| Literature DB >> 35712780 |
Janko Kajtez1,2, Milan Finn Wesseler3, Marcella Birtele1, Farinaz Riyahi Khorasgani2, Daniella Rylander Ottosson1, Arto Heiskanen2, Tom Kamperman4, Jeroen Leijten4, Alberto Martínez-Serrano5, Niels B Larsen3, Thomas E Angelini6, Malin Parmar1, Johan U Lind3, Jenny Emnéus2.
Abstract
Human in vitro models of neural tissue with tunable microenvironment and defined spatial arrangement are needed to facilitate studies of brain development and disease. Towards this end, embedded printing inside granular gels holds great promise as it allows precise patterning of extremely soft tissue constructs. However, granular printing support formulations are restricted to only a handful of materials. Therefore, there has been a need for novel materials that take advantage of versatile biomimicry of bulk hydrogels while providing high-fidelity support for embedded printing akin to granular gels. To address this need, Authors present a modular platform for bioengineering of neuronal networks via direct embedded 3D printing of human stem cells inside Self-Healing Annealable Particle-Extracellular matrix (SHAPE) composites. SHAPE composites consist of soft microgels immersed in viscous extracellular-matrix solution to enable precise and programmable patterning of human stem cells and consequent generation mature subtype-specific neurons that extend projections into the volume of the annealed support. The developed approach further allows multi-ink deposition, live spatial and temporal monitoring of oxygen levels, as well as creation of vascular-like channels. Due to its modularity and versatility, SHAPE biomanufacturing toolbox has potential to be used in applications beyond functional modeling of mechanically sensitive neural constructs.Entities:
Keywords: embedded 3D printing; granular gels; microgels; neural stem cells; neural tissue engineering
Mesh:
Substances:
Year: 2022 PMID: 35712780 PMCID: PMC9443452 DOI: 10.1002/advs.202201392
Source DB: PubMed Journal: Adv Sci (Weinh) ISSN: 2198-3844 Impact factor: 17.521
Figure 1The methodological concept and rheological characterization. A) Graphical illustration of the printing process in SHAPE support bath. B) Storage (G’) and loss moduli (G”) of jammed microgels and SHAPE material show weak frequency dependence, while dispersed microgel system exhibits drastically lower moduli with strong frequency dependence. C) Measurements of shear moduli as a function of applied strain amplitude show solid‐to‐liquid transition. D) Yield stress of the formulated material systems is determined by fitting a classic Herschel–Bulkley model to shear stress values measured at many constant strain rates. E) Stability of storage modulus for SHAPE material support at 4 °C over a period of 2 h. F) Increase in storage modulus when temperature is raised from 4 to 37 °C indicates temperature‐induced collagen crosslinking. G) The top row displays photographs of SHAPE hydrogel before (left) and after (right) annealing and molding. Corresponding reflectance microscopy images in the bottom row show the formation of collagen bundles in the annealed support. Jammed microgels contain ≈100% particle volume fraction, while dispersed microgels and SHAPE contain ≈70% particle volume fraction. n = 3 for rheological characterization in B, C, D, while rheological stability and annealing dynamics in E) and F) are displayed for one sample.
Figure 2Embedded 3D printing in SHAPE hydrogel support. A) Fluorescent images of hNSCs labeled with Calcein‐AM show the fidelity of embedded printing of a programmed path (purple, top) supports with varying packing density and continuous phase composition (left, blue). Scale bar 1 mm. B) Example of a printing process showing omnidirectional printing capability. Polystyrene beads were used in the ink instead of cells to visualize the structure. C) Concentric rings printed from three hNSC inks. D) Stacked crosshatch structure printed from three hNSC inks. E) Magnified view of a junction in a stacked crosshatch structure showing intact layers clear vertical separation. Distinct hNSC inks were created by staining live cells with Calcein‐AM (green), Calcein‐Red‐AM (red), and Hoechst (blue). F) Alternative SHAPE formulations provide diverse annealing mechanisms. While keeping the same granular component, we varied the contents of the continuous phase: 10% gelatin (left), 30% PEG‐DA (middle), and 1% alginate (right). The images show annealed SHAPE supports displaying structural stability with visible printed constructs inside of each hydrogel.
