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Review
. 2022 Feb 14:10:764682.
doi: 10.3389/fbioe.2022.764682. eCollection 2022.

Review on Multicomponent Hydrogel Bioinks Based on Natural Biomaterials for Bioprinting 3D Liver Tissues

Affiliations
Review

Review on Multicomponent Hydrogel Bioinks Based on Natural Biomaterials for Bioprinting 3D Liver Tissues

Daekeun Kim et al. Front Bioeng Biotechnol. .

Abstract

Three-dimensional (3D)-printed in vitro tissue models have been used in various biomedical fields owing to numerous advantages such as enhancements in cell response and functionality. In liver tissue engineering, several studies have been reported using 3D-printed liver tissue models with improved cellular responses and functions in drug screening, liver disease, and liver regenerative medicine. However, the application of conventional single-component bioinks for the printing of 3D in vitro liver constructs remains problematic because of the complex structural and physiological characteristics of the liver. The use of multicomponent bioinks has become an attractive strategy for bioprinting 3D functional in vitro liver tissue models because of the various advantages of multicomponent bioinks, such as improved mechanical properties of the printed tissue construct and cell functionality. Therefore, it is essential to review various 3D bioprinting techniques and multicomponent hydrogel bioinks proposed for liver tissue engineering to suggest future directions for liver tissue engineering. Accordingly, we herein review multicomponent bioinks for 3D-bioprinted liver tissues. We first describe the fabrication methods capable of printing multicomponent bioinks and introduce considerations for bioprinting. We subsequently categorize and evaluate the materials typically utilized for multicomponent bioinks based on their characteristics. In addition, we also review recent studies for the application of multicomponent bioinks to fabricate in vitro liver tissue models. Finally, we discuss the limitations of current studies and emphasize aspects that must be resolved to enhance the future applicability of such bioinks.

Keywords: 3D bioprinting; 3D-bioprinted liver; bioink; biomaterial; hepatic regeneration; hydrogel; tissue engineering.

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Conflict of interest statement

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.

