Applications of adeno-associated virus for 3D single-cell morphometric analysis in iPSC-derived midbrain organoids.

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Applications of adeno-associated virus for 3D single-cell morphometric analysis in iPSC-derived midbrain organoids.

Authors

Baeza Trallero, M. B.; Villeneuve, E.; Lepine, P.; Krahn Roldan, A. I.; Chen, X.; Reintsch, W. E.; Castellanos Montiel, M. J.; Durcan, T.; Berryer, M. H.

Abstract

Human midbrain organoids (hMBOs) are emerging in vitro models to mirror the cellular diversity and the structural complexity of the developing human brain. However, the dense neural network, limits the investigation of individual cell morphology or cell-cell connectivity, which is mostly restricted to fixed organoids following extensive optical clearing techniques. To better resolve individual cells within a brain organoid and for longitudinal tracking of its growth and development, we turned to adeno-associated virus (AAVs) for targeted gene delivery. In particular, we applied AAVs for expressing specific markers that provide the foundation to image individual cells within 3D hMBOs. Thus, we developed a phenotypic platform to specifically inspect the neuronal and astrocytic cytoarchitecture and to examine their connectivity in living hMBOs derived from two genetically unrelated control iPSC lines. We demonstrate that through AAV transduction, we could capture and reconstruct the 3D architecture of both neurons and astrocytes within the hMBO as a whole. Transduced cells exhibited an intrinsic heterogeneity in term of soma volume, arbor complexity and territory covered, regardless of both genetic background, age, and cell-type. Yet, these cellular morphometrics remained equivalent between the two cell lines, indicative of homogeneity in hMBO cellular development. We were able to establish longitudinal profiling of transduced cells, demonstrating how neurons and astrocytes could expand their network over time. Lastly, we describe time-lapse studies to track cellular motility and morphology fluctuations in neurons and astrocytes over time, highlighting the dynamic nature of these cells within the ramified architecture of the neural network in the developing hMBOs. Overall, our platform underscores the versatility of AAVs in studying single cell-morphometrics and cellular connectivity for longitudinal monitoring of cellular dynamics in live 3D hMBOs instead of a static snapshot.

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