Immunotherapy has reached clinical success in the last decade, with the emergence of new and effective treatments such as checkpoint blockade therapy and CAR T-cell therapy that have drastically improved patient outcomes. Still, these therapies can be improved to limit off-target effects, mitigate systemic toxicities, and increase overall efficacies. Nanoscale engineering offers strategies that enable researchers to attain these goals through the manipulation of immune cell functions, such as enhancing immunity against cancers and pathogens, controlling the site of immune response, and promoting tolerance via the delivery of small molecule drugs or biologics. By tuning the properties of the nanomaterials, such as size, shape, charge, and surface chemistry, different types of immune cells can be targeted and engineered, such as dendritic cells for immunization, or T cells for promoting adaptive immunity. Researchers have come to better understand the critical role the immune system plays in the progression of pathologies besides cancer, and developing nanoengineering approaches that seek to harness the potential of immune cell activities can lead to favorable outcomes for the treatment of injuries and diseases.

The growing knowledge of the links between aberrant mitochondrial gene transcription and human diseases necessitates both an effective and dynamic approach to control mitochondrial DNA (mtDNA) transcription. To address this challenge, we developed a nanoparticle-based synthetic mitochondrial transcription regulator (MitoScript). MitoScript provides great colloidal stability, excellent biocompatibility, efficient cell uptake, and selective mitochondria targeting and can be monitored in live cells using near-infrared fluorescence. Notably, MitoScript controlled mtDNA transcription in a human cell line in an effective and selective manner. MitoScript targeting the light strand promoter region of mtDNA resulted in the downregulation of ND6 gene silencing, which eventually affected cell redox status, with considerably increased reactive oxygen species (ROS) generation. In summary, we developed MitoScript for the efficient, nonviral modification of mitochondrial DNA transcription. Our platform technology can potentially contribute to understanding the fundamental mechanisms of mitochondrial disorders and developing effective treatments for mitochondrial diseases.

Biophysical cues, such as nanotopographies of extracellular matrix (ECM), are key cell regulators for direct cell reprogramming. Therefore, high-throughput methods capable of systematically screening a wide range of biophysical cue-regulated cell reprogramming are increasingly needed for tissue engineering and regenerative medicine. Here, we report the development of a dynamic laser interference lithography (DIL) to generate large-scale combinatorial biophysical cue (CBC) arrays with diverse micro/nanostructures at higher complexities than most current arrays. Using CBC arrays, a high-throughput cell mapping method is further demonstrated for the systematic investigation of biophysical cue-mediated direct cell reprogramming. This CBC array-based high-throughput cell screening approach facilitates the rapid identification of unconventional hierarchical nanopatterns that induce the direct reprogramming of human fibroblasts into neurons through epigenetic modulation mechanisms. In this way, we successfully demonstrate DIL for generating highly complex CBC arrays and establish CBC array-based cell screening as a valuable strategy for systematically investigating the role of biophysical cues in cell reprogramming.

A systematic investigation of stem cell-derived neural interfaces can facilitate the discovery of the molecular mechanisms behind cell behavior in neurological disorders and accelerate the development of stem cell-based therapies. Nevertheless, high-throughput investigation of the cell-type-specific biophysical cues associated with stem cell-derived neural interfaces continues to be a significant obstacle to overcome. To this end, we developed a combinatorial nanoarray-based method for high-throughput investigation of neural interface micro-/nanostructures (physical cues comprising geometrical, topographical, and mechanical aspects) and the effects of these complex physical cues on stem cell fate decisions. Furthermore, by applying a machine learning (ML)-based analytical approach to a large number of stem cell-derived neural interfaces, we comprehensively mapped stem cell adhesion, differentiation, and proliferation, which allowed for the cell-type-specific design of biomaterials for neural interfacing, including both adult and human-induced pluripotent stem cells (hiPSCs) with varying genetic backgrounds. In short, we successfully demonstrated how an innovative combinatorial nanoarray and ML-based platform technology can aid with the rational design of stem cell-derived neural interfaces, potentially facilitating precision, and personalized tissue engineering applications.

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