Figures

FIGURE 1
FIGURE 1
Schematic illustration and comparison of commonly utilized 3D bioprinting techniques for liver tissue engineering (A) Schematic illustration of 3D bioprinting techniques, such as inkjet-based bioprinting, light-assisted printing system, and extrusion-based bioprinting. (B) Comparison of 3D bioprinting techniques in terms of material selection, aspect ratio, and resolution. Representative images of inkjet-based, light-assisted, and extrusion-based printing. Reproduced with permission from Faulkner-Jones et al. (2015), Ma et al. (2016), Hiller et al. (2018).
FIGURE 2
FIGURE 2
Schematic illustration of four interconnecting networks in multicomponent hydrogel bioinks (A) Homogeneous networks (B) Interpenetrating networks (C) Nanocomposite networks (D) Supramolecular networks. Reproduced with permission from (Li et al., 2021).
FIGURE 3
FIGURE 3
Alginate-based multicomponent bioinks. (A) Rheological property of two different bioinks, 4% GelMA and 135ACG. (a) Flow behaviors of two different bioinks. (b) Elastic modulus ( G' ) and viscous modulus ( G" ) of the two different bioinks as a function of oscillatory frequency. (c) Compressive modulus changes of 135ACG gels with/without cells over 14 days. Reproduced with permission from Wu et al. (2020). (B) Characteristics of algMC bioink. (a) Stereo microscopic image of a cell-free core–shell strand with compartmentalized core and shell structure within the strand. Scale bar: 2 mm. (b) Viability of HepG2 cells encapsulated in algMC bioink comparing two conditions (with matrigel vs without matrigel) (n = 6, mean ± SD, ****p < 0.0001). (c) Proliferation of HepG2 cells encapsulated in algMC bioink comparing two conditions (with matrigel vs without matrigel) (n = 3, mean ± SD, *p < 0.05). (d) Morphology and organization of HepG2 encapsulated in algMC comparing two conditions (with matrigel vs without matrigel). Reproduced with permission from Taymour et al. (2021).
FIGURE 4
FIGURE 4
Collagen-based multicomponent bioinks. (A) Characteristics of photocrosslinkable modified collagen bioink (Methacrylamide-modified RCPhC1 (RCPhC1-MA), Norbornene-functionalized RCPhC1 (RCPhC1-NB), and Thiolated RCPhC1 (RCPhC1-SH)) (a) Rheological property on 7.5 and 10 w/v % solutions of RCPhC1-NB/SH and RCPhC1-MA in the presence of 2 mol% Li-TPO-L at 37°C. (b) Printability test of photocrosslinkable collagen-based bioinks using different logos (TU Wien, B-PHOT, and PBM) (left panel – 10 w/v % RCPh1-NB/SH, right panel – RCPhC1-MA). Scale bar: 100 µm. DS: degree of substitution. (c) Laser scanning microscopy (LSM) images of living ASCs-GFP printed in RCPhC1-NB/SH-based cubes at different polymer concentrations and laser power intensities. (d) Cell proliferation trends as a function of time in cubes printed using RCPhC1-NB/SH at different polymer concentrations and laser power conditions. Reproduced with permission from (Tytgat et al., 2020).
FIGURE 5
FIGURE 5
Gelatin-based multicomponent bioinks. (A) Characteristics of hybrid bioink of GelMA and collagen. (a) Shape fidelity of the acellular construct fabricated by GelMA and hybrid bioink of GelMA and collagen. Scale bar: 1 mm. (b) Cell viability of the MCF-7 encapsulated in GelMA/collagen with different Ru/SPS concentrations. (c) Live dead images of MCF-7 encapsulated in the hybrid bioink of GelMA and collagen with photoinitiator Ru/SPS (0.2 mM/2 mM and 2 mM/20 mM). Scale bar = 100 μm. Reproduced with permission from Lim et al. (2016). (B) Characteristics of GelMA. (a) Shape fidelity of the cell-laden construct fabricated by GelMA 3. Scale bar: 200 μm. (b) The viability of HepG2 cells respective encapsulated in GelMA 1, GelMA 2, and GelMA 3 during 5 days culture. Reproduced with permission from Cui et al. (2019).
FIGURE 6
FIGURE 6
dECM-based multicomponent bioinks. (A) Characteristics of hybrid bioink of VdECM and alginate. (a) Schematic depiction of the bio-blood vessel (BBV) printing using hybrid bioink with co-axial nozzle. (b) Shear-thinning behavior of the hybrid hydrogel. (c) The complex modulus of crosslinked hybrid bioink. (d) The proliferation rate of endothelial progenitor cells (EPCs) encapsulated in different types of bioinks (*p < 0.1, **p < 0.01). Reproduced with permission from Gao et al. (2017). (B) Characteristics of dECM bioinks with Ru/SPS (dERS). (a) Shear-thinning behavior of two different dECM-based dERS bioinks (cornea dECM (co-dECM) and heart dECM (hdECM)). (b) The complex modulus of crosslinked dERS bioinks compared with dECM bioinks. (c) Improved mechanical properties of dERS bioinks after photocrosslinking and thermal crosslinking process. *p < 0.1, **p < 0.01. (d) Cell viability of hiPSC-CMs embedded in the printed construct with hdECM-based bioinks at days 1, 3, and 7 (hdECM vs hdERS). (e) Metabolic activity of predifferentiated keratocytes in the printed construct with co-dECM bioinks at day 1 and day 7 (co-dECM vs co-dERS). ***p < 0.001. Reproduced with permission from Kim et al. (2021).
FIGURE 7
FIGURE 7
Multi-component hydrogel bioink-based 3D-printed liver tissue models. (A) 3D-printed liver tissue for infection and transduction studies. (a) 3D-printed liver tissue construct with HepaRG cell-laden hybrid alginate–gelatin–human extracellular matrix (hECM). (b) Comparison of AAV2.6 transduction and distribution within the multi-component bioink-based 3D-printed liver tissue construct with hECM or without hECM 7 days after printing. Blue: nuclei, green: AAV vectors. Scale bar: 200 μm. (c) Comparison of shRNA-mediated hCYcB RNA knockdown within the printed liver tissue construct with hECM or without hECM 7 days after printing. Results are shown as mean. ***p≤0.001. (d) Comparison of adenovirus replication within the 3D-printed liver tissue construct with hECM or without hECM. Reproduced with permission from Hiller et al. (2018). (B) 3D lobule-like microtissue assembled with co-culture 3D-printed micromodules. (a) The proliferation of the cells within the lobule-like 3D-printed microtissue for 7 days. (b) The evaluation of albumin secretion of HepG2 cells in mono-cultured 3D microtissue and co-cultured 3D microtissue for 7 days. Reproduced with permission from Cui et al. (2019). (C) 3D-printed bicellular liver tissue construct with in-direct co-culture honeycomb structure. (a) Top and side view of the embedded-printed structures with a height of 6.8 mm. Scale bars: 5 mm. (b) Changes in growth, proliferation, and morphology of cells embedded in compartmentalized bicellular liver-mimetic construct over 2 weeks. Reproduced with permission from Wu et al. (2020). (D) 3D-printed core–shell strand liver tissue construct. (a) Visualization of cell distribution in core–shell structure [DIL-labeled NIH3T3 (cyan), DIO-labeled HepG2 (red)]. Scale bar: 1000 μm. (b) Evaluation of hepatic function for the presence of co-culture with supporting cells or ECM components in the printed construct (purple—albumin stained). Reproduced with permission from Taymour et al. (2021). (E) 3D-printed tri-culture liver tissue construct with biomimetic liver lobule-like pattern. (a) Images taken in fluorescence and brightfield channels revealing the patterns of fluorescently labeled hiPSC-HPCs (green) in 5% (wt/vol) GelMA and support cells (red) in 2.5% (wt/vol) GelMA containing 1% GMHA on day 0. Scale bar: 500 μm. (b) Comparison of aggregation and intercellular interaction of hiPSC-HPC in 3D HPC-only construct and 3D triculture construct on days 0 and 7 [albumin (Alb), E-cadherin (E-cad), and nucleus (Dapi)]. Scale bars: 500 μm in bright field 100 μm in fluorescent images. (c) Comparison of albumin secretion levels of hiPSC-HPCs in three different conditions over time. (d) Comparison of urea secretion levels of HPCs in three different conditions over time. Error bars represent SEM, and n = 3 for all data points. Reproduced with permission from Ma et al. (2016).

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