Designed Surface Topographies Control ICAM-1 Expression in Tonsil-Derived Human Stromal Cells

High-Throughput Methods in the Discovery and Study of Biomaterials and Materiobiology

The complex interaction of cells with biomaterials (i.e., materiobiology) plays an increasingly pivotal role in the development of novel implants, biomedical devices, and tissue engineering scaffolds to treat diseases, aid in the restoration of bodily functions, construct healthy tissues, or regenerate diseased ones. However, the conventional approaches are incapable of screening the huge amount of potential material parameter combinations to identify the optimal cell responses and involve a combination of serendipity and many series of trial-and-error experiments. For advanced tissue engineering and regenerative medicine, highly efficient and complex bioanalysis platforms are expected to explore the complex interaction of cells with biomaterials using combinatorial approaches that offer desired complex microenvironments during healing, development, and homeostasis. In this review, we first introduce materiobiology and its high-throughput screening (HTS). Then we present an in-depth of the recent progress of 2D/3D HTS platforms (i.e., gradient and microarray) in the principle, preparation, screening for materiobiology, and combination with other advanced technologies. The Compendium for Biomaterial Transcriptomics and high content imaging, computational simulations, and their translation toward commercial and clinical uses are highlighted. In the final section, current challenges and future perspectives are discussed. High-throughput experimentation within the field of materiobiology enables the elucidation of the relationships between biomaterial properties and biological behavior and thereby serves as a potential tool for accelerating the development of high-performance biomaterials.

Discovery of synergistic material-topography combinations to achieve immunomodulatory osteoinductive biomaterials using a novel in vitro screening method: The ChemoTopoChip

Human mesenchymal stem cells (hMSCs) are widely represented in regenerative medicine clinical strategies due to their compatibility with autologous implantation. Effective bone regeneration involves crosstalk between macrophages and hMSCs, with macrophages playing a key role in the recruitment and differentiation of hMSCs. However, engineered biomaterials able to simultaneously direct hMSC fate and modulate macrophage phenotype have not yet been identified. A novel combinatorial chemistry-topography screening platform, the ChemoTopoChip, is used here to identify materials suitable for bone regeneration by screening 1008 combinations in each experiment for human immortalized mesenchymal stem cell (hiMSCs) and human macrophage response. The osteoinduction achieved in hiMSCs cultured on the "hit" materials in basal media is comparable to that seen when cells are cultured in osteogenic media, illustrating that these materials offer a materials-induced alternative to osteo-inductive supplements in bone-regeneration. Some of these same chemistry-microtopography combinations also exhibit immunomodulatory stimuli, polarizing macrophages towards a pro-healing phenotype. Maximum control of cell response is achieved when both chemistry and topography are recruited to instruct the required cell phenotype, combining synergistically. The large combinatorial library allows us for the first time to probe the relative cell-instructive roles of microtopography and material chemistry which we find to provide similar ranges of cell modulation for both cues. Machine learning is used to generate structure-activity relationships that identify key chemical and topographical features enhancing the response of both cell types, providing a basis for a better understanding of cell response to micro topographically patterned polymers.

Immune Modulation by Design: Using Topography to Control Human Monocyte Attachment and Macrophage Differentiation

Macrophages play a central role in orchestrating immune responses to foreign materials, which are often responsible for the failure of implanted medical devices. Material topography is known to influence macrophage attachment and phenotype, providing opportunities for the rational design of "immune-instructive" topographies to modulate macrophage function and thus foreign body responses to biomaterials. However, no generalizable understanding of the inter-relationship between topography and cell response exists. A high throughput screening approach is therefore utilized to investigate the relationship between topography and human monocyte-derived macrophage attachment and phenotype, using a diverse library of 2176 micropatterns generated by an algorithm. This reveals that micropillars 5-10 µm in diameter play a dominant role in driving macrophage attachment compared to the many other topographies screened, an observation that aligns with studies of the interaction of macrophages with particles. Combining the pillar size with the micropillar density is found to be key in modulation of cell phenotype from pro to anti-inflammatory states. Machine learning is used to successfully build a model that correlates cell attachment and phenotype with a selection of descriptors, illustrating that materials can potentially be designed to modulate inflammatory responses for future applications in the fight against foreign body rejection of medical devices.

