Fabrication of functional three-dimensional tissues by stacking cell sheets in vitro

The fabrication of 3D tissues retaining the original functions of tissues/organs in vitro is crucial for optimal tissue engineering and regenerative medicine. The fabrication of 3D tissues also contributes to the establishment of in vitro tissue/organ models for drug screening. Our laboratory has developed a fabrication system for functional 3D tissues by stacking cell sheets of confluent cultured cells detached from a temperature-responsive culture dish. Here we describe the protocols for the fabrication of 3D tissues by cell sheet engineering. Three-dimensional cardiac tissues fabricated by stacking cardiac cell sheets pulsate spontaneously, synchronously and macroscopically. Via this protocol, it is also possible to fabricate other tissues, such as 3D tissue including capillary-like prevascular networks, from endothelial cells sandwiched between layered cell sheets. Cell sheet stacking technology promises to provide in vitro tissue/organ models and more effective therapies for curing tissue/organ failures.     

Three-Dimensional (3D) cell culture monitoring: Opportunities and challenges for impedance spectroscopy

Three-dimensional (3D) cell culture has developed rapidly over the past 5–10 years with the goal of better replicating human physiology and tissue complexity in the laboratory. Quantifying cellular responses is fundamental in understanding how cells and tissues respond during their growth cycle and in response to external stimuli. There is a need to develop and validate tools that can give insight into cell number, viability, and distribution in real-time, nondestructively and without the use of stains or other labelling processes. Impedance spectroscopy can address all of these challenges and is currently used both commercially and in academic laboratories to measure cellular processes in 2D cell culture systems. However, its use in 3D cultures is not straight forward due to the complexity of the electrical circuit model of 3D tissues. In addition, there are challenges in the design and integration of electrodes within 3D cell culture systems. Researchers have used a range of strategies to implement impedance spectroscopy in 3D systems. This review examines electrode design, integration, and outcomes of a range of impedance spectroscopy studies and multiparametric systems relevant to 3D cell cultures. While these systems provide whole culture data, impedance tomography approaches have shown how this technique can be used to achieve spatial resolution. This review demonstrates how impedance spectroscopy and tomography can be used to provide real-time sensing in 3D cell cultures, but challenges remain in integrating electrodes without affecting cell culture functionality. If these challenges can be addressed and more realistic electrical models for 3D tissues developed, the implementation of impedance-based systems will be able to provide real-time, quantitative tracking of 3D cell culture systems.     

In vitro and in vivo translational models for rare liver diseases

A challenge in developing effective treatments is the modeling of the human disease using in vitro and in vivo systems. Animal models have played a critical role in the understanding of disease pathophysiology, target validation, and evaluation of novel therapeutic agents. However, as the success rate from entry into clinical testing to drug approval remains low, it is critical to have high quality and well-validated models reflective of the disease condition. Additional experimental models are being developed based on functional in vitro 3D tissue models such as organoids and 3D bioprinted tissues. Because these 3D tissue models mimic closer the architecture, cell composition and physiology of native tissues, they are now being used as screening platforms in drug discovery and development and for tissue transplant in regenerative medicine. Here we review the current state-of-art of in vitro and in vivo translational models for the development of therapies for rare diseases of the liver.     

Three-dimensional bioprinting human cardiac tissue chips of using a painting needle method

Three-dimensional (3D) printers are attracting attention as a method for arranging and building cells in three dimensions. Bioprinting technology has potential in tissue engineering for the fabrication of scaffolds, cells, and tissues. However, these various printing technologies have limitations with respect to print resolution and due to the characteristics of bioink such as viscosity. We report a method for constructing of 3D tissues with a “microscopic painting device using a painting needle method” that, when used with the layer-by-layer (LbL) cell coating technique, replaces conventional methods. This method is a technique of attaching the high viscosity bioink to the painting needle tip and arranging it on a substrate, and can construct 3D tissues without damage to cells. Cell viability is the same before and after painting. We used this biofabrication device to construct 3D cardiac tissue (LbL-3D Heart) using human-induced pluripotent stem cell–derived cardiomyocytes. The constructed LbL-3D Heart chips had multiple layers with a thickness of 60 µm, a diameter of 1.1 mm, and showed synchronous beating (50–60 beats per min). The aforementioned device and method of 3D tissue construction can be applied to various kinds of tissue models and would be a useful tool for pharmaceutical applications.     

