Continuous low-intensity ultrasound influences the transcriptomic profile in M1 macrophages by downregulating inflammation and promoting M2-like markers

Macrophages are key regulators of inflammation, capable of adopting pro-inflammatory (M1) or anti-inflammatory (M2) phenotypes in response to environmental cues. In chronic conditions such as post-traumatic osteoarthritis (PTOA), persistent M1 activation contributes to tissue damage and impaired healing. Traditional models using lipopolysaccharide (LPS) to induce inflammation may not fully capture the complex microenvironment of joint injury. Here, we use fibronectin fragments (Fnfs), which are associated with matrix degradation, to establish a physiologically relevant inflammatory model and to apply transcriptomic analysis to investigate how continuous low-intensity ultrasound (cLIUS), a non-pharmacological biophysical stimulus, modulates macrophage responses under Fnfs-induced conditions. Beyond identifying differentially expressed genes (DEGs), we introduced network-level differential clustering (DC) to capture transcriptional remodeling, revealing context-specific regulators and co-expression shifts overlooked by gene-level analyses. cLIUS reprogrammed Fnfs-induced macrophages toward an M2-like reparative phenotype, marked by downregulation of pro-inflammatory and upregulation of tissue repair and immune-regulatory genes. DC further identified significant genes not detected by DEG analysis, with only partial overlap between ranked gene lists, as quantified by concordance indices of 0.52 for SD genes and 0.42 for DS genes (scale 0–1). These findings highlight the value of integrating clustering-based metrics with expression data to elucidate how biophysical treatments like cLIUS modulate immune cell behavior.