large brain organoids,
methods have been proposed to address this deficiency. Bioinks
can be infused with multicellular aggregates called spheroids
that are formed either through spontaneous self-arrangement
or forced cell adhesion without scaffolds. Spheroids can be
adapted to more accurately recapitulate human brain features
such a cell diversity, electrical properties and mechanical stiffness
(Zhuang et al., 2018). Hsu et al. used spheroids composed of
neural and vascular progenitor cells formed by the chitosan (CS)based
substrates or other methods. The resulting co-spheroids
are suspended in growth factors and an appropriate bioink for
both types of progenitor cells and can be printed using available
methods (Han and Hsu, 2017). This approach could lead to
more accurate and functionally relevant brain organoids and
offers a way to study developing neuronal structures for the
purposes of therapeutics and understanding disease progression.
Recent advances in 3D printing technology have generated
significant interest in this topic, which could lead to more
accurate viral models.
In other work developing 3D models of brain tissues, Kador
et al. developed a technique in 2016 to construct 3D printed
scaffolds from electrospun polylactic acid (PLA) nanofibers
suspended in hydrogel to guide the formation of retinal ganglion
cell structures (Kador et al., 2016). Retinal ganglion cells were 3D
printed in an alginate bioink and shown to adhere and organize
along the scaffold while maintaining cell viability, neurite
outgrowth and their electrophysical properties. A separate study
constructed 3D scaffolds from laminin functionalized nanofibers
in hyaluronic acid hydrogels and recorded and average increase
in length of neurites per cell of 66% compared to laminin
nanofibers on 2D surfaces and with a 213% relative increase
in proportion of neurite lengths directed along the 3D scaffold
compared to the 2D scaffold (Johnson et al., 2014). A remaining
challenge with these approaches is that cells seeded onto the
scaffolds often grow along the surface resulting in unnatural
constraints in morphology that makes the construction of 3D
networks difficult. Creation of complex 3D neuronal structures
has been aided by the use of sacrificial scaffolds containing
guide cavities and micropores that are designed to be dissolved
of melted away after the cultures have fully developed (AntillO’Brien
et al., 2019). The resulting models have been shown
to more closely model human brain tissues and show great
promise for the study of brain development and response to
viral infection.
Many existing studies focus on clinical outcomes or
therapeutics, few consider viral transmission or mobility. 3D
bioprinting and organoid cultures have the potential to produce
more accurate models of biological interfaces. In the case of
ZIKV, the contagion must cross a maternal-fetal interface which
is most commonly the blood-placenta barrier or BPB, although
intrauterine transmission is also possible, with ZIKV having
been detected in the amniotic fluid of effected pregnancies
(Costa, 2016). For reasons already mentioned, traditional models
typically fail to accurately recapitulate the complex physiology
and properties of the BPB. In vivo studies during pregnancy
of these tissues are difficult or impossible due to safety and
ethical concerns surrounding the mother and fetus, making the
availability of accurate and reproducible engineered models a
necessity. While many studies exist that demonstrate the effects
of ZIKV exposure to both neural and placental cells, in 2018
Arumugasaamy et al. appear to have been the first to use 3D
models to study neural cell outcomes following transmission of
ZIKV across the BPB (Figures 8A–C) (Arumugasaamy et al.,
2018). In this instance, the BPB model was fabricated via
casting gelatin methacrylate and crosslinking to form a hydrogel
(Figures 8D,E). BeWo B30 cells and human umbilical vein
endothelial cells were then seeded on the hydrogel using manual
methods (Figure 8F). The resulting model (Figure 8G–K)
achieved a glucose transfer rate of 35.9% compared to a value of
26.5–38.3% noted in ex vivo perfused placenta (Blundell et al.,
2016) which suggests that the model performs comparably to
the current “gold standard” within the placental transport field.
Additionally, the researchers were able to observe preferential
interaction of ZIKV with placental tissue, offering support for
prior studies that suggest that the placenta plays a modulating
role in transmission (Miner et al., 2016). These findings highlight
the potential for better understanding of viral transmission and
pathogenesis through biomimetic organoid cultures, and the
techniques through which they are created lend themselves well
to recent advances in bioprinting technology.
Using 3D Culture Models to Study the
Hepatitis Virus
Hepatitis often refers to an inflamed liver. It can be caused by
several factors, most notably, alcohol abuse and Viral Hepatitis.
The five types of viral hepatitis are Hepatitis A, B, C, D, and
E virus (HAV, HBV, HCV HDV, HEV). The World Health
Organization estimates that 325 million people worldwide live
with HBV or HCV (Hepatitis, 2020). HAV and HBV currently
have effective vaccines while the rest do not. Hepatic models
usually utilize one of three categories of cell line each derived
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Lawko et al. 3D Tissue Models for Vaccine Development
FIGURE 8 | A model of the BPB, and the system used to culture BeWO b30 and HUVEC cells to perform a transport assay. (A) A diagram of the maternal decidua,
along with the (B) maternal side and the (C) maternal-fetal interface. A (D) diagram and (E) image of the BPB model used. (F) A timeline of culturing BeWo b30 cells
(day 0) and HUVEC cells (day 7) before the performed assays (day 10). (G) Schematic transport assay, (H,I) plug used in transwell insert, (J) transwell insert, and (K)
image of transport assay. This figure is reprinted under the terms of the Creative Commons Attribution License from Arumugasaamy et al. (2018).
from different sources, including cancer-based cell lines, primary
or patient derived cell lines, or stem cell derived models.