Modeling tissue morphogenesis and cancer in 3D

Three-dimensional (3D) in vitro models span the gap between two-dimensional cell cultures and whole-animal systems. By mimicking features of the in vivo environment and taking advantage of the same tools used to study cells in traditional cell culture, 3D models provide unique perspectives on the behavior of stem cells, developing tissues and organs, and tumors. These models may help to accelerate translational research in cancer biology and tissue engineering.     

3D Bioprinted cancer models: Revolutionizing personalized cancer therapy

After cardiovascular disease, cancer is the leading cause of death worldwide with devastating health and economic consequences, particularly in developing countries. Inter-patient variations in anti-cancer drug responses further limit the success of therapeutic interventions. Therefore, personalized medicines approach is key for this patient group involving molecular and genetic screening and appropriate stratification of patients to treatment regimen that they will respond to. However, the knowledge related to adequate risk stratification methods identifying patients who will respond to specific anti-cancer agents is still lacking in many cancer types. Recent advancements in three-dimensional (3D) bioprinting technology, have been extensively used to generate representative bioengineered tumor in vitro models, which recapitulate the human tumor tissues and microenvironment for high-throughput drug screening. Bioprinting process involves the precise deposition of multiple layers of different cell types in combination with biomaterials capable of generating 3D bioengineered tissues based on a computer-aided design. Bioprinted cancer models containing patient-derived cancer and stromal cells together with genetic material, extracellular matrix proteins and growth factors, represent a promising approach for personalized cancer therapy screening. Both natural and synthetic biopolymers have been utilized to support the proliferation of cells and biological material within the personalized tumor models/implants. These models can provide a physiologically pertinent cell–cell and cell–matrix interactions by mimicking the 3D heterogeneity of real tumors. Here, we reviewed the potential applications of 3D bioprinted tumor constructs as personalized in vitro models in anticancer drug screening and in the establishment of precision treatment regimens.     

The third dimension bridges the gap between cell culture and live tissue

Moving from cell monolayers to three-dimensional (3D) cultures is motivated by the need to work with cellular models that mimic the functions of living tissues. Essential cellular functions that are present in tissues are missed by 'petri dish'-based cell cultures. This limits their potential to predict the cellular responses of real organisms. However, establishing 3D cultures as a mainstream approach requires the development of standard protocols, new cell lines and quantitative analysis methods, which include well-suited three-dimensional imaging techniques. We believe that 3D cultures will have a strong impact on drug screening and will also decrease the use of laboratory animals, for example, in the context of toxicity assays.     

Bioengineered 3D Human Kidney Tissue,a Platform for the Determination of Nephrotoxicity

The staggering cost of bringing a drug to market coupled with the extremely high failure rate of prospective compounds in early phase clinical trials due to unexpected human toxicity makes it imperative that more relevant human models be developed to better predict drug toxicity. Drug–induced nephrotoxicity remains especially difficult to predict in both pre-clinical and clinical settings and is often undetected until patient hospitalization. Current pre-clinical methods of determining renal toxicity include 2D cell cultures and animal models, both of which are incapable of fully recapitulating the in vivo human response to drugs, contributing to the high failure rate upon clinical trials. We have bioengineered a 3D kidney tissue model using immortalized human renal cortical epithelial cells with kidney functions similar to that found in vivo. These 3D tissues were compared to 2D cells in terms of both acute (3 days) and chronic (2 weeks) toxicity induced by Cisplatin, Gentamicin, and Doxorubicin using both traditional LDH secretion and the pre-clinical biomarkers Kim-1 and NGAL as assessments of toxicity. The 3D tissues were more sensitive to drug-induced toxicity and, unlike the 2D cells, were capable of being used to monitor chronic toxicity due to repeat dosing. The inclusion of this tissue model in drug testing prior to the initiation of phase I clinical trials would allow for better prediction of the nephrotoxic effects of new drugs.     

