Back

Keratinocyte Arginase1 Deficiency Impairs Healing and Antimicrobial Defence against Pseudomonas aeruginosa Infection

Crompton, R. A.; Szondi, D. C.; Doherty, C.; Thomason, H. A.; Lee, S. H.; Ping, L. Y.; O'Neill, C. A.; Vardy, L.; McBain, A. J.; Cruickshank, S. M.

2025-02-25 microbiology
10.1101/2025.02.24.640016 bioRxiv
Show abstract

Wound infection is a major disruptor of wound healing. Keratinocytes, critical in repair and microbial responses, require the L-arginine hydrolysing enzyme arginase1, for effective healing. Wound pathogens such as Pseudomonas aeruginosa may also need L-arginine. We therefore investigated host-microbial interactions in the context of wound healing and L-arginine metabolism. Arginase-inhibited murine wounds challenged with P. aeruginosa, exhibited significantly delayed re-epithelialisation. This finding was recapitulated in vitro using P. aeruginosa-challenged, arginase1 deficient (shARG1) keratinocytes, associated with reduced epithelial proliferation and viability, and heightened inflammation. Whilst P. aeruginosa challenge promoted host metabolism of L-arginine, this was perturbed in wounded shARG1 keratinocytes. There was, however, heightened downstream polyamine metabolism in shARG1 cells when under P. aeruginosa challenge. Host keratinocyte arginase1 deficiency promoted bacterial growth in vitro, in line with a failure to upregulate the anti-microbial peptides, {beta}-defensins, in shARG1 scratches. This work demonstrates a pivotal role for keratinocyte arginase1 in wound infection. HIGHLIGHTSO_LIHost arginase is required for effective healing under P. aeruginosa challenge. C_LIO_LIP. aeruginosa enhances host keratinocyte L-arginine metabolism upon scratch. C_LIO_LIP. aeruginosa promotes polyamine metabolism in arginase1 deficient wounds in vitro. C_LIO_LIArginase1 is required for keratinocyte anti-microbial defence against P. aeruginosa. C_LI

Matching journals

The top 8 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.