Cancer derived cell lines are immortalized liver-derived cells
that are often utilized for their availability, relative stability, and
reproducibility since the cell lines can reproduce indefinitely
(Jeon et al., 2017). Common hepatic cancer-based cell lines
include HepG2 and Huh7. Hepatocytes in 2D cell cultures do
not usually sustain hepatic like functionality over long-term trials
in vitro. Nguyen et al. compared patient-derived hepatocytes and
non-parenchymal cells in 2D cell culture with a 3D bioprinted
culture it was shown that ATP, albumin, and drug induced
enzyme levels decreased after 2 weeks in the 2D culture while they
stayed consistent in the 3D culture over a 4 week period (Nguyen
et al., 2016). Histologic analysis of the 3D tissues indicated that
the tissues condense and remodel over time, providing stable 3D
structures with dense cellularity and no necrosis. The same study
showed higher metabolism in the 3D culture evident by CYP3A4
expression from exposure to Rifampicin following day14 of the
trial providing further evidence of the advantage of the 3D culture
over 2D. While the study was intended to show the viability of the
3D culture for drug toxicity testing, the results are promising for
testing the ability of viruses to infect liver tissue.
The production of 3D hepatic structures to more closely
mimic in vivo conditions is often sought for potential transplants.
Recent advances in 3D bioprinting of liver models showed
promising results and possibilities for future viral treatment
and testing. A 2018 study by Mazzocchi et al. (2019) used a
novel method of forming an extrusion collagen bioink by mixing
a ratio of collagen I with hyaluronic acid to print a robust
extracellular matrix for liver models. Primary human hepatocytes
and liver stellate cells were used to form the hepatic model and
testing showed promising cell viability as well as retaining the
desired printed shape. The study also tested the tissue model’s
response to acetaminophen and found appropriately decreased
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Lawko et al. 3D Tissue Models for Vaccine Development
FIGURE 9 | 3D microfluidic system with primary human hepatocytes cultured in a bioreactor. (A) Illustration of the bioreactor showing continuous pumping of media
and a collagen-coated scaffold. (B) Cell viability 13 days after seeding 3D cultures. (C) Comparison of the various cell cultures: 2D hepatocytes, 3D spheroids, hepatic
and mouse fibroblasts (SACC PHH), and 3D hepatocytes. (D) Immunofluorescence of cell cultures 14 days after seeding. (E) Albumin secretion from cultures 14 days
after seeding from ELISA. White scale bars are 200 mm and gray scale bars are 500 mm. This figure is reprinted under the terms of the Creative Commons Attribution
License from Ortega-Prieto et al. (2018).
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Lawko et al. 3D Tissue Models for Vaccine Development
levels of albumin and urea secretion responding to toxicity and
implying good metabolism properties. Another 2018 study by
Hiller et al. (2018) found promising results of infection from
an adeno-associated virus vector in a 3D bioprinted liver model
using an alginate/gelatin-based bioink to form the extracellular
matrix. An issue observed in the past has been the density of
hepatic spheroids have prevented adequate virus transduction,
this 3D model would thus improve testing in these cases. The
model showed lower levels of albumin and CYP3A4 in the
3D cultures compared to the monolayer samples. Over a 7day
period, an increase in albumin and CYP3A4 was seen
the 3D model was seen while there was a decrease in the
monolayer model. The results of this study showed the 3D model
was an adequate hepatic model and demonstrates infection
from the test virus. Ortega-Prieto et al. (2018) produced a 3D
microfluidic system using primary human hepatocyte cultured
in a bioreactor (Figure 9). The culture model described allows
for the formation of hepatic microtissues that mimic hepatic
sinusoid microarchitecture including tight junctions, functional
bile canaliculi, and complete cell polarization. The model showed
better albumin and CYP3A4 secretion than 2D monolayers and
simple 3D spheroids, and additionally demonstrated an HBV
infection for over 40-days. A similar 2018 study tested a novel
method of generating liver organoids using a microwell system
with human iPSCs to test HBV infection (Nie et al., 2018). The
study compared the differences between liver organoids, which
were established through a culture of hiPSC-derived endodermal,
mesenchymal, and endothelial cells, with simple hiPSC-derived
hepatic-like cells especially with regards to their infection ability.
Liver organoids displayed more hepatic like features, such as
tight junctions and bile capillaries between hepatic cells. The
liver organoids, once infected, showed increased fibrosis and
markers believed to play a role in cancer development. Prolonged
maintenance in hepatic functionality was also noted in both
studies with each mentioning a possible study period of 40days.
As well, when infection of HBV was tested, both show
increase in HBV covalently closed circular DNA (cccDNA)
compared to simpler models. A 2019 study by Zhang et al.
utilized decellularized human liver scaffolds engrafted with
human hepatocytes cultures to derive a 3D hepatic model for
HBV testing (Zhang et al., 2019). The study argues that using
primary human hepatocytes (PHH) with decellularized human
liver scaffolds mimic in vivo conditions more closely than liver
organoid hiPSC and are thus a better candidate for HBV testing.
