Expect the unexpected: conventional and unconventional roles for cadherins in collective cell migration

Effects of various cross-linked collagen scaffolds on wound healing in rats model by deep-learning CNN

Scar tissue is connective tissue formed on the wound during the wound-healing process. The most significant distinction between scar tissue and normal tissue is the appearance of covalent cross-linking and the amount of collagen fibers in the tissue. This study investigates the efficacy of four types of collagen scaffolds in promoting wound healing and regeneration in a Sprague-Dawley murine model-the histomorphology analysis of collagen scaffolds and developing a deep learning model for accurate tissue classification. Four female rats (n = 24) groups received collagen scaffolds prepared through physical and chemical crosslinking. Wound healing progress was evaluated by monitoring granulation tissue formation, collagen matrix organization, and collagen fiber deposition, with histological scoring for quantification-the EDC and HA groups demonstrated enhanced tissue regeneration. The EDC and HA groups observed significant differences in wound regeneration outcomes. Deep-learning CNN models with data augmentation techniques were used for image analysis to enhance objectivity. The CNN architecture featured pre-trained VGG16 layers and global average pooling (GAP) layers. Feature visualization using Grad-CAM heatmaps provided insights into the neural network's focus on specific wound features. The model's AUC score of 0.982 attests to its precision. In summary, collagen scaffolds can promote wound healing in mice, and the deep learning image analysis method we proposed may be a new method for wound healing assessment.

Transcriptome analysis reveals temporally regulated genetic networks during Drosophila border cell collective migration

BACKGROUND

Collective cell migration underlies many essential processes, including sculpting organs during embryogenesis, wound healing in the adult, and metastasis of cancer cells. At mid-oogenesis, Drosophila border cells undergo collective migration. Border cells round up into a small group at the pre-migration stage, detach from the epithelium and undergo a dynamic and highly regulated migration at the mid-migration stage, and stop at the oocyte, their final destination, at the post-migration stage. While specific genes that promote cell signaling, polarization of the cluster, formation of protrusions, and cell-cell adhesion are known to regulate border cell migration, there may be additional genes that promote these distinct active phases of border cell migration. Therefore, we sought to identify genes whose expression patterns changed during border cell migration.

RESULTS

We performed RNA-sequencing on border cells isolated at pre-, mid-, and post-migration stages. We report that 1,729 transcripts, in nine co-expression gene clusters, are temporally and differentially expressed across the three migration stages. Gene ontology analyses and constructed protein-protein interaction networks identified genes expected to function in collective migration, such as regulators of the cytoskeleton, adhesion, and tissue morphogenesis, but also uncovered a notable enrichment of genes involved in immune signaling, ribosome biogenesis, and stress responses. Finally, we validated the in vivo expression and function of a subset of identified genes in border cells.

CONCLUSIONS

Overall, our results identified differentially and temporally expressed genetic networks that may facilitate the efficient development and migration of border cells. The genes identified here represent a wealth of new candidates to investigate the molecular nature of dynamic collective cell migrations in developing tissues.