An algorithm-based topographical biomaterials library to instruct cell fate

Abstract

It is increasingly recognized that material surface topography is able to evoke specific cellular responses, endowing materials with instructive properties that were formerly reserved for growth factors. This opens the window to improve upon, in a cost-effective manner, biological performance of any surface used in the human body. Unfortunately, the interplay between surface topographies and cell behavior is complex and still incompletely understood. Rational approaches to search for bioactive surfaces will therefore omit previously unperceived interactions. Hence, in the present study, we use mathematical algorithms to design nonbiased, random surface features and produce chips of poly(lactic acid) with 2,176 different topographies. With human mesenchymal stromal cells (hMSCs) grown on the chips and using high-content imaging, we reveal unique, formerly unknown, surface topographies that are able to induce MSC proliferation or osteogenic differentiation. Moreover, we correlate parameters of the mathematical algorithms to cellular responses, which yield novel design criteria for these particular parameters. In conclusion, we demonstrate that randomized libraries of surface topographies can be broadly applied to unravel the interplay between cells and surface topography and to find improved material surfaces.

Substrate topography: A valuable in vitro tool, but a clinical red herring for in vivo tenogenesis

“…electrospun polymeric fibres, extruded collagen fibres and isoelectrically focused collagen fibres) have been shown to maintain tenocyte phenotype and to differentiate stem cells towards tenogenic lineage in vitro and to induce acceptable regeneration in preclinical models, none of these technologies offers precise control over the spatial distribution of the fibres. Imprinting technologies, on the other hand, have demonstrated a diverse effect on a range of permanently differentiated and stem cell functions, including adhesion, orientation, secretome expression and lineage commitment [41][42][43][44][45][46][47][48] and offer significantly greater control over feature dimension and spacing. Specifically to tendon repair, such technologies have been shown to maintain tenocyte phenotype [38]; to promote aligned tendon-specific ECM deposition [39]; and to differentiate stem cells towards tenogenic lineage [40].…”

Dynamic and Responsive Growth Factor Delivery from Electrospun and Hydrogel Tissue Engineering Materials

“…[4] Much research has been done investigating and optimizing one material property at a time to mimic the ECM. For example, extensive work has been done tuning material stiffness [5] and the nano/microscale morphology, [6] and these properties have both been shown to significantly affect cell differentiation and proliferation. [7] While tuning an individual biochemical or physical cue can enable study of its effect in isolation and enhance material performance, [8] multiple biomimetic cues often have a synergistic effect, such that the overall benefit is greater than the combined individual benefits.…”

A modular versatile chip carrier for high-throughput screening of cell–biomaterial interactions

“…In addition, the field of biomaterials is changing from the use of bioinert materials to that of more bioactive materials. To realize the emergence of bioactive materials, different functionalization techniques such as topographic patterning, peptide patterning, plasma etching and combinatorial chemistry are being developed [1,2]. Each of these emerging techniques generates enormous possibilities in terms of physico-chemical variations.…”

“…For example, Anderson and co-workers [7] have investigated the effect of embryonic stem cell behaviour on polymer libraries. We recently developed a high-throughput platform for systematically studying the effect of thousands of surface topographies on cell behaviour [2]. For studying a multitude of biomaterial properties, biological assays need to be miniaturized to accommodate a higher number of materials, which is similar to the drug discovery approaches used in the pharmaceutical industry [8].…”

“…In the latter case, the cell lysate has to be distributed uniformly on the arrays to avoid inconsistent data. Recently, we developed a chip for high-throughput screening of surface topographies [2], i.e. TopoChip, with 4356 areas each with a given surface structure referred to as TopoUnits across a grid of 66 rows and 66 columns.…”