Aim. Bone and joint infections (BJI) need frequently prolonged antibiotic treatment at high dosage for a total of 6 or 12 weeks depending the type of infection. Impact of such prolonged antibiotic exposure on the gut
Aim. The origin of surgical site and biomaterial-associated infection is still elusive. Microorganisms contaminating the wound may come from the air, the surgical team, or from the skin of the patient. Prior to surgery the skin of patients is disinfected, but bacteria deeper in the skin (e.g. in sweat glands or sebaceous glands), may not be reached. This study aims to assess a potential role of this intracutaneous bacterial reservoir in biomaterial-associated infection. Method. To study if cutaneous
Aim. To date, no ultimate diagnostic gold standard for prosthetic joint infections (PJI) has been established. In recent years, next generation sequencing (NGS) has emerged as a promising new tool, especially in culture-negative samples. In this prospective study, we performed metagenomic analysis using 16S rRNA V3-V4 amplicon NGS in samples from patients with suspected PJI. Methods. A total of 257 (187 culture-negative (CN) and 70 culture-positive (CP)) prospectively collected tissues and sonication fluid from 32 patients (56 revisions) were included. 16S rRNA V3-V4 amplicons were sequenced using Illumina's MiSeq (California, USA) followed by bioinformatic analysis using nf-core/ampliseq pipeline. Results. We successfully sequenced 255 samples and detected a total of 105 microorganisms. These were mainly environmental microorganisms present in a small number of reads (≤100), indicating possible contamination. Pseudomonas spp. (non-aeruginosa species) was detected most frequently in 73% (187/255) of samples. The test showed limitations in species classification and identified microorganisms mainly at genus level. Significant differences in the number of reads were observed when comparing CN (≤100) and CP (≥1000) samples. In two CP, no bacteria were identified with sequencing, which is probably due to low bacterial load (1 CFU. Haemophilus spp. was detected with a significant number of reads (≥10000) in five samples from a single patient, in whom infection was considered likely according to EBJIS criteria, changing it to confirmed infection. Staphylococcus spp. was identified with ≥10000 reads in two CNs from an individual who was receiving antibiotic treatment at the time, had clinical signs of infection, and had a confirmed infection with S. lugdunensis one month earlier. Cutibacterium spp. with 36% (93/257) and Staphylococcus spp. with 34% (87/257) were detected with a minimal number of reads (≤100) in several CN, indicating possible contamination with normal skin