Back

Characterisation of mesenchymal stromal cells in the skin of Atlantic salmon

Ruiz-Daniels, R.; J Salisbury, S.; Sveen, L.; S Taylor, R.; Vaadal, M.; Tengs, T.; Monaghan, S.; R Villamayor, P.; Ballantyne, M.; Penaloza, C.; D Fast, M.; E Bron, J.; D Houston, R.; Robinson, N.; Robledo, D.

2024-02-25 genomics
10.1101/2024.02.23.581759 bioRxiv
Show abstract

BackgroundThe skin serves as the first line of defence for an organism against the external environment. Despite the global significance of salmon in aquaculture, a critical component of this first line of defence, mesenchymal stromal cells, remains unexplored. These pluripotent cells can differentiate into various tissues, including bone, cartilage, tendon, ligament, adipocytes, dermis, muscle and connective tissue within the skin. These cells are pivotal for preserving the integrity of skin tissue throughout an organisms lifespan and actively participate in wound healing processes. ResultsIn this study, we characterise mesenchymal stromal cells in detail for the first time in healthy Atlantic salmon tissue and during the wound healing process. Single-nucleus sequencing and spatial transcriptomics revealed the transcriptional dynamics of these cells, elucidating the differentiation pathways leading to osteogenic and fibroblast lineages in the skin of Atlantic salmon. We charted their activity during an in vivo wound healing time course, showing clear evidence of their active role during this process, as they become transcriptionally more active during the remodelling stage of wound healing. ConclusionsFor the first time, we chart the activity of sub-clusters of differentiating stromal cells during the process of wound healing, revealing different spatial niches of the various MSC subclusters, and setting the stage for investigations into the manipulation of MSCs to improve fish health.

Matching journals

The top 11 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.