A heuristic computational model of basic cellular processes and oxygenation during spheroid-dependent biofabrication

Computational methods for biofabrication in tissue engineering and regenerative medicine - a literature review

This literature review rigorously examines the growing scientific interest in computational methods for Tissue Engineering and Regenerative Medicine biofabrication, a leading-edge area in biomedical innovation, emphasizing the need for accurate, multi-stage, and multi-component biofabrication process models. The paper presents a comprehensive bibliometric and contextual analysis, followed by a literature review, to shed light on the vast potential of computational methods in this domain. It reveals that most existing methods focus on single biofabrication process stages and components, and there is a significant gap in approaches that utilize accurate models encompassing both biological and technological aspects. This analysis underscores the indispensable role of these methods in understanding and effectively manipulating complex biological systems and the necessity for developing computational methods that span multiple stages and components. The review concludes that such comprehensive computational methods are essential for developing innovative and efficient Tissue Engineering and Regenerative Medicine biofabrication solutions, driving forward advancements in this dynamic and evolving field.

Agent-based model demonstrates the impact of nonlinear, complex interactions between cytokinces on muscle regeneration

Muscle regeneration is a complex process due to dynamic and multiscale biochemical and cellular interactions, making it difficult to identify microenvironmental conditions that are beneficial to muscle recovery from injury using experimental approaches alone. To understand the degree to which individual cellular behaviors impact endogenous mechanisms of muscle recovery, we developed an agent-based model (ABM) using the Cellular-Potts framework to simulate the dynamic microenvironment of a cross-section of murine skeletal muscle tissue. We referenced more than 100 published studies to define over 100 parameters and rules that dictate the behavior of muscle fibers, satellite stem cells (SSCs), fibroblasts, neutrophils, macrophages, microvessels, and lymphatic vessels, as well as their interactions with each other and the microenvironment. We utilized parameter density estimation to calibrate the model to temporal biological datasets describing cross-sectional area (CSA) recovery, SSC, and fibroblast cell counts at multiple timepoints following injury. The calibrated model was validated by comparison of other model outputs (macrophage, neutrophil, and capillaries counts) to experimental observations. Predictions for eight model perturbations that varied cell or cytokine input conditions were compared to published experimental studies to validate model predictive capabilities. We used Latin hypercube sampling and partial rank correlation coefficient to identify in silico perturbations of cytokine diffusion coefficients and decay rates to enhance CSA recovery. This analysis suggests that combined alterations of specific cytokine decay and diffusion parameters result in greater fibroblast and SSC proliferation compared to individual perturbations with a 13% increase in CSA recovery compared to unaltered regeneration at 28 days. These results enable guided development of therapeutic strategies that similarly alter muscle physiology (i.e. converting extracellular matrix [ECM]-bound cytokines into freely diffusible forms as studied in cancer therapeutics or delivery of exogenous cytokines) during regeneration to enhance muscle recovery after injury.

The influence of spheroid maturity on fusion dynamics and micro-tissue assembly in 3D tumor models

Three-dimensional (3D) cell culture has been used in many fields of biology because of its unique advantages. As a representative of the 3D systems, 3D spheroids are used as building blocks for tissue construction. Larger tumor aggregates can be assembled by manipulating or stacking the tumor spheroids. The motivation of this study is to investigate the behavior of the cells distributed at different locations of the spheroids in the fusion process and the mechanism behind it. To this aim, spheroids with varying grades of maturity or age were generated for fusion to assemble micro-tumor tissues. The dynamics of the fusion process, the motility of the cells distributed in different heterogeneous architecture sites, and their reactive oxygen species profiles were studied. We found that the larger the spheroid necrotic core, the slower the fusion rate of the spheroid. The cells that move were mainly distributed on the spheroid's surface during fusion. In addition to dense microfilament distribution and low microtubule content, the reactive oxygen content was high in the fusion site, while the non-fusion site was the opposite. Last, multi-spheroids with different maturities were fused to complex micro-tissues to mimic solid tumors and evaluate Doxorubicin's anti-tumor efficacy.