Development of a finite element musculoskeletal model with the ability to predict contractions of three-dimensional muscles

Representation of realistic muscle geometries is needed for systematic biomechanical simulation of musculoskeletal systems. Most of the previous musculoskeletal models are based on multibody dynamics simulation with muscles simplified as one-dimensional (1D) line-segments without accounting for the large muscle attachment areas, spatial fibre alignment within muscles and contact and wrapping between muscles and surrounding tissues. In previous musculoskeletal models with three-dimensional (3D) muscles, contractions of muscles were among the inputs rather than calculated, which hampers the predictive capability of these models. To address these issues, a finite element musculoskeletal model with the ability to predict contractions of 3D muscles was developed. Muscles with realistic 3D geometry, spatial muscle fibre alignment and muscle-muscle and muscle-bone interactions were accounted for. Active contractile stresses of the 3D muscles were determined through an efficient optimization approach based on the measured kinematics of the lower extremity and ground force during gait. This model also provided stresses and strains of muscles and contact mechanics of the muscle-muscle and muscle-bone interactions. The total contact force of the knee predicted by the model corresponded well to the in vivo measurement. Contact and wrapping between muscles and surrounding tissues were evident, demonstrating the need to consider 3D contact models of muscles. This modelling framework serves as the methodological basis for developing musculoskeletal modelling systems in finite element method incorporating 3D deformable contact models of muscles, joints, ligaments and bones.     

MRI vs CT-based 2D-3D auto-registration accuracy for quantifying shoulder motion using biplane video-radiography

Biplane 2D-3D registration approaches have been used for measuring 3D, in vivo glenohumeral (GH) joint kinematics. Computed tomography (CT) has become the gold standard for reconstructing 3D bone models, as it provides high geometric accuracy and similar tissue contrast to video-radiography. Alternatively, magnetic resonance imaging (MRI) would not expose subjects to radiation and provides the ability to add cartilage and other soft tissues to the models. However, the accuracy of MRI-based 2D-3D registration for quantifying glenohumeral kinematics is unknown. We developed an automatic 2D-3D registration program that works with both CT- and MRI-based image volumes for quantifying joint motions. The purpose of this study was to use the proposed 2D-3D auto-registration algorithm to describe the humerus and scapula tracking accuracy of CT- and MRI-based registration relative to radiostereometric analysis (RSA) during dynamic biplanar video-radiography. The GH kinematic accuracy (RMS error) was 0.6–1.0 mm and 0.6–2.2° for the CT-based registration and 1.4–2.2 mm and 1.2–2.6° for MRI-based registration. Higher kinematic accuracy of CT-based registration was expected as MRI provides lower spatial resolution and bone contrast as compared to CT and suffers from spatial distortions. However, the MRI-based registration is within an acceptable accuracy for many clinical research questions.     

Capturing complex 3D tissue physiology in vitro

The emergence of tissue engineering raises new possibilities for the study of complex physiological and pathophysiological processes in vitro. Many tools are now available to create 3D tissue models in vitro, but the blueprints for what to make have been slower to arrive. We discuss here some of the 'design principles' for recreating the interwoven set of biochemical and mechanical cues in the cellular microenvironment, and the methods for implementing them. We emphasize applications that involve epithelial tissues for which 3D models could explain mechanisms of disease or aid in drug development.     

Postfailure modulus strongly affects microcracking and mechanical property change in human iliac cancellous bone: a study using a 2D nonlinear finite element method

A two-dimensional (2D) finite element (FE) method was used to estimate the ability of bone tissue to sustain damage as a function of postfailure modulus. Briefly, 2D nonlinear compact-tension FE models were created from quantitative back-scattered electron images taken of human iliac crest bone specimens. The effects of different postfailure moduli on predicted microcrack propagation were examined. The 2D FE models were used as surrogates for real bone tissues. The crack number was larger in models with higher postfailure modulus, while mean crack length and area were smaller in these models. The rate of stiffness reduction was greater in the models with lower postfailure modulus. Hence, the current results supported the hypothesis that hard tissue postfailure properties have strong effects on bone microdamage morphology and the rate of change in apparent mechanical properties.     

A multi-model approach to simultaneous segmentation and classification of heterogeneous populations of cell nuclei in 3D confocal microscope images.