Multifunctional Biomaterials: Combining Material Modification Strategies for Engineering of Cell-Contacting Surfaces

In the human body, cells in a tissue are exposed to signals derived from their specific extracellular matrix (ECM), such as architectural structure, mechanical properties, and chemical composition (proteins, growth factors). Research on biomaterials in tissue engineering and regenerative medicine aims to recreate such stimuli using engineered materials to induce a specific response of cells at the interface. Although traditional biomaterials design has been mostly limited to varying individual signals, increasing interest has arisen on combining several features in recent years to improve the mimicry of extracellular matrix properties. Tremendous progress in combinatorial surface modification exploiting, for example, topographical features or variations in mechanics combined with biochemical cues has enabled the identification of their key regulatory characteristics on various cell fate decisions. Gradients especially facilitated such research by enabling the investigation of combined continuous changes of different signals. Despite unravelling important synergies for cellular responses, challenges arise in terms of fabrication and characterization of multifunctional engineered materials. This review summarizes recent work on combinatorial surface modifications that aim to control biological responses. Modification and characterization methods for enhanced control over multifunctional material properties are highlighted and discussed. Thereby, this review deepens the understanding and knowledge of biomimetic combinatorial material modification, their challenges but especially their potential.

Screening as a strategy to drive regenerative medicine research

In the field of regenerative medicine, optimization of the parameters leading to a desirable outcome remains a huge challenge. Examples include protocols for the guided differentiation of pluripotent cells towards specialized and functional cell types, phenotypic maintenance of primary cells in cell culture, or engineering of materials for improved tissue interaction with medical implants. This challenge originates from the enormous design space for biomaterials, chemical and biochemical compounds, and incomplete knowledge of the guiding biological principles. To tackle this challenge, high-throughput platforms allow screening of multiple perturbations in one experimental setup. In this review, we provide an overview of screening platforms that are used in regenerative medicine. We discuss their fabrication techniques, and in silico tools to analyze the extensive data sets typically generated by these platforms.

Predicting gene expression using morphological cell responses to nanotopography

Cells respond in complex ways to their environment, making it challenging to predict a direct relationship between the two. A key problem is the lack of informative representations of parameters that translate directly into biological function. Here we present a platform to relate the effects of cell morphology to gene expression induced by nanotopography. This platform utilizes the ‘morphome’, a multivariate dataset of cell morphology parameters. We create a Bayesian linear regression model that uses the morphome to robustly predict changes in bone, cartilage, muscle and fibrous gene expression induced by nanotopography. Furthermore, through this model we effectively predict nanotopography-induced gene expression from a complex co-culture microenvironment. The information from the morphome uncovers previously unknown effects of nanotopography on altering cell–cell interaction and osteogenic gene expression at the single cell level. The predictive relationship between morphology and gene expression arising from cell-material interaction shows promise for exploration of new topographies.

The surface nanotopography of biomaterials direct cell behavior, but screening for desired effects is inefficient. Here, the authors introduce a platform that enables prediction of nanotopography-induced gene expression changes from changes in cell morphology, including in co-culture environments.

From Shape to Function: The Next Step in Bioprinting

In 2013, the "biofabrication window" was introduced to reflect the processing challenge for the fields of biofabrication and bioprinting. At that time, the lack of printable materials that could serve as cell-laden bioinks, as well as the limitations of printing and assembly methods, presented a major constraint. However, recent developments have now resulted in the availability of a plethora of bioinks, new printing approaches, and the technological advancement of established techniques. Nevertheless, it remains largely unknown which materials and technical parameters are essential for the fabrication of intrinsically hierarchical cell-material constructs that truly mimic biologically functional tissue. In order to achieve this, it is urged that the field now shift its focus from materials and technologies toward the biological development of the resulting constructs. Therefore, herein, the recent material and technological advances since the introduction of the biofabrication window are briefly summarized, i.e., approaches how to generate shape, to then focus the discussion on how to acquire the biological function within this context. In particular, a vision of how biological function can evolve from the possibility to determine shape is outlined.