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Oberhettinger, P.

Publications and source records attributed to Oberhettinger, P..

2 recordsLinked to original sources

Tracking of antibiotic resistance transfer and rapid plasmid evolution in a hospital setting by Nanopore sequencing

BackgroundInfection of patients with multidrug-resistant (MDR) bacteria often leave very limited or no treatment options. The transfer of antimicrobial resistance genes (ARG) carrying plasmids between bacterial species by horizontal gene transfer represents an important mode of expansion of ARGs. Here, we evaluated the application of Nanopore sequencing technology in a hospital setting for monitoring the transfer and rapid evolution of antibiotic resistance plasmids within and across multiple species.\n\nResultsIn 2009 we experienced an outbreak with an extensively multidrug resistant P. aeruginosa harboring the carbapenemase enzyme blaIMP-8, and in 2012 the first Citrobacter freundii and Citrobacter werkmanii harboring the same enzyme were detected. Using Nanopore and Illumina sequencing we conducted a comparative analysis of all blaIMP-8 bacteria isolated in our hospital over a 6-year period (n = 54). We developed the computational platforms pathoLogic and plasmIDent for Nanopore-based characterization of clinical isolates and monitoring of ARG transfer, comprising de-novo assembly of genomes and plasmids, polishing, QC, plasmid circularization, ARG annotation, comparative genome analysis of multiple isolates and visualization of results. Using plasmIDent we identified a 40 kb plasmid carrying blaIMP-8 in P. aeruginosa and C. freundii, verifying that plasmid transfer had occurred. Within C. freundii the plasmid underwent further evolution and plasmid fusion, resulting in a 164 kb mega-plasmid, which was transferred to C. werkmanii. Moreover, multiple rearrangements of the multidrug resistance gene cassette were detected in P. aeruginosa, including deletions and translocations of complete ARGs.\n\nConclusionPlasmid transfer, plasmid fusion and rearrangement of the multidrug resistance gene cassette mediated the rapid evolution of opportunistic pathogens in our hospital. We demonstrated the feasibility of tracking plasmid evolution dynamics and ARG transfer in clinical settings in a timely manner. The approach will allow for successful countermeasures to contain not only clonal, but also plasmid mediated outbreaks.

genomics↗

Multi-omics approach identifies novel pathogen-derived prognostic biomarkers in patients with Pseudomonas aeruginosa bloodstream infection

Pseudomonas aeruginosa is a human pathogen that causes health-care associated blood stream infections (BSI). Although P. aeruginosa BSI are associated with high mortality rates, the clinical relevance of pathogen-derived prognostic biomarker to identify patients at risk for unfavorable outcome remains largely unexplored. We found novel pathogen-derived prognostic biomarker candidates by applying a multi-omics approach on a multicenter sepsis patient cohort. Multi-level Cox regression was used to investigate the relation between patient characteristics and pathogen features (2298 accessory genes, 1078 core protein levels, 107 parsimony-informative variations in reported virulence factors) with 30-day mortality. Our analysis revealed that presence of the helP gene encoding a putative DEAD-box helicase was independently associated with a fatal outcome (hazard ratio 2.01, p = 0.05). helP is located within a region related to the pathogenicity island PAPI-1 in close proximity to a pil gene cluster, which has been associated with horizontal gene transfer. Besides helP, elevated protein levels of the bacterial flagellum protein FliL (hazard ratio 3.44, p < 0.001) and of a bacterioferritin-like protein (hazard ratio 1.74, p = 0.003) increased the risk of death, while high protein levels of a putative aminotransferase were associated with an improved outcome (hazard ratio 0.12, p < 0.001). The prognostic potential of biomarker candidates and clinical factors was confirmed with different machine learning approaches using training and hold-out datasets. The helP genotype appeared the most attractive biomarker for clinical risk stratification due to its relevant predictive power and ease of detection.

microbiology↗