Mathematical and computational models in spheroid-based biofabrication

Ubiquitous in embryonic development, tissue fusion is of interest to tissue engineers who use tissue spheroids or organoids as building blocks of three-dimensional (3D) multicellular constructs. This review presents mathematical models and computer simulations of the fusion of tissue spheroids. The motivation of this study stems from the need to predict the post-printing evolution of 3D bioprinted constructs. First, we provide a brief overview of differential adhesion, the main morphogenetic mechanism involved in post-printing structure formation. It will be shown that clusters of cohesive cells behave as an incompressible viscous fluid on the time scale of hours. The discussion turns then to mathematical models based on the continuum hydrodynamics of highly viscous liquids and on statistical mechanics. Next, we analyze the validity and practical use of computational models of multicellular self-assembly in live constructs created by tissue spheroid bioprinting. Finally, we discuss the perspectives of the field as machine learning starts to reshape experimental design, and modular robotic workstations tend to alleviate the burden of repetitive tasks in biofabrication. STATEMENT OF SIGNIFICANCE: Bioprinted constructs are living systems, which evolve via morphogenetic mechanisms known from developmental biology. This review presents mathematical and computational tools devised for modeling post-printing structure formation. They help achieving a desirable outcome without expensive optimization experiments. While previous reviews mainly focused on assumptions, technical details, strengths, and limitations of computational models of multicellular self-assembly, this article discusses their validity and practical use in biofabrication. It also presents an overview of mathematical models that proved to be useful in the evaluation of experimental data on tissue spheroid fusion, and in the calibration of computational models. Finally, the perspectives of the field are discussed in the advent of robotic biofabrication platforms and bioprinting process optimization by machine learning.

3D Printing: Advancement in Biogenerative Engineering to Combat Shortage of Organs and Bioapplicable Materials

Abstract

Organ or cell transplantation is medically evaluated for end-stage failure saving or extending the lives of thousands of patients who are suffering from organ failure disorders. The unavailability of adequate organs for transplantation to meet the existing demand is a major challenge in the medical field. This led to day-day-increase in the number of patients on transplant waiting lists as well as in the number of patients dying while on the queue. Recently, technological advancements in the field of biogenerative engineering have the potential to regenerate tissues and, in some cases, create new tissues and organs. In this context, major advances and innovations are being made in the fields of tissue engineering and regenerative medicine which have a huge impact on the scientific community is three-dimensional bioprinting (3D bioprinting) of tissues and organs. Besides this, the decellularization of organs and using this as a scaffold for generating new organs through the recellularization process shows promising results. This review discussed about current approaches for tissue and organ engineering including methods of scaffold designing, recent advances in 3D bioprinting, organs regenerated successfully using 3D printing, and extended application of 3D bioprinting technique in the field of medicine. Besides this, information about commercially available 3D printers has also been included in this article.

Lay Summary

Today's need for organs for the transplantation process in order to save a patient's life or to enhance the survival rate of diseased one is the prime concern among the scientific community. Recent, advances in the field of biogenerative engineering have the potential to regenerate tissues and create organs compatible with the patient's body. In this context, major advances and innovations are being made in the fields of tissue engineering and regenerative medicine which have a huge impact on the scientific community is three-dimensional bioprinting (3D bioprinting) of tissues and organs. Besides this, the decellularization of organs and using this as a scaffold for generating new organs through the recellularization process shows promising results. This review dealt with the current approaches for tissue and organ engineering including methods of scaffold designing, recent advances in 3D bioprinting, organs regenerated successfully using 3D printing, and extended application of 3D bioprinting technique in the field of medicine. Furthermore, information about commercially available 3D printers has also been included in this article.

Generation of multicellular spatiotemporal models of population dynamics from ordinary differential equations, with applications in viral infection

BACKGROUND

The biophysics of an organism span multiple scales from subcellular to organismal and include processes characterized by spatial properties, such as the diffusion of molecules, cell migration, and flow of intravenous fluids. Mathematical biology seeks to explain biophysical processes in mathematical terms at, and across, all relevant spatial and temporal scales, through the generation of representative models. While non-spatial, ordinary differential equation (ODE) models are often used and readily calibrated to experimental data, they do not explicitly represent the spatial and stochastic features of a biological system, limiting their insights and applications. However, spatial models describing biological systems with spatial information are mathematically complex and computationally expensive, which limits the ability to calibrate and deploy them and highlights the need for simpler methods able to model the spatial features of biological systems.

