Diagnostics, Typing And Identification

MALDI-TOF: A useful tool for laboratory identification of uncommon glucose non-fermenting Gram-negative bacteria associated with cystic fibrosis

  • 1Bacteriology Section, Hospital de Clínicas – Universidade Federal do Paraná (UFPR), Curitiba, PR, Brazil
  • 2Pele Pequeno Príncipe Research Institute, Faculdades Pequeno Príncipe, Curitiba, PR, Brazil
  • 3Immunochemistry Section, Laboratório Municipal de Curitiba, Curitiba, PR, Brazil
  • 4Department of Pediatrics – Universidade Federal do Paraná (UFPR), Curitiba, PR, Brazil
  • 5Department of Microbiology, School of Health and Biosciences, Pontifícia Universidade Católica do Paraná (PUC), Curitiba, PR, Brazil
  • 6Molecular Bacteriology Section, Laboratório Central de Saúde Pública do Estado LACEN-PR, Curitiba, PR, Brazil
  • Correspondence
    Libera Maria Dalla-Costa lmdc{at}ufpr.br
  • Journal of Medical Microbiology 2014; 63(Pt 9):1148–1153 · https://doi.org/10.1099/jmm.0.076869-0

    View at publisher PubMed

    Abstract

    The predisposition of patients with cystic fibrosis (CF) for recurrent pulmonary infections can result in poor prognosis of the disease. Although the clinical significance in CF of micro-organisms, such as Staphylococcus aureus, Haemophilus influenzae and Pseudomonas aeruginosa, is well established, the implication of uncommon glucose non-fermenting Gram-negative bacilli (UGNF-GNB) in respiratory samples from CF patients is still unclear. Because of limitations of traditional methods used in most clinical laboratories, the accurate identification of these microbes is a challenge. Matrix-assisted laser desorption ionization-time of flight (MALDI-TOF) is an alternative tool for efficient identification of bacteria. This was a retrospective study to evaluate different identification methods in a collection of UGNF-GNB isolated from children with CF during a period of three years. The performance of MALDI-TOF was compared to that of 16S rDNA gene sequencing and to a conventional and automated phenotypic identification. The discriminatory power of MALDI-TOF (75.0 % agreement) was superior to automated techniques (67.1 % agreement) and to conventional phenotypical identification (50.0 % agreement). MALDI-TOF also demonstrated high accuracy in identifying Stenotrophomonas maltophilia, Achromobacter xylosoxidans and Chryseobacterium indologenes, but had limited utility in identifying Pandoraea spp. and some species of Acinetobacter and Chryseobacterium (other than C. indologenes). Although MALDI-TOF identified only 75 % of the isolates in comparison with 16S rDNA gene sequencing, the prompt identification and high discriminatory power exhibited by MALDI-TOF make it a useful tool for the characterization of micro-organisms that are difficult to identify using routine methods.

    Abbreviations:
    APID
    automated phenotypic identification
    BCC
    Burkholderia cepacia complex
    CF
    cystic fibrosis
    CPID
    conventional phenotypic identification
    GNF-GNB
    glucose non-fermenting Gram-negative bacilli
    MALDI-TOF
    matrix-assisted laser desorption ionization-time of flight
    UGNF-GNB
    uncommon glucose non-fermenting Gram-negative bacilli