Compartmentalized microfluidic chambers enable long-term maintenance and communication between human pluripotent stem cell-derived forebrain and midbrain neurons

Engineering an in vitro retinothalamic nerve model

Understanding the retinogeniculate pathway in vitro can offer insights into its development and potential for future therapeutic applications. This study presents a Polydimethylsiloxane-based two-chamber system with axon guidance channels, designed to replicate unidirectional retinogeniculate signal transmission in vitro. Using embryonic rat retinas, we developed a model where retinal spheroids innervate thalamic targets through up to 6 mm long microfluidic channels. Using a combination of electrical stimulation and functional calcium imaging we assessed how channel length and electrical stimulation frequency affects thalamic target response. In the presented model we integrated up to 20 identical functional retinothalamic neural networks aligned on a single transparent microelectrode array, enhancing the robustness and quality of recorded functional data. We found that network integrity depends on channel length, with 0.5-2 mm channels maintaining over 90% morphological and 50% functional integrity. A reduced network integrity was recorded in longer channels. The results indicate a notable reduction in forward spike propagation in channels longer than 4 mm. Additionally, spike conduction fidelity decreased with increasing channel length. Yet, stimulation-induced thalamic target activity remained unaffected by channel length. Finally, the study found that a sustained thalamic calcium response could be elicited with stimulation frequencies up to 31 Hz, with higher frequencies leading to transient responses. In conclusion, this study presents a high-throughput platform that demonstrates how channel length affects retina to brain network formation and signal transmission in vitro.

Microfluidic Brain-on-a-Chip: From Key Technology to System Integration and Application

As an ideal in vitro model, brain-on-chip (BoC) is an important tool to comprehensively elucidate brain characteristics. However, the in vitro model for the definition scope of BoC has not been universally recognized. In this review, BoC is divided into brain cells-on-a- chip, brain slices-on-a-chip, and brain organoids-on-a-chip according to the type of culture on the chip. Although these three microfluidic BoCs are constructed in different ways, they all use microfluidic chips as carrier tools. This method can better meet the needs of maintaining high culture activity on a chip for a long time. Moreover, BoC has successfully integrated cell biology, the biological material platform technology of microenvironment on a chip, manufacturing technology, online detection technology on a chip, and so on, enabling the chip to present structural diversity and high compatibility to meet different experimental needs and expand the scope of applications. Here, the relevant core technologies, challenges, and future development trends of BoC are summarized.

Probabilistic cell seeding and non-autofluorescent 3D-printed structures as scalable approach for multi-level co-culture modeling

To model complex biological tissue in vitro, a specific layout for the position and numbers of each cell type is necessary. Establishing such a layout requires manual cell placement in three dimensions (3D) with micrometric precision, which is complicated and time-consuming. Moreover, 3D printed materials used in compartmentalized microfluidic models are opaque or autofluorescent, hindering parallel optical readout and forcing serial characterization methods, such as patch-clamp probing. To address these limitations, we introduce a multi-level co-culture model realized using a parallel cell seeding strategy of human neurons and astrocytes on 3D structures printed with a commercially available non-autofluorescent resin at micrometer resolution. Using a two-step strategy based on probabilistic cell seeding, we demonstrate a human neuronal monoculture that forms networks on the 3D printed structure and can establish cell-projection contacts with an astrocytic-neuronal co-culture seeded on the glass substrate. The transparent and non-autofluorescent printed platform allows fluorescence-based immunocytochemistry and calcium imaging. This approach provides facile multi-level compartmentalization of different cell types and routes for pre-designed cell projection contacts, instrumental in studying complex tissue, such as the human brain.

Portrait of intense communications within microfluidic neural networks

In vitro model networks could provide cellular models of physiological relevance to reproduce and investigate the basic function of neural circuits on a chip in the laboratory. Several tools and methods have been developed since the past decade to build neural networks on a chip; among them, microfluidic circuits appear to be a highly promising approach. One of the numerous advantages of this approach is that it preserves stable somatic and axonal compartments over time due to physical barriers that prevent the soma from exploring undesired areas and guide neurites along defined pathways. As a result, neuron compartments can be identified and isolated, and their interconnectivity can be modulated to build a topological neural network (NN). Here, we have assessed the extent to which the confinement imposed by the microfluidic environment can impact cell development and shape NN activity. Toward that aim, microelectrode arrays have enabled the monitoring of the short- and mid-term evolution of neuron activation over the culture period at specific locations in organized (microfluidic) and random (control) networks. In particular, we have assessed the spike and burst rate, as well as the correlations between the extracted spike trains over the first stages of maturation. This study enabled us to observe intense neurite communications that would have been weaker and more delayed within random networks; the spiking rate, burst and correlations being reinforced over time in terms of number and amplitude, exceeding the electrophysiological features of standard cultures. Beyond the enhanced detection efficiency that was expected from the microfluidic channels, the confinement of cells seems to reinforce neural communications and cell development throughout the network.