Figure 3Generation of authentic human neurons within 3D printed constructs. A) Photograph of a 3D printed construct in annealed SHAPE support after 2 months of differentiation. B) Confocal image of the same construct labeled with Calcein‐AM. C) Maximum intensity projection of a 200 µm optical section showing that neural projections extend in the volume between printed lines. D) Quantification of the extent of projection outgrowth away from a 3D printed structure as a function of the differentiation time. E) Orthogonal projection showing that the structural integrity with defined features in different layers are preserved. F) Fluorescence images of immunostained 3D printed construct after 2 months of differentiation displaying neuronal and dopaminergic markers (β‐III tubulin and TH respectively). G) RT‐qPCR gene expression analysis of the printed construct at 3 different time points indicating midbrain patterning and neuronal maturation. Nondifferentiated hNSCs were used as a reference. H) Maximum projection fluorescence image of neurons in a 3D printed construct resembling brain meanders with a 3D close‐up view of a selected segment. I) Illustration showing the printing of cells with orthogonal differentiation trajectories by using 2 inks containing hNSCs with different predefined fates. Inks were printed in consecutive order in concentric circle design within the same SHAPE support. The outer radius of the inner and outer disk is 2 and 4 mm, respectively. J) Fluorescence images of fixed and immunolabeled constructs after 1 month of differentiation. DNA counterstain shows the presence of cells both in the inner and outer ring but staining for GFAP and β‐III tubulin reveal distinct protein expression characteristics between cells generated from each ink. Cells display elongated morphology indicating successful differentiation.
Figure 4Functional assessment of neuronal activity. A) Differential fluorescence intensity profiles showing changes in intracellular Ca2+ as a function of time (left); regions of interest marked for intensity profiling (middle); selected timeframes displaying Ca2+ transient in a cell marked by an arrow (right). B) Image of a microelectrode targeting the synapsin‐GFP neuron during whole‐cell patch‐clamp recordings. C) Representative trace of whole‐cell patch‐clamp recordings performed in current‐clamp mode displaying induced action potentials (APs) elicited by a neuronal cell. D) Representative trace of whole‐cell patch‐clamp recordings performed in voltage‐clamp mode showing the presence of inward sodium/outward potassium currents in the targeted cell. E) Resting membrane potential (RMP) measured during electrophysiological recordings demonstrating a hyperpolarized state, typical of neuronal cells. F) Analysis of APs elicited by recorded cells (n = 22).
Figure 5Oxygen mapping in 3D printed neuronal constructs. A) Graphical illustration depicting the 3D oxygen mapping approach. Oxygen sensitive polystyrene microprobes are integrated in the printed cellular constructs both by mixing with the SHAPE printing support and by mixing with the stem cell ink. Oxygen levels are measured through optical readout based on oxygen‐mediated quenching of phosphorescence. B) Simultaneously acquired 3D oxygen and live‐cell image stacks of a 3D printed cellular disk with collapsed Z dimension (top) and collapsed projection of 18 vertical planes extracted through a vertical center axis in rotational steps of 20° (bottom). C) Oxygen map of 3D printed neuronal construct with ascending grid spacing with collapsed Z‐dimension (top) and collapsed side view of the tissue construct area (bottom). D) Patterning induced oxygen gradient in the construct with ascending grid spacing. E) Influence of infill density on the oxygenation of the 3D printed construct. F) The effect of line thickness (extrusion rate) on the construct oxygenation at two different infill densities. G) Monitoring of oxygen tension over time.
Figure 6Printing vascular‐like channels inside SHAPE material support. A) Images showing the process of generating channels by printing and evacuating sacrificial ink: solid sacrificial gelatin structure visible immediately after printing (left), annealed support (middle), liquid sacrificial gelatin displaced and filled with a dye (right). B) Channels before (left) and after (right) displacement of the sacrificial gelatin structure as seen under brightfield microscope. Channels are filled with polystyrene beads for visualization. C) Channel cross section under phase contrast microscope displaying collagen fibers in the bulk around the channel. D) Direct writing of sacrificial gelatin ink produces printed strands with uniform dimensions as indicated by the measurements of channel radius along the printed path. E) Time‐lapse images exhibiting perfusion of a branching sacrificial structure show simultaneous gelatin displacement of both channel branches indicating successful strand fusion at the branching point.