RESULTS

In this work, we develop a formal method for deriving cell-based, spatial, multicellular models from ODE models of population dynamics in biological systems, and vice versa. We provide examples of generating spatiotemporal, multicellular models from ODE models of viral infection and immune response. In these models, the determinants of agreement of spatial and non-spatial models are the degree of spatial heterogeneity in viral production and rates of extracellular viral diffusion and decay. We show how ODE model parameters can implicitly represent spatial parameters, and cell-based spatial models can generate uncertain predictions through sensitivity to stochastic cellular events, which is not a feature of ODE models. Using our method, we can test ODE models in a multicellular, spatial context and translate information to and from non-spatial and spatial models, which help to employ spatiotemporal multicellular models using calibrated ODE model parameters. We additionally investigate objects and processes implicitly represented by ODE model terms and parameters and improve the reproducibility of spatial, stochastic models.

CONCLUSION

We developed and demonstrate a method for generating spatiotemporal, multicellular models from non-spatial population dynamics models of multicellular systems. We envision employing our method to generate new ODE model terms from spatiotemporal and multicellular models, recast popular ODE models on a cellular basis, and generate better models for critical applications where spatial and stochastic features affect outcomes.

Engineering Functional Rat Ovarian Spheroids Using Granulosa and Theca Cells

Although menopausal hormone therapy (MHT) is the most effective approach to managing the loss of ovarian activity, serious side effects have been reported. Cell-based therapy is a promising alternative for MHT. This study constructed engineered ovarian cell spheroids and investigated their endocrine function. Theca and granulosa cells were isolated from ovaries of 10-week-old rats. Two types of engineered ovarian cell spheroids were fabricated through forced aggregation in microwells, multilayered spheroids with centralized granulosa aggregates surrounded by an outer layer of theca cells and mixed ovarian spheroids lacking spatial rearrangement. The ovarian cell spheroids were encapsulated into a collagen gel. Non-aggregated ovarian cells served as controls. The endocrine function of the engineered ovarian spheroids was assessed over 30 days. The structure of the spheroids was well maintained during culture. The secretion of 17β-estradiol from both types of engineered ovarian cell spheroids was higher than in the control group and increased continuously in a time-dependent manner. Secretion of 17β-estradiol in the multi-layered ovarian cell spheroids was higher than in the non-layered constructs. Increased secretion of progesterone was detected in the multi-layered ovarian cell spheroids at day 5 of culture and was sustained during the culture period. The initial secretion level of progesterone in the non-layered ovarian cell spheroids was similar to those from the controls and increased significantly from days 21 to 30. An in vitro rat model of engineered ovarian cell spheroids was developed that was capable of secreting sex steroid hormones, indicating that the hormone secreting function of ovaries can be recapitulated ex vivo and potentially adapted for MHT.

Biofabrication of spheroids fusion-based tumor models: computational simulation of glucose effects

In vitro tumor models consisting of cell spheroids are increasingly used for mechanistic studies and pharmacological testing. However, unless vascularized, the availability of nutrients such as glucose to deeper layers of multicellular aggregates is limited. In addition, recent developments in cells-only biofabrication (e.g. 'scaffold-free bioprinting'), allow the creation of more complex spheroid-based structures, further exposing the cells to nutrient deprivation within these constructs. To explore the impact of glucose availability on such tumor-like structures, we used the CompuCell3D (CC3D) platform for modeling of tumor spheroids. By monitoring the types of cells, fusing pairs geometry and the distance between spheroids centers of mass, we made novel heuristic observations on how binary- and multi-spheroid fusions are impacted by glucose availability. At limiting glucose concentrations mimicking hypoglycemia we noted an abrupt collapse of the tumor spheroids, unexpectedly amplified by the contact with normal cell spheroids. At higher glucose concentrations, we found an increased intermixing of cancerous cells, strong anti-phase oscillations between proliferating and quiescent tumor cells and a structural instability of fusing tumor spheroids, leading to their re-fragmentation. In a model of tumor microenvironment composed of normal cell spheroids fusing around a tumoral one, the competition for glucose lead to either the tumor's disappearance, or to its steady expansion. Moreover, the invasion of this microenvironment by individual tumor cells was also strongly depended on the available glucose. In conclusion, we demonstrate the value of computational simulations for anticipating the properties of biofabricated tumor models, and in generating testable hypotheses regarding the relationship between cancer, nutrition and diabetes.

