Rapid detection of antibiotic resistance in positive blood cultures by MALDI-TOF MS and an automated and optimized MBT-ASTRA protocol for Escherichia coli and Klebsiella pneumoniae

Carolina Axelsson, Ann Sofi Rehnstam-Holm, Bo Nilson

Forskningsoutput: TidskriftsbidragArtikel i vetenskaplig tidskriftPeer review

Sammanfattning

Introduction: For fast and effective antibiotic therapy of serious infections like sepsis, it is crucial with rapid information about antibiotic susceptibility, especially in a time when the number of infections caused by multi resistant bacteria has escalated in the world. Methods: Here, we have used a semi-quantitative MALDI-TOF-MS based method for antibiotic resistance detection, MBT-ASTRA™, which is based on the comparison of growth rate of the bacteria cultivated with and without antibiotics. We demonstrate a new protocol where several parameters have been optimized and automated leading to reduced hands-on time and improved capacity to simultaneously analyse multiple clinical samples and antibiotics. Results: Ninety minutes of incubation at 37 °C with agitation was sufficient to differentiate the susceptible and resistant strains of E. coli and K. pneumoniae, for the antibiotics cefotaxime, meropenem and ciprofloxacin. In total, 841 positive blood culture analyses of 14 reference strains were performed. The overall sensitivity was 99%, specificity 99% and the accuracy 97%. The assay gave no errors for cefotaxime (n = 263) or meropenem (n = 289) for sensitive and resistant strains, whilst ciprofloxacin (n = 289) gave six (0.7%) major errors (false resistance) and four (0.5%) very major errors (false susceptibility). The intermediate strains showed a larger variety compared to the E-test MIC values. Conclusions: The hands-on time and the analysis time to detect antibiotic resistance of clinical blood samples can be substantially reduced and the sample capacity can be increased by using automation and this improved protocol.

Originalspråkengelska
Sidor (från-till)45-53
Antal sidor9
TidskriftInfectious Diseases
Volym52
Nummer1
Tidigt onlinedatum2019 okt. 29
DOI
StatusPublished - 2020 jan.

Ämnesklassifikation (UKÄ)

  • Mikrobiologi inom det medicinska området
  • Infektionsmedicin

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