Emerging Concepts in Periprosthetic Joint Infection Research: RNA, DNA, and Protein Sequencing Tools for the...

Culture-based diagnostics have been utilized historically by the orthopaedic community to help identify the causative organism for patients with periprosthetic joint infection (PJI) following total joint arthroplasty. However, conventional cultures fail to isolate the causative organisms in up to 42% of cases. This is concerning, as treatment of culture-negative PJI poses a real challenge, often requiring prolonged administration of multiple antimicrobials. Furthermore, counseling patients regarding a diagnosis of PJI, the need for multiple surgical procedures, and prolonged antimicrobial therapy without identification of a causative organism is challenging and highlights the diagnostic uncertainty that complicates prognostication, antimicrobial selection, and shared decision-making in culture-negative cases. Novel sequencing techniques have been developed to help identify the infective organism(s), particularly in culture-negative cases, and better understand the pathogenesis of PJI and infection recurrence. Specifically, next-generation sequencing, including DNA and RNA sequencing, and protein-based analysis have emerged as promising tools. The DNA-based approaches represent the most commonly employed tools used in clinical practice for arthroplasty surgeons, demonstrating superior sensitivity and specificity when used in tandem with culture. Beyond pathogen detection, RNA-based sequencing provides profiling of both host immune response and active pathogen gene expression. Preliminary evidence from RNA-based sequencing has also demonstrated the ability to identify antibiotic-resistance genes. Additionally, these novel sequencing tools can help elucidate the pathogenesis of PJI, characterize microbe-host interactions, and improve the understanding of both chronic and refractory PJI. CLINICAL RELEVANCE: Although challenges remain regarding cost and interpretation, sequencing-based tools may optimize diagnostic accuracy, identify novel biomarkers, guide targeted antimicrobial therapy, and ultimately improve treatment and prevent infection recurrence. Moreover, high-resolution sequencing platforms have revealed heterogeneity among infections that appear clinically similar. Together, these evolving technologies represent a paradigm shift from binary pathogen detection toward comprehensive profiling of microbial identity, pathogen activity, and host response.