Biomimetic strategies for replicating the neural stem cell niche

Modelling the central nervous system: tissue engineering of the cellular microenvironment

With the increasing prevalence of neurodegenerative diseases, improved models of the central nervous system (CNS) will improve our understanding of neurophysiology and pathogenesis, whilst enabling exploration of novel therapeutics. Studies of brain physiology have largely been carried out using in vivo models, ex vivo brain slices or primary cell culture from rodents. Whilst these models have provided great insight into complex interactions between brain cell types, key differences remain between human and rodent brains, such as degree of cortical complexity. Unfortunately, comparative models of human brain tissue are lacking. The development of induced Pluripotent Stem Cells (iPSCs) has accelerated advancement within the field of in vitro tissue modelling. However, despite generating accurate cellular representations of cortical development and disease, two-dimensional (2D) iPSC-derived cultures lack an entire dimension of environmental information on structure, migration, polarity, neuronal circuitry and spatiotemporal organisation of cells. As such, researchers look to tissue engineering in order to develop advanced biomaterials and culture systems capable of providing necessary cues for guiding cell fates, to construct in vitro model systems with increased biological relevance. This review highlights experimental methods for engineering of in vitro culture systems to recapitulate the complexity of the CNS with consideration given to previously unexploited biophysical cues within the cellular microenvironment.

Engineering Approaches to Study Cellular Decision Making

In their native environment, cells are immersed in a complex milieu of biochemical and biophysical cues. These cues may include growth factors, the extracellular matrix, cell-cell contacts, stiffness, and topography, and they are responsible for regulating cellular behaviors such as adhesion, proliferation, migration, apoptosis, and differentiation. The decision-making process used to convert these extracellular inputs into actions is highly complex and sensitive to changes both in the type of individual cue (e.g., growth factor dose/level, timing) and in how these individual cues are combined (e.g., homotypic/heterotypic combinations). In this review, we highlight recent advances in the development of engineering-based approaches to study the cellular decision-making process. Specifically, we discuss the use of biomaterial platforms that enable controlled and tailored delivery of individual and combined cues, as well as the application of computational modeling to analyses of the complex cellular decision-making networks.