Background: Necrotizing soft-tissue infections (NSTIs) are life threatening, requiring broad-spectrum antibiotics. Their aetiological diagnosis can be limited by poor performance of cultures and administration of antibiotics before surgery.
Objectives: We aimed (i) to compare 16S-targeted metagenomics (TM) and unbiased semiquantitative panmicroorganism DNA- and RNA-based shotgun metagenomics (SM) with cultures, (ii) to identify patients who would best benefit from metagenomics approaches and (iii) to detect the microbial pathogens in surrounding non-necrotic 'healthy' tissues by SM-based methods.
Methods: A prospective observational study was performed to assess the analytical performance of standard cultures, TM and SM on tissues from 34 patients with NSTIs. Pathogen identification obtained with these three methods was compared.
Results: Thirty-four necrotic and 10 healthy tissues were collected from 34 patients. The performance of TM was inferior to that of the other methods (P < 0·05), whereas SM performed better than standard culture, although the result was not statistically significant (P = 0·08). SM was significantly more sensitive than TM for the detection of all bacteria (P = 0·02) and more sensitive than standard culture for the detection of anaerobic bacteria (P < 0·01). There was a strong correlation (r = 0·71, Spearman correlation coefficient) between the semiquantitative abundance of bacteria in the culture and the bacteria-to-human sequence ratio in SM. Low amounts of bacterial DNA were found in healthy tissues, suggesting a bacterial continuum between macroscopically 'healthy' and necrotic tissue.
Conclusions: SM showed a significantly better ability to detect a broader range of pathogens than TM and identify strict anaerobes than standard culture. Patients with diabetes with NSTIs appeared to benefit most from SM. Finally, our results suggest a bacterial continuum between macroscopically 'healthy' non-necrotic areas and necrotic tissues. What's already known about this topic? Necrotizing soft-tissue infections (NSTIs) are characterized by rapidly progressive necrosis of subcutaneous tissues and high mortality, despite surgical debridement combined with broad-spectrum antibiotics. The spectrum of potentially involved pathogens is very large, and identification is often limited by the poor performance of standard cultures, which may be impaired by previous antibiotic intake. Metagenomics-based approaches show promise for better identification of the pathogens that cause these infections, but they have not been evaluated in this medical context. What does this study add? Shotgun metagenomics (SM) showed higher sensitivity than 16S rRNA gene sequencing and a better ability than culture to detect anaerobic bacteria. As a result, a significant proportion of infections with bacteria, such as Pasteurella multocida or Clostridium perfringens, were detected only by SM. SM bacterial quantification enabled better detection of low amounts of bacterial DNA from macroscopically 'healthy' tissue, suggesting a subclinical infectious extension. What is the translational message? The high analytical performance of SM shown in this study should allow its future implementation for the diagnosis of necrotizing fasciitis, complementing or replacing routine methods. The large amount of data, including additional information on antimicrobial resistance, virulence profiles and metabolic adaptation of the pathogens, will improve microbiological documentation. Our results will improve our understanding of infectious pathophysiology in the future, leading to potentially better medical care.
© 2019 British Association of Dermatologists.