Unification of aggregate growth models by emergence from cellular and intracellular mechanisms

Multicellular aggregate growth is regulated by nutrient availability and removal of metabolites, but the specifics of growth dynamics are dependent on cell type and environment. Classical models of growth are based on differential equations. While in some cases these classical models match experimental observations, they can only predict growth of a limited number of cell types and so can only be selectively applied. Currently, no classical model provides a general mathematical representation of growth for any cell type and environment. This discrepancy limits their range of applications, which a general modelling framework can enhance. In this work, a hybrid cellular Potts model is used to explain the discrepancy between classical models as emergent behaviours from the same mathematical system. Intracellular processes are described using probability distributions of local chemical conditions for proliferation and death and simulated. By fitting simulation results to a generalization of the classical models, their emergence is demonstrated. Parameter variations elucidate how aggregate growth may behave like one classical growth model or another. Three classical growth model fits were tested, and emergence of the Gompertz equation was demonstrated. Effects of shape changes are demonstrated, which are significant for final aggregate size and growth rate, and occur stochastically.

The potential role of 3D-bioprinting in xenotransplantation

PURPOSE OF REVIEW

To review the impact of a new technology, 3D-bioprinting, in xenotransplantation research.

RECENT FINDINGS

Genetically engineered pigs, beginning with human (h) CD55-transgenic and Gal-knockout pigs, have improved the outcomes of xenotransplantation research. Today, there are more than 30 different genetically engineered pigs either expressing human gene(s) or lacking pig gene(s). CRIPSR/cas9 technology has facilitated the production of multigene pigs (up to nine genes in a single pig), which lack multiple pig xenoantigens, and express human transgenes, such as hCD46, hCD55, hThrombomodulin, hCD39, etc. Although recent studies in nonhuman primates (NHPs) have demonstrated prolonged survival after life-supporting pig kidney, heart, and islet xenotransplantation, researchers have difficulty determining the best genetic combination to test in NHPs because of a potential greater than 100 000 genetic combinations. 3D-bioprinting of genetically engineered pig cells: is superior to 2D in-vitro testing, enables organ-specific testing, helps to understand differences in immunogenicity between organs, and is faster and cheaper than testing in NHPs. Moreover, 3D-bioprinted cells can be continuously perfused in a bioreactor, controlling for all variables, except the studied variable.

SUMMARY

3D-bioprinting can help in the study of the impact of specific genes (human or pig) in xenotransplantation in a rapid, inexpensive, and reliable way.

Biofabrication strategies for 3D in vitro models and regenerative medicine

Organs are complex systems composed of different cells, proteins and signalling molecules that are arranged in a highly ordered structure to orchestrate a myriad of functions in our body. Biofabrication strategies can be applied to engineer 3D tissue models in vitro by mimicking the structure and function of native tissue through the precise deposition and assembly of materials and cells. This approach allows the spatiotemporal control over cell-cell and cell-extracellular matrix communication and thus the recreation of tissue-like structures. In this Review, we examine biofabrication strategies for the construction of functional tissue replacements and organ models, focusing on the development of biomaterials, such as supramolecular and photosensitive materials, that can be processed using biofabrication techniques. We highlight bioprinted and bioassembled tissue models and survey biofabrication techniques for their potential to recreate complex tissue properties, such as shape, vasculature and specific functionalities. Finally, we discuss challenges, such as scalability and the foreign body response, and opportunities in the field and provide an outlook to the future of biofabrication in regenerative medicine.

Progress in scaffold-free bioprinting for cardiovascular medicine

Biofabrication of tissue analogues is aspiring to become a disruptive technology capable to solve standing biomedical problems, from generation of improved tissue models for drug testing to alleviation of the shortage of organs for transplantation. Arguably, the most powerful tool of this revolution is bioprinting, understood as the assembling of cells with biomaterials in three‐dimensional structures. It is less appreciated, however, that bioprinting is not a uniform methodology, but comprises a variety of approaches. These can be broadly classified in two categories, based on the use or not of supporting biomaterials (known as “scaffolds,” usually printable hydrogels also called “bioinks”). Importantly, several limitations of scaffold‐dependent bioprinting can be avoided by the “scaffold‐free” methods. In this overview, we comparatively present these approaches and highlight the rapidly evolving scaffold‐free bioprinting, as applied to cardiovascular tissue engineering.