Automated segmentation and morphometry of fluorescently labeled cell nuclei in batches of 3D confocal stacks is essential for quantitative studies. Model-based segmentation algorithms are attractive due to their robustness. Previous methods incorporated a single nuclear model. This is a limitation for tissues containing multiple cell types with different nuclear features. Improved segmentation for such tissues requires algorithms that permit multiple models to be used simultaneously. This requires a tight integration of classification and segmentation algorithms. Two or more nuclear models are constructed semiautomatically from user-provided training examples. Starting with an initial over-segmentation produced by a gradient-weighted watershed algorithm, a hierarchical fragment merging tree rooted at each object is built. Linear discriminant analysis is used to classify each candidate using multiple object models. On the basis of the selected class, a Bayesian score is computed. Fragment merging decisions are made by comparing the score with that of other candidates, and the scores of constituent fragments of each candidate. The overall segmentation accuracy was 93.7% and classification accuracy was 93.5%, respectively, on a diverse collection of images drawn from five different regions of the rat brain. The multi-model method was found to achieve high accuracy on nuclear segmentation and classification by correctly resolving ambiguities in clustered regions containing heterogeneous cell populations.     

Using 2D In Vivo IVUS-Based Models for Human Coronary Plaque Progression Analysis and Comparison with 3D Fluid-Structure Interaction Models: A Multi-Patient Study

Computational modeling has been used extensively in cardiovascular and biological research, providing valuable information. However, 3D vulnerable plaque model construction with complex geometrical features and multicomponents is often very time consuming and not practical for clinical implementation. This paper investigated if 2D atherosclerotic plaque models could be used to replace 3D models to perform correlation analysis and achieve similar results. In vivo intravascular ultrasound (IVUS) coronary plaque data were acquired from a patient follow-up study to construct 2D structure-only and 3D FSI models to obtain plaque wall stress (PWS) and strain (PWSn) data. One hundred and twenty-seven (127) matched IVUS slices at baseline and follow up were obtained from 3 patients. Our results showed that 2D models overestimated stress and strain by 30% and 33%, respectively, compared to results from 3D FSI models. 2D/3D correlation comparison indicated that 116 out of 127 slices had a consistent correlation between plaque progression (WTI) and wall thickness; 103 out of 127 slices had a consistent correlation between WTI and PWS; and 99 out of 127 slices had a consistent correlation between WTI and PWSn. This leads to the potential that 2D models could be used in actual clinical implementation where quick analysis delivery time is essential.     

Invasive three-dimensional organotypic neoplasia from multiple normal human epithelia

Refined cancer models are required if researchers are to assess the burgeoning number of potential targets for cancer therapeutics in a clinically relevant context that allows a fast turnaround. Here we use tumor-associated genetic pathways to transform primary human epithelial cells from the epidermis, oropharynx, esophagus and cervix into genetically defined tumors in a human three-dimensional (3D) tissue environment that incorporates cell-populated stroma and intact basement membrane. These engineered organotypic tissues recapitulated natural features of tumor progression, including epithelial invasion through basement membrane, a complex process that is necessary for biological malignancy in 90% of human cancers. Invasion was rapid and was potentiated by stromal cells. Oncogenic signals in 3D tissue, but not 2D culture, resembled gene expression profiles from spontaneous human cancers. We screened 3D organotypic neoplasia with well-characterized signaling pathway inhibitors to distill a clinically faithful cancer gene signature. Multitissue 3D human tissue cancer models may provide an efficient and relevant complement to current approaches to characterizing cancer progression.     

