Abstract
Category:
Other
Introduction/Purpose:
Foot infections are often polymicrobial with diverse microbiomes. Accurate identification of the main pathogen in diabetic foot ulcer (DFU) remain challenging due to contamination or negative cultures often leading to ineffective post-surgical antibiotic treatment. Application of molecular diagnostics, such as next generation sequencing (NGS) has been explored as an alternative to standard culture in orthopaedic infections. NGS is highly sensitive and detects an entire bacterial genome along with pharmacologic resistant genes in a given sample. We sought to investigate the potential use of NGS for accurate diagnosis and quantification of various species in infected DFU. We hypothesize that NGS will provide a more accurate means of diagnosing and profiling microorganisms in infected DFU compared to the standard culture method.
Methods:
We investigated 30 infected DFU patients who underwent surgical treatment by a single academic orthopaedic surgeon from October 2018 to September 2019. The average age of the patient was 60.4 (range 33-82) years-old. Surgical procedures performed were irrigation and debridement (12), toe or ray amputation (13), calcanectomies (4), and below-knee amputation (1). Infected bone specimens were obtained intraoperatively and processed for standard culture and NGS. Quantitative PCR was performed to determine the bacterial burden present in the sample. DNA was amplified by PCR from a highly conserved region of the rRNA gene in the bacteria (16S rRNA). Once a high level of DNA was generated and determined, it was compared against NIH GenBank database. Concordance between the standard culture and NGS was assessed.
Results:
In 28 of 29 patients, pathogens were identified by both NGS and culture, with complete consistency of organisms in 13 cases (concordance rate: 43.3%). NGS provided relative quantitative measures and the presence of antibiotic resistant genes for each pathogen. In NGS, Anaerococcus species (79.3%) was the most common organism, followed by Streptococcus species (44.8%), Prevotella species (44.8%), Finegoldia magna (44.8%). In culture, S. aureus (58.6%) was the most common, followed by Streptococcus species (34.5%), coagulase-negative Staphylococci (24.1%), Corynebacterium species (20.7%). On average, NGS revealed 5.1 (1-11) number of pathogens, whereas standard culture revealed 2.6 (1-6) pathogens in a given sample. NGS identified 2 cases with false positive standard culture and detected antibiotic resistant organisms in 15 specimens.
Conclusion:
NGS is an emerging method of microbial identification in orthopedic infection. It is particularly helpful in profiling diverse microbes in polymicrobial infected DFU. It can identify major pathogens and may correct false positive or false negative culture. NGS may allow a faster invitation of postoperative targeted antibiotic therapy.
