Mathematical and deep learning analysis of wound healing in flies #

Jake Turley, I V Chenchiah, T B Liverpool, H Weavers, P Martin

15:10 Tuesday in 4Q56.

Part of the New mathematical approaches in the life sciences session.

Abstract #

Wound healing is a highly conserved process required for survival after tissue damage. In mammals, the three cell-behaviours that contribute to wound re-epithelialisation are cell shape deformation, cell division, and cell migration. Here we quantify the contributions of each of these cell behaviours after wounding the translucent Drosophila pupal wing. We have developed several deep learning algorithms to identify dividing cells with 96% accuracy and determine the orientation of these divisions and shuffling of daughter cells relative to the wound margin. We find a reduction in their density close to the wound edge suggesting that active cell migration reduces cell divisions. About 2hr after wounding we observe a synchronised burst of divisions further back. Next, we will genetically modify wound signals to knockdown one or more cell behaviours and examine not only the gross effect on wound closure, but also how the other behaviours compensate.