The method showed much higher secretions of albumin and
CYP3A4 than 2D models over 14-day periods. The study also
noted that the cccDNA of HBV was 30-folds higher than in 2D
counterparts 7 days after infection. Overall, these models serve
as an excellent starting point for modeling the effects of viral
infection in the liver.
CONCLUSION
Modeling biological systems in vitro remains a difficult task, built
on reducing complexity so that the effect of various conditions
can be observed, while replicating in vivo morphology and
biochemistry in a meaningful way. This review illustrates the
benefits of using 3D tissue culture techniques over 2D tissue
culture when studying viral infections and the implications
with regards to studying COVID-19. Techniques like spheroid
cultures and organoids have been shown to replicate systems of
viral infection more accurately than 2D cultures and to produce
morphology and biochemical behaviors required to allow for
viral infection in cases where 2D cultures do not. Bioprinting and
OOAC allow for high throughput drug screening and antibody
testing on systems that more accurately replicate human tissue
than 2D counterparts.
3D culture methods, however, are not without their
limitations. The greatest concern with 3D tissue models for
the purpose of drug and vaccine development remains to be
the ability of the culture model to fully embody the biological,
chemical, and physical microenvironmental parameters that
mimic in-vivo tissue and disease pathology. Spheroids cultures
have been known to exhibit hypoxia and necrosis at their
core. The incorporation of spheroids into a microfluidic system
that is oxygen and growth factor-permeable can mitigate these
limitations (Ryu et al., 2019). The use of an OOAC microfluidic
system can mitigate these limitations while also providing a
physiologically relevant microenvironment.
Similarly, the incorporation of a rotating or spinning vessel,
such as the RWV bioreactor, can help provide the necessary
oxygenation and nutrients for development and polarization
as described previously. Organoid cultures are typically formed
with only the epithelial layer and lack the surrounding tissue
microenvironment. Due to this, organoids as well as spheroids
lack tissue-tissue interactions, limiting their functionality. This
can be addressed by conducting more extensive studies
on organoid co-culture systems. Organoid cultures are also
commonly dependent on the use of batch-varying xeno-derived
ECM or basement membrane, making them that are inapt for
human drug studies (Xu et al., 2018). However, there is great
potential in the field of personalized medicine for patient-derived
organoids to provide robust personalized data, including patientspecific
mutation profiles and drug responses (Kim et al., 2020).
Moreover, streamlined processes have not been established
for culture methods, which can result in variability within
studies especially in regard to high throughput and high content
screening. There is also a lack of automated imaging techniques
of 3D cultures that provide satisfactory images. The size of
3D constructs, material transparency, and depth of microscopes
available all limit the ability to achieve clear, representative
images (Anton et al., 2015). These techniques must be further
developed to continue to advance 3D culturing research. Still,
the current progress made on these technologies are especially
important during the current SARS-CoV-2 pandemic and will
allow us to assess the virus’s behavior more accurately in human
patients and study treatments and vaccines at a pace never
before possible.
AUTHOR CONTRIBUTIONS
NL, CP, CS, LA, IF, RS, RK, and MH contributed to the writing
of the initial draft. IF, LA, EA, and SW edited and formatted the
draft for submission. All authors contributed to the article and
approved the submitted version.
Frontiers in Materials | www.frontiersin.org 14 March 2021 | Volume 8 | Article 631373
Lawko et al. 3D Tissue Models for Vaccine Development
FUNDING
This project funded with support from TechNation wage subsidy
program, Coast Capital Savings, Innovate B.C co-op program,
NSERC Discovery Grant program, the Alzheimer’s Association,
Canada Research Chairs and the Michael Smith Foundation
for Health Research and Pacific Parkinson’s Research Institute’s
Innovation to Commercialization grant.
REFERENCES
Adcock, R. S., Chu, Y. K., Golden, J. E., and Chung, D. H. (2017). Evaluation
of anti-Zika virus activities of broad-spectrum antivirals and NIH clinical
collection compounds using a cell-based, high-throughput screen assay.
Antiviral Res. 138, 47–56. doi: 10.1016/j.antiviral.2016.11.018
Agumadu, V. C., and Ramphul, K. (2018). Zika virus: a review of literature. Cureus.
10:e3025. doi: 10.7759/cureus.3025
Alberca, R. W., Pereira, N. Z., Oliveira, L. M. D. S., Gozzi-Silva, S. C., and Sato, M.
N. (2020). Pregnancy, viral infection, and COVID-19. Front. Immunol. 11:1672.
doi: 10.3389/fimmu.2020.01672
Andrade, C. F., Wong, A. P., Waddell, T. K., Keshavjee, S., and Liu, M. (2007).
Cell-based tissue engineering for lung regeneration. Am. J. Physiol. Lung Cell.
