open access publication

Article, 2024

A single-source nosocomial outbreak of Aspergillus flavus uncovered by genotyping.

Microbiology Spectrum, ISSN 2165-0497, Page e0027324, 10.1128/spectrum.00273-24

Contributors

Gewecke, A [1] Hare, Rasmus Krøger 0000-0002-9796-023X [1] Salgård, C [2] Kyndi, L [2] Høg, Mia Kristine Grønning [2] Petersen, G [2] Nahimana, D [1] Abou-Chakra, Nissrine [1] Knudsen, Jenny Dahl 0000-0002-8699-9956 [2] Rosendahl, S [3] Vissing, Nadja Hawwa [2] Arendrup, M C [1] [2] [3]

Affiliations

  1. [1] Statens Serum Institut
  2. [NORA names: SSI Statens Serum Institut; Governmental Institutions; Denmark; Europe, EU; Nordic; OECD];
  3. [2] Rigshospitalet
  4. [NORA names: Capital Region of Denmark; Hospital; Denmark; Europe, EU; Nordic; OECD];
  5. [3] University of Copenhagen
  6. [NORA names: KU University of Copenhagen; University; Denmark; Europe, EU; Nordic; OECD]

Abstract

During construction work (2017-2019), an increase in Aspergillus flavus infections was noted among pediatric patients, the majority of whom were receiving amphotericin B prophylaxis. Microsatellite genotyping was used to characterize the outbreak. A total of 153 A. flavus isolates of clinical and environmental origin were included. Clinical isolates included 140 from 119 patients. Eight patients were outbreak-related patients, whereas 111 were outbreak-unrelated patients from Danish hospitals (1994-2023). We further included four control strains. Nine A. flavus isolates were from subsequent air sampling in the outbreak ward (2022-2023). Typing followed Rudramurthy et al.(S. M. Rudramurthy, H. A. de Valk, A. Chakrabarti, J. Meis, and C. H. W. Klaassen, PLoS One 6:e16086, 2011, https://doi.org/10.1371/journal.pone.0016086). Minimum spanning tree (MST) and discriminant analysis of principal components (DAPC) were used for cluster analysis. DAPC analysis placed all 153 isolates in five clusters. Microsatellite marker pattern was clearly distinct for one cluster compared to the others. The same cluster was observed in an MST. This cluster included all outbreak isolates, air-sample isolates, and additional patient isolates from the outbreak hospital, previously undisclosed as outbreak related. The highest air prevalence of A. flavus was found in two technical risers of the outbreak ward, which were then sealed. Follow-up air samples were negative for A. flavus. Microsatellite typing defined the outbreak as nosocomial and facilitated the identification of an in-hospital source. Six months of follow-up air sampling was without A. flavus. Outbreak-related/non-related isolates were easily distinguished with DAPC and MST, as the outbreak clone's distinct marker pattern was delineated in both statistical analyses. Thus, it could be a variant of A. flavus, with a niche ability to thrive in the outbreak-hospital environment. IMPORTANCE: Aspergillus flavus can cause severe infections and hospital outbreaks in immunocompromised individuals. Although lack of isogeneity does not preclude an outbreak, our study underlines the value of microsatellite genotyping in the setting of potential A. flavus outbreaks. Microsatellite genotyping documented an isogenic hospital outbreak with an internal source. This provided the "smoking gun" that prompted the rapid allocation of resources for thorough environmental sampling, the results of which guided immediate and relevant cleaning and source control measures. Consequently, we advise that vulnerable patients should be protected from exposure and that genotyping be included early in potential A. flavus outbreak investigations. Inspection and sampling are recommended at any site where airborne spores might disperse from. This includes rarely accessed areas where air communication to the hospital ward cannot be disregarded.

Keywords

Airborne, Aspergillus flavus, Danish hospitals, ability, air, air communication, air samples, airborne spores, allocation, allocation of resources, amphotericin, amphotericin B prophylaxis, analysis, analysis of principal components, cleaning, clinical isolates, cluster analysis, clusters, communication, components, construction, construction work, control, control measures, control strain, discriminant analysis, discriminant analysis of principal component analysis, discriminant analysis of principal components, environment, environmental origin, environmental samples, exposure, flavus, genotypes, gun, hospital, hospital outbreaks, hospital wards, identification, immunocompromised individuals, increase, individuals, infection, inspection, internal sources, isogenes, isolates, marker patterns, measurements, microsatellite, microsatellite genotyping, microsatellite typing, minimum, minimum spanning tree, months, niche, nosocomial outbreaks, origin, outbreak, outbreak hospital, outbreak isolates, outbreak ward, outbreak-related patients, patient isolates, patients, patterns, pediatric patients, prevalence, principal components, resources, results, riser, samples, severe infections, sites, smoking, smoking gun, source, source control measures, spanning tree, spores, statistical analysis, strain, study, trees, type, variants, vulnerable patients, ward, work

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