Building blocks of microphysiological system to model physiology and pathophysiology of human heart

Microphysiological systems (MPS) are drawing increasing interest from academia and from biomedical industry due to their improved capability to capture human physiology. MPS offer an advanced in vitro platform that can be used to study human organ and tissue level functions in health and in diseased states more accurately than traditional single cell cultures or even animal models. Key features in MPS include microenvironmental control and monitoring as well as high biological complexity of the target tissue. To reach these qualities, cross-disciplinary collaboration from multiple fields of science is required to build MPS. Here, we review different areas of expertise and describe essential building blocks of heart MPS including relevant cardiac cell types, supporting matrix, mechanical stimulation, functional measurements, and computational modelling. The review presents current methods in cardiac MPS and provides insights for future MPS development with improved recapitulation of human physiology.

Biosensor integrated brain-on-a-chip platforms: Progress and prospects in clinical translation

Because of the brain's complexity, developing effective treatments for neurological disorders is a formidable challenge. Research efforts to this end are advancing as in vitro systems have reached the point that they can imitate critical components of the brain's structure and function. Brain-on-a-chip (BoC) was first used for microfluidics-based systems with small synthetic tissues but has expanded recently to include in vitro simulation of the central nervous system (CNS). Defining the system's qualifying parameters may improve the BoC for the next generation of in vitro platforms. These parameters show how well a given platform solves the problems unique to in vitro CNS modeling (like recreating the brain's microenvironment and including essential parts like the blood-brain barrier (BBB)) and how much more value it offers than traditional cell culture systems. This review provides an overview of the practical concerns of creating and deploying BoC systems and elaborates on how these technologies might be used. Not only how advanced biosensing technologies could be integrated with BoC system but also how novel approaches will automate assays and improve point-of-care (PoC) diagnostics and accurate quantitative analyses are discussed. Key challenges providing opportunities for clinical translation of BoC in neurodegenerative disorders are also addressed.

Recent Progress and Perspectives on Neural Chip Platforms Integrating PDMS-Based Microfluidic Devices and Microelectrode Arrays

Recent years have witnessed a spurt of progress in the application of the encoding and decoding of neural activities to drug screening, diseases diagnosis, and brain-computer interactions. To overcome the constraints of the complexity of the brain and the ethical considerations of in vivo research, neural chip platforms integrating microfluidic devices and microelectrode arrays have been raised, which can not only customize growth paths for neurons in vitro but also monitor and modulate the specialized neural networks grown on chips. Therefore, this article reviews the developmental history of chip platforms integrating microfluidic devices and microelectrode arrays. First, we review the design and application of advanced microelectrode arrays and microfluidic devices. After, we introduce the fabrication process of neural chip platforms. Finally, we highlight the recent progress on this type of chip platform as a research tool in the field of brain science and neuroscience, focusing on neuropharmacology, neurological diseases, and simplified brain models. This is a detailed and comprehensive review of neural chip platforms. This work aims to fulfill the following three goals: (1) summarize the latest design patterns and fabrication schemes of such platforms, providing a reference for the development of other new platforms; (2) generalize several important applications of chip platforms in the field of neurology, which will attract the attention of scientists in the field; and (3) propose the developmental direction of neural chip platforms integrating microfluidic devices and microelectrode arrays.

From 2D to 3D: Development of Monolayer Dopaminergic Neuronal and Midbrain Organoid Cultures for Parkinson's Disease Modeling and Regenerative Therapy

Parkinson's Disease (PD) is a prevalent neurodegenerative disorder that is characterized pathologically by the loss of A9-specific dopaminergic (DA) neurons in the substantia nigra pars compacta (SNpc) of the midbrain. Despite intensive research, the etiology of PD is currently unresolved, and the disease remains incurable. This, in part, is due to the lack of an experimental disease model that could faithfully recapitulate the features of human PD. However, the recent advent of induced pluripotent stem cell (iPSC) technology has allowed PD models to be created from patient-derived cells. Indeed, DA neurons from PD patients are now routinely established in many laboratories as monolayers as well as 3D organoid cultures that serve as useful toolboxes for understanding the mechanism underlying PD and also for drug discovery. At the same time, the iPSC technology also provides unprecedented opportunity for autologous cell-based therapy for the PD patient to be performed using the patient's own cells as starting materials. In this review, we provide an update on the molecular processes underpinning the development and differentiation of human pluripotent stem cells (PSCs) into midbrain DA neurons in both 2D and 3D cultures, as well as the latest advancements in using these cells for drug discovery and regenerative medicine. For the novice entering the field, the cornucopia of differentiation protocols reported for the generation of midbrain DA neurons may seem daunting. Here, we have distilled the essence of the different approaches and summarized the main factors driving DA neuronal differentiation, with the view to provide a useful guide to newcomers who are interested in developing iPSC-based models of PD.