Mol. Physiol. 292, 510–518. doi: 10.1152/ajplung.00175.2006
Antill-O’Brien, N., Bourke, J., and O’Connell, C. D. (2019). Layer-by-layer: the case
for 3D bioprinting neurons to create patient-specific epilepsy models. Materials
12:3218. doi: 10.3390/ma12193218
Anton, D., Burckel, H., Josset, E., and Noel, G. (2015). Three-dimensional
cell culture: a breakthrough in vivo. Int. J. Mol. Sci. 16, 5517–5527.
doi: 10.3390/ijms16035517
Arumugasaamy, N., Ettehadieh, L. E., Kuo, C. Y., Paquin-Proulx, D., Kitchen, S.
M., Santoro, M., et al. (2018). Biomimetic placenta-fetus model demonstrating
maternal–fetal transmission and fetal neural toxicity of Zika virus. Ann.
Biomed. Eng. 46, 1963–1974. doi: 10.1007/s10439-018-2090-y
Bahram, M., Mohseni, N., and Moghtader, M. (2016). “Introduction to hydrogels
and some recent applications,” in In Emerging Concepts in Analysis and
Applications of Hydrogels, eds Majee, S. B. (London: InTech).
Baig, A. M., Khaleeq, A., Ali, U., and Syeda, H. (2020). Evidence of the
COVID-19 virus targeting the CNS: tissue distribution, host-virus interaction,
and proposed neurotropic mechanisms. ACS Chem. Neurosci. 11, 995–998.
doi: 10.1021/acschemneuro.0c00122
Berg, J., Hiller, T., Kissner, M. S., Qazi, T. H., Duda, G. N., Hocke, A. C.,
et al. (2018). Optimization of cell-laden bioinks for 3D bioprinting
and efficient infection with influenza A virus. Sci. Rep. 8, 1–13.
doi: 10.1038/s41598-018-31880-x
Bhowmick, R., Derakhshan, T., Liang, Y., Ritchey, J., Liu, L., and GappaFahlenkamp,
H. (2018). A three-dimensional human tissue-engineered lung
model to study influenza a infection. Tissue Eng. Part A 24, 1468–1480.
doi: 10.1089/ten.tea.2017.0449
Blundell, C., Tess, E. R., Schanzer, A. S. R., Coutifaris, C., Su, E. J., Parry, S., et al.
(2016). A microphysiological model of the human placental barrier. Lab Chip
16, 3065–3073. doi: 10.1039/C6LC00259E
Booth, A. J., Hadley, R., Cornett, A. M., Dreffs, A. A., Matthes, S. A., Tsui, J. L.,
et al. (2012). Acellular normal and fibrotic human lung matrices as a culture
system for in vitro investigation. Am. J. Respir. Crit. Care Med. 186, 866–876.
doi: 10.1164/rccm.201204-0754OC
Bouvier, N. M., and Palese, P. (2008). The biology of influenza viruses. Vaccine 26,
49–53. doi: 10.1016/j.vaccine.2008.07.039
Bregu, M., Draper, S. J., Hill, A. V. S., and Greenwood, B. M. (2011).
Accelerating vaccine development and deployment: report of a Royal
Society satellite meeting. Philos. Trans. R. Soc. B Biol. Sci. 366, 2841–2849.
doi: 10.1098/rstb.2011.0100
Breslin, S., and O’Driscoll, L. (2016). The relevance of using 3D cell
cultures, in addition to 2D monolayer cultures, when evaluating breast
cancer drug sensitivity and resistance. Oncotarget 7, 45745–45756.
doi: 10.18632/oncotarget.9935
Cairns, D. M., Rouleau, N., Parker, R. N., Walsh, K. G., Gehrke, L., and
Kaplan, D. L. (2020). A 3D human brain–like tissue model of herpesinduced
Alzheimer’s disease. Sci. Adv. 6:eaay8828. doi: 10.1126/sciadv.aa
y8828
CDC (2021). Summary of Progress since 2009 | Pandemic Influenza (Flu).
CDC. Available online at: https://www.cdc.gov/flu/pandemic-resources/h1n1summary.htm
(accessed February 14, 2021).
Centeno, E. G. Z., Cimarosti, H., and Bithell, A. (2018). 2D versus 3D human
induced pluripotent stem cell-derived cultures for neurodegenerative disease
modelling. Mol. Neurodegener. 13:27. doi: 10.1186/s13024-018-0258-4
Chan, J. F. W., Yip, C. C. Y., Tsang, J. O. L., Tee, K. M., Cai, J. P., Chik, K. K.
H., et al. (2016). Differential cell line susceptibility to the emerging Zika virus:
implications for disease pathogenesis, non-vector-borne human transmission
and animal reservoirs. Emerg. Microbes Infect. 5:e93. doi: 10.1038/emi.2016.99
Cheng, Q., Yang, Y., and Gao, J. (2020). Infectivity of human coronavirus in the
brain. EBioMedicine 56:102799. doi: 10.1016/j.ebiom.2020.102799
Cortiella, J., Nichols, J. E., Kojima, K., Bonassar, L. J., Dargon, P., Roy,
A. K., et al. (2006). Tissue-engineered lung: an in vivo and in vitro
comparison of polyglycolic acid and pluronic F-127 hydrogel/somatic lung
progenitor cell constructs to support tissue growth. Tissue Eng. 12, 1213–1225.
doi: 10.1089/ten.2006.12.1213
Costa, E. C., Moreira, A. F., de Melo-Diogo, D., Gaspar, V. M., Carvalho,
M. P., and Correia, I. J. (2016). 3D tumor spheroids: an overview on the
tools and techniques used for their analysis. Biotechnol. Adv. 34, 1427–1441.
doi: 10.1016/j.biotechadv.2016.11.002
Costa, M. A. (2016). The endocrine function of human placenta: an overview.
