Materials Map

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The Materials Map is an open tool for improving networking and interdisciplinary exchange within materials research. It enables cross-database search for cooperation and network partners and discovering of the research landscape.

The dashboard provides detailed information about the selected scientist, e.g. publications. The dashboard can be filtered and shows the relationship to co-authors in different diagrams. In addition, a link is provided to find contact information.

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The Materials Map is still under development. In its current state, it is only based on one single data source and, thus, incomplete and contains duplicates. We are working on incorporating new open data sources like ORCID to improve the quality and the timeliness of our data. We will update Materials Map as soon as possible and kindly ask for your patience.

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in Cooperation with on an Cooperation-Score of 37%

Topics

Publications (1/1 displayed)

  • 2024Rapid nanopore sequencing and predictive susceptibility testing of positive blood cultures from intensive care patients with sepsis16citations

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Chart of shared publication
Shekar, Kiran
1 / 1 shared
Schlapbach, Luregn
1 / 1 shared
Balch, Ross
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Beisken, Stephan
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Paterson, David L.
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Lüftinger, Lukas
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Bialasiewicz, Seweryn
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Raman, Sainath
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2024

Co-Authors (by relevance)

  • Shekar, Kiran
  • Schlapbach, Luregn
  • Balch, Ross
  • Beisken, Stephan
  • Paterson, David L.
  • Lüftinger, Lukas
  • Irwin, Adam D.
  • Lipman, Jeff
  • Coin, Lachlan
  • Forde, Brian
  • Roberts, Jason
  • Bialasiewicz, Seweryn
  • Raman, Sainath
  • Kruger, Peter
OrganizationsLocationPeople

article

Rapid nanopore sequencing and predictive susceptibility testing of positive blood cultures from intensive care patients with sepsis

  • Shekar, Kiran
  • Schlapbach, Luregn
  • Balch, Ross
  • Beisken, Stephan
  • Paterson, David L.
  • Lüftinger, Lukas
  • Bauer, Michelle J.
  • Irwin, Adam D.
  • Lipman, Jeff
  • Coin, Lachlan
  • Forde, Brian
  • Roberts, Jason
  • Bialasiewicz, Seweryn
  • Raman, Sainath
  • Kruger, Peter
Abstract

<jats:title>ABSTRACT</jats:title><jats:p>We aimed to evaluate the performance of Oxford Nanopore Technologies (ONT) sequencing from positive blood culture (BC) broths for bacterial identification and antimicrobial susceptibility prediction. Patients with suspected sepsis in four intensive care units were prospectively enrolled. Human-depleted DNA was extracted from positive BC broths and sequenced using ONT (MinION). Species abundance was estimated using Kraken2, and a cloud-based system (AREScloud) provided<jats:italic>in silico</jats:italic>predictive antimicrobial susceptibility testing (AST) from assembled contigs. Results were compared to conventional identification and phenotypic AST. Species-level agreement between conventional methods and AST predicted from sequencing was 94.2% (49/52), increasing to 100% in monomicrobial infections. In 262 high-quality AREScloud AST predictions across 24 samples, categorical agreement (CA) was 89.3%, with major error (ME) and very major error (VME) rates of 10.5% and 12.1%, respectively. Over 90% CA was achieved for some taxa (e.g.,<jats:italic>Staphylococcus aureus</jats:italic>) but was suboptimal for<jats:italic>Pseudomonas aeruginosa</jats:italic>. In 470 AST predictions across 42 samples, with both high quality and exploratory-only predictions, overall CA, ME, and VME rates were 87.7%, 8.3%, and 28.4%. VME rates were inflated by false susceptibility calls in a small number of species/antibiotic combinations with few representative resistant isolates. Time to reporting from sequencing could be achieved within 8–16 h from BC positivity. Direct sequencing from positive BC broths is feasible and can provide accurate predictive AST for some species. ONT-based approaches may be faster but significant improvements in accuracy are required before it can be considered for clinical use.</jats:p><jats:sec><jats:title>IMPORTANCE</jats:title><jats:p>Sepsis and bloodstream infections carry a high risk of morbidity and mortality. Rapid identification and susceptibility prediction of causative pathogens, using Nanopore sequencing direct from blood cultures, may offer clinical benefit. We assessed this approach in comparison to conventional phenotypic methods and determined the accuracy of species identification and susceptibility prediction from genomic data. While this workflow holds promise, and performed well for some common bacterial species, improvements in sequencing accuracy and more robust predictive algorithms across a diverse range of organisms are required before this can be considered for clinical use. However, results could be achieved in timeframes that are faster than conventional phenotypic methods.</jats:p></jats:sec>

Topics
  • impedance spectroscopy
  • size-exclusion chromatography
  • susceptibility