A pH-gated surface-mediated hydrogel patch for infection-responsive delivery of CRISPR-Cas9 ribonucleoprotein (RNP) complexes establishes a novel paradigm for localized, precision gene therapy and holds strong translational promise for the treatment of chronic inflammatory wounds.
Abstract
The NLRP3 inflammasome is a central driver of inflammatory tissue injury and delayed repair in bacteria-infected wounds, yet local genome editing in such lesions remains limited by nonspecific release and off-target exposure. Here, we report a pH-gated surface-mediated hydrogel patch for infection-responsive delivery of CRISPR-Cas9 ribonucleoprotein (RNP) complexes. Rather than embedding the cargo within the bulk matrix, polymer-coated NLRP3-targeting RNPs are reversibly anchored on the hydrogel surface, enabling localized presentation under physiological conditions and rapid detachment in the acidic microenvironment of Staphylococcus aureus (S. aureus)-infected wounds. In vitro studies demonstrated an NLRP3 editing efficiency of 57% in J774A.1 cells and 69% in L929 cells surpassing or matching the performance of the commercial transfection reagent Lipofectamine CRISPRMAX (50% in J774A.1; comparable in L929). In a murine full-thickness skin defect model with S. aureus infection, topical administration of the patch achieved >20% NLRP3 editing efficiency in wound tissue, accompanied by a statistically significant reduction in inflammatory cell infiltration. Consequently, this pH-responsive surface anchoring and release strategy establishes a novel paradigm for localized, precision gene therapy and holds strong translational promise for the treatment of chronic inflammatory wounds.
It is concluded that bridging the gap between foundational CRISPR research and its real-world applications is imperative and future efforts should focus on democratizing tools via open-source platforms, advancing delivery systems, and fostering sustainable innovation through synthetic biology integration to fully realize the transformative potential of genome editing in organisms beyond model organisms.
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MIT News · Artificial Intelligence· news.mit.eduAug 17, 2026