Reprod. Biomed. Online 32, 14–43. doi: 10.1016/j.rbmo.2015.10.005
D’Aiuto, L., Naciri, J., Radio, N., Tekur, S., Clayton, D., Apodaca, G.,
et al. (2018). Generation of three-dimensional human neuronal cultures:
application to modeling CNS viral infections. Stem Cell Res. Ther. 9:134.
doi: 10.1186/s13287-018-0881-6
Dang, J., Tiwari, S. K., Lichinchi, G., Qin, Y., Patil, V. S., Eroshkin, A. M., et al.
(2016). Zika virus depletes neural progenitors in human cerebral organoids
through activation of the innate immune receptor TLR3. Cell Stem Cell 19,
258–265. doi: 10.1016/j.stem.2016.04.014
de la Vega, L., Lee, C., Sharma, R., Amereh, M., and Willerth, S. M.
(2019). 3D bioprinting models of neural tissues: the current state
of the field and future directions. Brain Res. Bull. 150, 240–249.
doi: 10.1016/j.brainresbull.2019.06.007
DosSantos, M. F., Devalle, S., Aran, V., Capra, D., Roque, N. R., Coelho-Aguiar, J.,
et al. (2020). Neuromechanisms of SARS-CoV-2: A Review. Front. Neuroanat.
14:37. doi: 10.3389/fnana.2020.00037
Draft Landscape of COVID-19 Candidate Vaccines - 9 June 2020 (2020). World
Heatlh Organization.
Draft Landscape and Tracker of COVID-19 Candidate Vaccines. (2021). Available
online at: https://www.who.int/publications/m/item/draft-landscape-ofcovid-19-candidate-vaccines
(accessed February 15, 2021).
Duval, K., Grover, H., Han, L. H., Mou, Y., Pegoraro, A. F., Fredberg, J., et al.
(2017). Modeling physiological events in 2D vs. 3D cell culture. Physiology 32,
266–277. doi: 10.1152/physiol.00036.2016
Gardner, J. K., and Herbst-Kralovetz, M. M. (2016). Three-dimensional rotating
wall vessel-derived cell culture models for studying virus-host interactions.
Viruses 8:304. doi: 10.3390/v8110304
Gilpin, S. E., and Ott, H. C. (2015). Using nature’s platform to
engineer bio-artificial lungs. Ann. Am. Thorac. Soc. 12, S45–S49.
doi: 10.1513/AnnalsATS.201408-366MG
Goodwin, T. J. (2006). Three-Dimensional Human Bronchial-Tracheal Epithelial
Tissue-Like Assemblies (TLAs) as Hosts for Severe Acute Respiratory Syndrome
(SARS)-CoV Infection SARS-CoV Infection in a 3-D HBTE Tissue-Like Assembly,
NASA Technical Paper.
Gouglas, D., Thanh Le, T., Henderson, K., Kaloudis, A., Danielsen, T.,
Hammersland, N. C., et al. (2018). Estimating the cost of vaccine development
against epidemic infectious diseases: a cost minimisation study. Lancet Glob.
Heal. 6, e1386–e1396. doi: 10.1016/S2214-109X(18)30346-2
Frontiers in Materials | www.frontiersin.org 15 March 2021 | Volume 8 | Article 631373
Lawko et al. 3D Tissue Models for Vaccine Development
Han, H. W., and Hsu, S. H. (2017). Using 3D bioprinting to produce mini-brain.
Neural Regen. Res. 12, 1595–1596. doi: 10.4103/1673-5374.217325
He, B., Chen, G., and Zeng, Y. (2016). Three-dimensional cell culture
models for investigating human viruses. Virol. Sin. 31, 363–379.
doi: 10.1007/s12250-016-3889-z
Hengli Tang, A., Hammack, C., Ogden, S. C., Jin, P., Song, H., and Ming, G.
(2016). Zika virus infects human cortical neural progenitors and attenuates
their growth. Cell Stem Cell 18, 587–590. doi: 10.1016/j.stem.2016.02.016
Hepatitis. (2020). Available online at: https://www.who.int/health-topics/
hepatitis#tab=tab_1 (accessed October 4, 2020).
Hiller, T., Berg, J., Elomaa, L., Röhrs, V., Ullah, I., Schaar, K., et al. (2018).
Generation of a 3D liver model comprising human extracellular matrix in
an alginate/gelatin-based bioink by extrusion bioprinting for infection and
transduction studies. Int. J. Mol. Sci. 19:3129. doi: 10.3390/ijms19103129
Hoffmann, M., Kleine-Weber, H., Schroeder, S., Krüger, N., Herrler, T., Erichsen,
S., et al. (2020). SARS-CoV-2 cell entry depends on ACE2 and TMPRSS2
and is blocked by a clinically proven protease inhibitor. Cell 181, 271–280.e8.
doi: 10.1016/j.cell.2020.02.052
Hu, W.-S. (2020). “Overview of cell culture processes,” in Cell Culture Bioprocess
Engineering (Boca Raton: CRC Press), 1–35.
