Surface‐Functionalized Self‐Standing Microdevices Exhibit Predictive Localization and Seamless Integration in 3D Neural Spheroids

Abstract

diseases and develop potential cures. [1] Developments across the fields of biotechnology, tissue engineering, biomaterials, and microtechnology, have led to in vitro models ranging from multilayer 3D cell cultures [2] to small self-standing cell aggregates called spheroids, [3] up to complex brain organoids derived from human pluripotent stem (hPS) cells. [4] Albeit grown in an artificial in vitro environment, the shift from conventional 2D neural cultures to 3D models was shown to better mimic the complexity of intertwined 3D networks found in the brain. [5] hPS-derived brain organoids can indeed recapitulate several aspects specific to human brain development at the level of gene expression, [6] cell-type differentiation and network formation, [7] and can express phenotypes of human brain diseases when generated from patient-derived hPS-cells. [4a,8] Following these results, 3D neural cell assemblies have raised a large interest for the study of human brain diseases and therapies. Furthermore, these models can overcome certain limitations of currently used animal models, such as low experimental accessibility for functional studies, [9] low sample size, low reproducibility and, above all, poor translational relevance of screening results to humans. [5] The routine experimental use of 3D brain tissue models, however, remains largely unpractical for applications in drugdiscovery. On one side, intermodel variability and unmonitored cellular viability can affect the reliable generation of complex 3D brain tissue model systems. For instance, as 3D models become critically sized, the low diffusion of nutrients and oxygen tends to induce the formation of a necrotic core, [1b,4a,5] with consequent losses in cellular viability. On the other side, available biosensing technologies are not yet adapted for the routine monitoring of biosignals such as neural activity inside individual 3D models. This hinders studies aiming toward a better understanding of the emergence of spontaneous neural activity in these models as well as their optimization to reliably generate electrically active brain tissue models for functional assays. Over the last few years, researchers have been working on protocols for culturing organoids with minimal variability, mainly focusing on homogenizing morphologies. [4c] As far as monitoring brain organoids, current major biosensing Brain organoids is an exciting technology proposed to advance studies on human brain development, diseases, and possible therapies. Establishing and applying such models, however, is hindered by the lack of technologies to chronically monitor neural activity. A promising new approach comprising selfstanding biosensing microdevices capable of achieving seamless tissue integration during cell aggregation and culture. To date, there is little information on how to control the aggregation of such bioartificial 3D neural assemblies. Here, the growth of hybrid neurospheroids obtained by the aggregation of silicon sham microchips (100 × 100 × 50 μm 3) with primary cortical cells ...

Integrated Micro-Devices for a Lab-in-Organoid Technology Platform: Current Status and Future Perspectives

“…Additionally, Micro Electro-Mechanical Systems (MEMS) solutions previously developed in our lab ( Angotzi et al, 2019a ) for post-processing CMOS dies can be adapted to extracting single μRadios from the bulky silicon either from single dies or from whole CMOS wafers. Similarly, our results previously reported in Lecomte et al (2020) demonstrate how the presence of Si micro-device of similar size as the one targeted in this work does not affect the developing 3D morphology, cellular composition and the spontaneous neural activity of developing neurospheroids. In addition, surface functionalization via protein-binding can tune the integration and final 3D location of self-standing micro-devices into neurospheroids.…”

“…The post-processing of the CMOS micro-device, recurring to MEMS manufacturing technologies, besides the final micro-device dimensions, can also allow for the encapsulation of the micro-device with biologically compatible and functionalized materials, as well as for depositing noble, bio compatible materials on the native Al-Cu CMOS alloy of the sensing electrodes. Solutions previously developed in our lab (see Angotzi et al, 2019a ; Lecomte et al, 2020 ; Ribeiro et al, 2021 ) for post-processing CMOS dies and (bio)materials functionalization can be adapted for extracting single μRadios from the bulky silicon either from single dies or from whole CMOS wafers. Furthermore, using author’s previous experience with polyimide based neural interfaces ( Simi et al, 2014 ; Rodrigues et al, 2020 ; Pimenta et al, 2021 ), polyimide-based 3D structures with through polymer vias ( Hussain and Hussain, 2016 ) can be used to integrate the designed antenna between polyimide layers, routing the electrodes to the top surface of the micro-device ensuring the biocompatibility.…”

“…Within this framework, an emerging new approach consists in fusing sensing strategies and/or actuating artificial devices with organoids ( Li et al, 2019 ; McDonald et al, 2021 ). Differently from these approaches, our concept is based on the development of bio-artificial 3D brain model systems with seamless, tissue-integrated, untethered microscale active devices that can provide wireless sensing or actuation of extracellular bio-signals ( Angotzi et al, 2018 , 2019a ; Lecomte et al, 2020 ). Advances in complementary metal-oxide-semiconductor (CMOS) technology have in fact permitted over the past few years the design and fabrication of low-area, low-power, and highly integrated solutions optimized for untethered sensing of biological parameters.…”

“…As illustrated in Figure 1 , we envision the generation of these novel 3D models with built-in transducers by promoting the self-aggregation of cells and microscale devices while culturing in vitro the resulting assemblies. In our previous work we have shown that the surface functionalization of Si micro-devices of 100 μm × 100 μm in size can be used to control their final localization inside self-aggregated bio-artificial neural spheroids ( Lecomte et al, 2020 ). For read-out, we plan to channelize each 3D model within a microfluidic device, therefore, with powering and readout operations occurring for one model at a time, while transiting through the section equipped with a Base reader .…”

2022 roadmap on neuromorphic computing and engineering

“…Much progress has been made to incorporate artificial devices within neural spheroids [522], or inside single living cells [512,513]. However, these are biosensors of simple architecture, far from the complexity of a neuromorphic system.…”