Multizone paper platform for 3D cell cultures

In vitro 3D culture is an important model for tissues in vivo. Cells in different locations of 3D tissues are physiologically different, because they are exposed to different concentrations of oxygen, nutrients, and signaling molecules, and to other environmental factors (temperature, mechanical stress, etc). The majority of high-throughput assays based on 3D cultures, however, can only detect the average behavior of cells in the whole 3D construct. Isolation of cells from specific regions of 3D cultures is possible, but relies on low-throughput techniques such as tissue sectioning and micromanipulation. Based on a procedure reported previously ("cells-in-gels-in-paper" or CiGiP), this paper describes a simple method for culture of arrays of thin planar sections of tissues, either alone or stacked to create more complex 3D tissue structures. This procedure starts with sheets of paper patterned with hydrophobic regions that form 96 hydrophilic zones. Serial spotting of cells suspended in extracellular matrix (ECM) gel onto the patterned paper creates an array of 200 micron-thick slabs of ECM gel (supported mechanically by cellulose fibers) containing cells. Stacking the sheets with zones aligned on top of one another assembles 96 3D multilayer constructs. De-stacking the layers of the 3D culture, by peeling apart the sheets of paper, "sections" all 96 cultures at once. It is, thus, simple to isolate 200-micron-thick cell-containing slabs from each 3D culture in the 96-zone array. Because the 3D cultures are assembled from multiple layers, the number of cells plated initially in each layer determines the spatial distribution of cells in the stacked 3D cultures. This capability made it possible to compare the growth of 3D tumor models of different spatial composition, and to examine the migration of cells in these structures.     

Cell3: a new vision for study of the endomembrane system in mammalian cells

The endomembrane system of mammalian cells provides massive capacity for the segregation of biochemical reactions into discrete locations. The individual organelles of the endomembrane system also require the ability to precisely transport material between these compartments in order to maintain cell homeostasis; this process is termed membrane traffic. For several decades, researchers have been systematically identifying and dissecting the molecular machinery that governs membrane trafficking pathways, with the overwhelming majority of these studies being carried out in cultured cells growing as monolayers. In recent years, a number of methodological innovations have provided the opportunity for cultured cells to be grown as 3-dimensional (3D) assemblies, for example as spheroids and organoids. These structures have the potential to better replicate the cellular environment found in tissues and present an exciting new opportunity for the study of cell function. In this mini-review, we summarize the main methods used to generate 3D cell models and highlight emerging studies that have started to use these models to study basic cellular processes. We also describe a number of pieces of work that potentially provide the basis for adaptation for deeper study of how membrane traffic is coordinated in multicellular assemblies. Finally, we comment on some of the technological challenges that still need to be overcome if 3D cell biology is to become a mainstream tool toward deepening our understanding of the endomembrane system in mammalian cells.     

The canine virtual ventricular wall: a platform for dissecting pharmacological effects on propagation and arrhythmogenesis

We have constructed computational models of canine ventricular cells and tissues, ultimately combining detailed tissue architecture and heterogeneous transmural electrophysiology. The heterogeneity is introduced by modifying the Hund–Rudy canine cell model in order to reproduce experimentally reported electrophysiological properties of endocardial, midmyocardial (M) and epicardial cells. These models are validated against experimental data for individual ionic current and action potential characteristics, and their rate dependencies. 1D and 3D heterogeneous virtual tissues are constructed, with detailed tissue architecture (anisotropy and orthotropy, due to fibre orientation and sheet structure) of the left ventricular wall wedge extracted from a diffusion tensor imaging data set. The models are used to study the effects of tissue heterogeneity and class III drugs on transmural propagation and tissue vulnerability to re-entry.

We have determined relationships between the transmural dispersion of action potential duration (APD) and the vulnerable window in the 1D virtual ventricular wall, and demonstrated how changes in the transmural heterogeneity, and hence tissue vulnerability, can lead to generation of re-entry in the 3D ventricular wedge. Two class III drugs with opposite qualitative effects on transmural APD heterogeneity are considered: d-sotalol that increases transmural APD dispersion, and amiodarone that decreases it. Simulations with the 1D virtual ventricular wall show that under d-sotalol conditions the vulnerable window is substantially wider compared to amiodarone conditions, primarily in the epicardial region where unidirectional conduction block persists until the adjacent M cells are fully repolarised.

Further simulations with the 3D ventricular wedge have shown that ectopic stimulation of the epicardial region results in generation of sustained re-entry under d-sotalol conditions, but not under amiodarone conditions or in control. Again, APD increase in M cells was identified as the major contributor to tissue vulnerability—re-entry was initiated primarily due to ectopic excitation propagating around the unidirectional conduction block in the M cell region. This suggests an electrophysiological mechanism for the anti- and proarrhythmic effects of the class III drugs: the relative safety of amiodarone in comparison to d-sotalol can be explained by relatively low transmural APD dispersion, and hence, a narrow vulnerable window and low probability of re-entry in the tissue.