Jeon, H., Kang, K., Park, S. A., Kim, W. D., Paik, S. S., Lee, S. H., et al. (2017).
Generation of multilayered 3D structures of HepG2 cells using a bio-printing
technique. Gut Liver 11, 121–128. doi: 10.5009/gnl16010
Johansen, L. M., DeWald, L. E., Shoemaker, C. J., Hoffstrom, B. G., Lear-Rooney,
C. M., Stossel, A., et al. (2015). A screen of approved drugs and molecular
probes identifies therapeutics with anti-Ebola virus activity. Sci. Transl. Med.
7:290ra89. doi: 10.1126/scitranslmed.aaa5597
Johnson, C. D., Amato, A. R. D.’, and Puhl, D. L. (2014). Patterned and
functionalized nanofiber scaffolds in three-dimensional hydrogel constructs
enhance neurite outgrowth and directional control. J. Nueral Eng. 11:066009.
doi: 10.1088/1741-2560/11/6/066009
Kador, K. E., Grogan, S. P., Dorth,é, E. W., Venugopalan, P., Malek, M. F.,
Goldberg, J. L., et al. (2016). Control of retinal ganglion cell positioning and
neurite growth: combining 3D printing with radial electrospun scaffolds. Tissue
Eng. Part A 22, 286–294. doi: 10.1089/ten.tea.2015.0373
Kapałczy´nska, M., Kolenda, T., Przybyła, W., Zajaczkowska, M., Teresiak, A., Filas,
V., et al. (2018). 2D and 3D cell cultures – a comparison of different types of
cancer cell cultures. Arch. Med. Sci. 14, 910–919. doi: 10.5114/aoms.2016.63743
Kim, J., Koo, B. K., and Knoblich, J. A. (2020). Human organoids: model systems
for human biology and medicine. Nat. Rev. Mol. Cell Biol. 21, 571–584.
doi: 10.1038/s41580-020-0259-3
Lancaster, M. A., Renner, M., Martin, C. A., Wenzel, D., Bicknell, L. S., Hurles,
M. E., et al. (2013). Cerebral organoids model human brain development and
microcephaly. Nature 501, 373–379. doi: 10.1038/nature12517
Langhans, S. A. (2018). Three-dimensional in vitro cell culture models
in drug discovery and drug repositioning. Front. Pharmacol. 9:6.
doi: 10.3389/fphar.2018.00006
Liu, W., He, H., and Zheng, S. Y. (2020). Microfluidics in single-cell
virology: technologies and applications. Trends Biotechnol. 38, 1360–1372.
doi: 10.1016/j.tibtech.2020.04.010
Lodish, H., Berk, A., Zipursky, S. L., Matsudaira, P., Baltimore, D., and Darnell, J.
(2000). Viruses: Structure, Function, and Uses, New York, NY: WH Freeman.
Martin, I., Wendt, D., and Heberer, M. (2004). The role of bioreactors in tissue
engineering. Trends Biotechnol. 22, 80–86. doi: 10.1016/j.tibtech.2003.12.001
Mazzocchi, A., Devarasetty, M., Huntwork, R., Soker, S., and Skardal,
A. (2019). Optimization of collagen type I-hyaluronan hybrid bioink
for 3D bioprinted liver microenvironments. Biofabrication 11:15003.
doi: 10.1088/1758-5090/aae543
Meneses, J. D. A., Ishigami, A. C., De Mello, L. M., De Albuquerque, L. L., De
Brito, C. A. A., Cordeiro, M. T., et al. (2017). Lessons learned at the epicenter
of Brazil’s congenital Zika epidemic: evidence from 87 confirmed cases. Clin.
Infect. Dis. 64, 1302–1308. doi: 10.1093/cid/cix166
Miller, A. J., and Spence, J. R. (2017). In vitro models to study human
lung development, disease and homeostasis. Physiology 32, 246–260.
doi: 10.1152/physiol.00041.2016
Miner, J. J., Cao, B., Govero, J., Smith, A. M., Fernandez, E., Cabrera, O. H., et al.
(2016). Zika virus infection during pregnancy in mice causes placental damage
and fetal demise. Cell 165, 1081–1091. doi: 10.1016/j.cell.2016.05.008
Mondrinos, M. J., Koutzaki, S., Lelkes, P. I., and Finck, C. M. (2007).
A tissue-engineered model of fetal distal lung tissue. Am. J. Physiol.
Lung Cell. Mol. Physiol. 293, 639–650. doi: 10.1152/ajplung.004
03.2006
Monteil, V., Kwon, H., Prado, P., Hagelkrüys, A., Wimmer, R. A., Stahl, M.,
et al. (2020). Inhibition of SARS-CoV-2 infections in engineered human
tissues using clinical-grade soluble human ACE2. Cell 181, 905–913.e7.
doi: 10.1016/j.cell.2020.04.004
Murphy, S. V., and Atala, A. (2014). 3D bioprinting of tissues and organs. Nat.
