bioRxivBioengineeringPreprint
AggreBots: configuring CiliaBots through guided, modular tissue aggregation
Dhruv BhattaramiD, Keyvan GolestaniD, X. ZhangiD, Shu Min YangiD, Z. Gong, Steven L. BrodyiD, Amjad HoraniiD, Victoria A. Webster‐WoodiD, Amir Barati FarimaniiD, Xi ReniD
Abstract
Ciliated biobots, or CiliaBots, are a class of engineered multicellular tissues that are capable of self-actuated motility propelled by the motile cilia located on their exterior surface. Correlations have been observed between CiliaBot motility patterns and their morphology and cilia distribution. However, precise control of these structural parameters to generate desired motility patterns predictably remains lacking. Here, we developed a novel Aggregated CiliaBot (AggreBot) platform capable of producing designer motility patterns through spatially controlled aggregation of epithelial spheroids made from human airway cells (referred to as CiliaBot Building Blocks or CBBs), yielding AggreBots with configurable geometry and distribution of active cilia. Guided multi-CBB aggregation led to the production of rod-, triangle-, and diamond-shaped AggreBots, which consistently effected greater motility than traditional single-spheroid CiliaBots. Furthermore, CBBs were found to maintain internal boundaries post-aggregation through the combined action of pathways controlling cellular fluidity and tissue polarity. This boundary fidelity, combined with the use of CBBs with immotile cilia due to mutations in the CCDC39 gene, allowed for the generation of hybrid AggreBots with precision control over the coverage and distribution of active cilia, further empowering control of motility patterns. Our results demonstrate the potential of AggreBots as self-propelling biological tissues through the establishment of morphological "levers" by which alterations to tissue motility can be theoretically planned and experimentally verified.
- organism: human
- assay: multiome
- research focus: cell type annotation
- research focus: clustering
- research focus: cell-cell communication
- research focus: spatial domain detection
- approach: experimental assay
- Citations
- 0
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