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Kidney transplant recipients develop atypical infections in their epidemiology, presentation and outcome. Among these, meningitis and meningoencephalitis require urgent and adapted anti-infectious therapy, but published data is scarce in KTRs. The aim of this study was to describe their epidemiology, presentation and outcome, in order to improve their diagnostic and management. We performed a retrospective, multicentric cohort study in 15 French hospitals that included all 199 cases of M/ME in KTRs between 2007 and 2018 (0.9 case per 1,000 KTRs annually). Epidemiology was different from that in the general population: 20% were due to Cryptococcus neoformans, 13.5% to varicella-zoster virus, 5.5% to Mycobacterium tuberculosis, and 4.5% to Enterobacteria (half of which produced extended spectrum beta-lactamases), and 5% were Post Transplant Lymphoproliferative Disorders. Microorganisms causing M/ME in the general population were infrequent (2%, for Streptococcus pneumoniae) or absent (Neisseria meningitidis). M/ME caused by Enterobacteria, Staphylococci or filamentous fungi were associated with high and early mortality (50%–70% at 1 year). Graft survival was not associated with the etiology of M/ME, nor was impacted by immunosuppression reduction. Based on these results, we suggest international studies to adapt guidelines in order to improve the diagnosis and the probabilistic treatment of M/ME in SOTRs.

Bacteriological diagnosis is traditionally based on culture. However, this method may be limited by the difficulty of cultivating certain species or by prior exposure to antibiotics, which justifies the resort to molecular methods, such as Sanger sequencing of the 16S rRNA gene (Sanger 16S). Recently, shotgun metagenomics (SMg) has emerged as a powerful tool to identify a wide range of pathogenic microorganisms in numerous clinical contexts. In this study, we compared the performance of SMg to Sanger 16S for bacterial detection and identification. All patients’ samples for which Sanger 16S was requested between November 2019 and April 2020 in our institution were prospectively included. The corresponding samples were tested with a commercial 16S semi-automated method and a semi-quantitative pan-microorganism DNA- and RNA-based SMg method. Sixty-seven samples from 64 patients were analyzed. Overall, SMg was able to identify a bacterial etiology in 46.3% of cases (31/67) vs. 38.8% (26/67) with Sanger 16S. This difference reached significance when only the results obtained at the species level were compared (28/67 vs. 13/67). This study provides one of the first evidence of a significantly better performance of SMg than Sanger 16S for bacterial detection at the species level in patients with infectious diseases for whom culture-based methods have failed. This technology has the potential to replace Sanger 16S in routine practice for infectious disease diagnosis.