Biotechnol. 32, 773–785. doi: 10.1038/nbt.2958
Musso, D., Nilles, E. J., and Cao-Lormeau, V. M. (2014). Rapid spread of
emerging Zika virus in the Pacific area. Clin. Microbiol. Infect. 20, O595–O596.
doi: 10.1111/1469-0691.12707
Nguyen, D. G., Funk, J., Robbins, J. B., Crogan-Grundy, C., Presnell, S. C., Singer,
T., et al. (2016). Bioprinted 3D primary liver tissues allow assessment of organlevel
response to clinical drug induced toxicity in vitro. PLoS ONE 11:e0158674.
doi: 10.1371/journal.pone.0158674
Ni, W., Yang, X., Yang, D., Bao, J., Li, R., Xiao, Y., et al. (2020). Role of
angiotensin-converting enzyme 2 (ACE2) in COVID-19. Crit. Care 24:422.
doi: 10.1186/s13054-020-03120-0
NIAID (2020). Vaccine Types | NIH: National Institute of Allergy and Infectious
Diseases. Available online at: https://www.niaid.nih.gov/research/vaccine-types
(accessed August 23, 2020).
Nie, Y. Z., Zheng, Y. W., Miyakawa, K., Murata, S., Zhang, R. R., Sekine, K.,
et al. (2018). Recapitulation of hepatitis B virus–host interactions in liver
organoids from human induced pluripotent stem cells. EBioMedicine 35,
114–123. doi: 10.1016/j.ebiom.2018.08.014
Ortega-Prieto, A. M., Skelton, J. K., Wai, S. N., Large, E., Lussignol, M.,
Vizcay-Barrena, G., et al. (2018). 3D microfluidic liver cultures as a
physiological preclinical tool for hepatitis B virus infection. Nat. Commun.
9:682. doi: 10.1038/s41467-018-02969-8
Ozbolat, I. T. (2015). Bioprinting scale-up tissue and organ
constructs for transplantation. Trends Biotechnol. 33, 395–400.
doi: 10.1016/j.tibtech.2015.04.005
Peng, W., Datta, P., Ayan, B., Ozbolat, V., Sosnoski, D., and Ozbolat, I. T. (2017).
3D bioprinting for drug discovery and development in pharmaceutics. Acta
Biomater. 57, 26–46. doi: 10.1016/j.actbio.2017.05.025
Plunkett, N., and O’Brien, F. J. (2011). Bioreactors in tissue engineering. Technol.
Heal. Care 19, 55–69. doi: 10.3233/THC-2011-0605
Qian, X., Nguyen, H. N., Song, M. M., Hadiono, C., Ogden, S. C., Hammack,
C., et al. (2016). Brain-region-specific organoids using mini-bioreactors for
modeling ZIKV exposure. Cell 165, 1238–1254. doi: 10.1016/j.cell.2016.04.032
Radigan, K. A., Misharin, A. V., Chi, M., and Budinger, G. R. S. (2015). Modeling
human influenza infection in the laboratory. Infect. Drug Resist. 8, 311–320.
doi: 10.2147/IDR.S58551
Ravi, M., Paramesh, V., Kaviya, S. R., Anuradha, E., and Paul Solomon, F. D.
(2015). 3D cell culture systems: advantages and applications. J. Cell. Physiol.
230, 16–26. doi: 10.1002/jcp.24683
Rock, J. R., Onaitis, M. W., Rawlins, E. L., Lu, Y., Clark, C. P., Xue, Y., et al. (2009).
Basal cells as stem cells of the mouse trachea and human airway epithelium.
Proc. Natl. Acad. Sci. U. S. A. 106, 12771–12775. doi: 10.1073/pnas.09068
50106
Rosellini, A., Freer, G., Quaranta, P., Dovere, V., Menichini, M., Maggi, F.,
et al. (2019). Enhanced in vitro virus expression using 3-dimensional
cell culture spheroids for infection. J. Virol. Methods 265, 99–104.
doi: 10.1016/j.jviromet.2018.12.017
Rossi, G., Manfrin, A., and Lutolf, M. P. (2018). Progress and potential in organoid
research. Nat. Rev. Genet. 19, 671–687. doi: 10.1038/s41576-018-0051-9
Ruedinger, F., Lavrentieva, A., Blume, C., Pepelanova, I., and Scheper, T.
(2015). Hydrogels for 3D mammalian cell culture: a starting guide
for laboratory practice. Appl. Microbiol. Biotechnol. 99, 623–636.
doi: 10.1007/s00253-014-6253-y
Ryan, J. A. (2020). Introduction to Animal Cell Culture. Available online at: https://
www.corning.com/catalog/cls/documents/application-notes/CLS-AN-042.pdf
(accessed August 20, 2020).
Ryu, N. E., Lee, S. H., and Park, H. (2019). Spheroid culture system
methods and applications for mesenchymal stem cells. Cells 8, 1–13.
doi: 10.3390/cells8121620
Frontiers in Materials | www.frontiersin.org 16 March 2021 | Volume 8 | Article 631373
Lawko et al. 3D Tissue Models for Vaccine Development
Simpson, C., Lee, S. S., Lee, C. S., and Yamauchi, Y. (2018). Microfluidics:
an untapped resource in viral diagnostics and viral cell biology. Curr. Clin.
Microbiol. Rep. 5, 245–251. doi: 10.1007/s40588-018-0105-y
Singh, K., and Mehta, S. (2016). The clinical development process for
a novel preventive vaccine: an overview. J. Postgrad. Med. 62:4.
doi: 10.4103/0022-3859.173187
Takayama, K. (2020). Trends in pharmacological sciences in vitro and
animal models for SARS-CoV- 2 research trends in pharmacological
sciences. Trends Pharmacol. Sci. 41, 513–517. doi: 10.1016/j.tips.2020.
05.005
Takebe, T., Sekine, K., Enomura, M., Koike, H., Kimura, M., Ogaeri, T.,
et al. (2013). Vascularized and functional human liver from an iPSCderived
organ bud transplant. Nature 499, 481–484. doi: 10.1038/nature
12271
Tan, Q., Choi, K. M., Sicard, D., and Tschumperlin, D. J. (2018). Human airway
organoid engineering as a step toward lung regeneration and disease modeling.
Biomaterials 113, 118–132. doi: 10.1016/j.biomaterials.2016.10.046
Tang, H., Abouleila, Y., Si, L., Ortega-Prieto, A. M., Mummery, C. L., Ingber, D.
E., et al. (2020). Human organs-on-chips for virology. Trends Microbiol. 28,
934–946. doi: 10.1016/j.tim.2020.06.005
Tatara, A. M. (2020). Role of tissue engineering in COVID-19 and future viral
outbreaks. Tissue Eng. Part A 6, 468–474. doi: 10.1089/ten.tea.2020.0094
Thanh Le, T., Andreadakis, Z., Kumar, A., Gómez Román, R., Tollefsen, S., Saville,
M., et al. (2020). The COVID-19 vaccine development landscape. Nat. Rev.
Drug Discov. 19, 305–306. doi: 10.1038/d41573-020-00151-8
Thomas, D., Burns, J., Audette, J., and Analysis, A. C. (2016). Clinical Development
Success Rates 2006–2015. The Biotechnology Innovation Organization.
Tibbitt, M. W., and Anseth, K. S. (2009). Hydrogels as extracellular matrix mimics
for 3D cell culture. Biotechnol. Bioeng. 103, 655–663. doi: 10.1002/bit.22361
Vetter, V., Denizer, G., Friedland, L. R., Krishnan, J., and Shapiro, M. (2018).
Understanding modern-day vaccines: what you need to know. Ann. Med. 50,
110–120. doi: 10.1080/07853890.2017.1407035
Wu, Q., Liu, J., Wang, X., Feng, L., Wu, J., Zhu, X., et al. (2020). Organ-on-achip:
recent breakthroughs and future prospects. Biomed. Eng. Online 19, 1–19.
doi: 10.1186/s12938-020-0752-0
Xu, H., Jiao, Y., Qin, S., Zhao, W., Chu, Q., and Wu, K. (2018). Organoid
technology in disease modelling, drug development, personalized
treatment and regeneration medicine. Exp. Hematol. Oncol. 7:30.
doi: 10.1186/s40164-018-0122-9
Yin, X., Mead, B. E., Safaee, H., Langer, R., Karp, J. M., and Levy,
O. (2016). Engineering stem cell organoids. Cell Stem Cell 18, 25–38.
doi: 10.1016/j.stem.2015.12.005
Zhang, B., Korolj, A., Lai, B. F. L., and Radisic, M. (2018). Advances in organ-on-achip
engineering. Nat. Rev. Mater. 3, 257–278. doi: 10.1038/s41578-018-0034-7
Zhang, Z., Xu, H., Mazza, G., Zhang, M., Frenguelli, L., Liu, Q., et al. (2019).
Decellularized human liver scaffold-based three-dimensional culture system
facilitate hepatitis B virus infection. J. Biomed. Mater. Res. Part A 107,
1744–1753. doi: 10.1002/jbm.a.36690
Zhu, X., and Ding, X. (2017). Study on a 3D hydrogel-based culture model for
characterizing growth of fibroblasts under viral infection and drug treatment.
SLAS Discov. 22, 626–634. doi: 10.1177/2472555217701247
Zhuang, P., Sun, A. X., An, J., Chua, C. K., and Chew, S. Y. (2018). 3D neural
tissue models: from spheroids to bioprinting. Biomaterials 154, 113–133.
doi: 10.1016/j.biomaterials.2017.10.002
Ziegler, C. G. K., Allon, S. J., Nyquist, S. K., Mbano, I. M., Miao, V. N., Tzouanas, C.
N., et al. (2020). SARS-CoV-2 receptor ACE2 Is an interferon-stimulated gene
in human airway epithelial cells and is detected in specific cell subsets across
tissues. Cell 181, 1016–1035.e19. doi: 10.1016/j.cell.2020.04.035
Conflict of Interest: The authors declare that the research was conducted in the
absence of any commercial or financial relationships that could be construed as a
potential conflict of interest.
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