Dataset Information

Molecular phylogenetic and matrix-assisted laser desorption ionization time-of-flight mass spectrometry identification of isolates from horses identified as Enterobacter cloacae by biochemical identification.

ABSTRACT: Enterobacter cloacae is an opportunistic pathogen of horses. Thirty isolates obtained from horses and their environments and identified as Enterobacter cloacae by biochemical methods were reidentified by taxonomic identification based on multilocus sequence analysis (MLSA) and by a commercial identification system based on matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS). MLSA identified the 30 equine isolates as E. ludwigii (9/30), E. asburiae (1/30), or E. cloacae (1/30); 19 isolates were not identified. The MALDI-TOF MS system could not clearly distinguish isolates to the species level, and the limited numbers of reference spectra for Enterobacter species might have contributed to the poor identification.

SUBMITTER: Uchida-Fujii E

PROVIDER: S-EPMC7538261 | biostudies-literature | 2020 Oct

REPOSITORIES: biostudies-literature

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Molecular phylogenetic and matrix-assisted laser desorption ionization time-of-flight mass spectrometry identification of isolates from horses identified as <i>Enterobacter cloacae</i> by biochemical identification.

Uchida-Fujii Eri E Niwa Hidekazu H Kinoshita Yuta Y Katayama Yoshinari Y Nukada Toshio T

Journal of equine science 20201005 3

Enterobacter cloacae is an opportunistic pathogen of horses. Thirty isolates obtained from horses and their environments and identified as Enterobacter cloacae by biochemical methods were reidentified by taxonomic identification based on multilocus sequence analysis (MLSA) and by a commercial identification system based on matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS). MLSA identified the 30 equine isolates as E. ludwigii (9/30), E. asburiae (1/30), ...[more]

PMID: 33061784

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Project description:Matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) is commonly used by clinical microbiology laboratories to identify pathogens, despite some limitations of the technique. The Enterobacter cloacae complex (ECC) taxonomy has recently been expanded, leading to uncertain identification of some species within the ECC when commercial MALDI-TOF MS is used. This technique is especially unsuited in the case of E. hormaechei, the main species responsible for infections and one of the most prone, within the ECC, to acquire antibiotic resistance. Hence, rapid and reliable identification at the species level could improve patient management. Here, we evaluated the performance of the Bruker Microflex MALDI-TOF MS instrument to identify ECC isolates using two databases and algorithms in comparison to the hsp60 gene sequencing reference method: the Bruker database included in the MALDI Biotyper software and an extensive online database coupled to an original Mass Spectrometric Identification (MSI) algorithm. Among a panel of 94 ECC isolates tested in triplicate, the online database coupled to MSI software allowed the highest rate of identification at the species level (92%) compared to the MALDI Biotyper database (25%), especially for the species E. hormaechei (97% versus 20%). We show that by creating a database of MALDI-TOF reference spectral profiles with a high number of representatives associated with the performant MSI software, we were able to substantially improve the identification of the E. cloacae complex members, with only 8% of isolates misidentified at the species level. This online database is available through a free online MSI application (https://msi.happy-dev.fr/). IMPORTANCE Creation of a database of MALDI-TOF reference spectral profiles with a high number of representatives associated with the performant MSI software enables substantial improvement in identification of E. cloacae complex members. Moreover, this online database is available through a free online MSI application (https://msi.happy-dev.fr/).

Project description:BackgroundSchistosomiasis is a major neglected tropical disease that affects up to 250 million individuals worldwide. The diagnosis of human schistosomiasis is mainly based on the microscopic detection of the parasite's eggs in the feces (i.e., for Schistosoma mansoni or Schistosoma japonicum) or urine (i.e., for Schistosoma haematobium) samples. However, these techniques have limited sensitivity, and microscopic expertise is waning outside endemic areas. Matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) mass spectrometry (MS) has become the gold standard diagnostic method for the identification of bacteria and fungi in many microbiological laboratories. Preliminary studies have recently shown promising results for parasite identification using this method. The aims of this study were to develop and validate a species-specific database for adult Schistosoma identification, and to evaluate the effects of different storage solutions (ethanol and RNAlater) on spectra profiles.MethodsAdult worms (males and females) of S. mansoni and S. japonicum were obtained from experimentally infected mice. Species identification was carried out morphologically and by cytochrome oxidase 1 gene sequencing. Reference protein spectra for the creation of an in-house MALDI-TOF MS database were generated, and the database evaluated using new samples. We employed unsupervised (principal component analysis) and supervised (support vector machine, k-nearest neighbor, Random Forest, and partial least squares discriminant analysis) machine learning algorithms for the identification and differentiation of the Schistosoma species.ResultsAll the spectra were correctly identified by internal validation. For external validation, 58 new Schistosoma samples were analyzed, of which 100% (58/58) were correctly identified to genus level (log score values ≥ 1.7) and 81% (47/58) were reliably identified to species level (log score values ≥ 2). The spectra profiles showed some differences depending on the storage solution used. All the machine learning algorithms classified the samples correctly.ConclusionsMALDI-TOF MS can reliably distinguish adult S. mansoni from S. japonicum.

Dataset Information

Molecular phylogenetic and matrix-assisted laser desorption ionization time-of-flight mass spectrometry identification of isolates from horses identified as Enterobacter cloacae by biochemical identification.

Publications

Molecular phylogenetic and matrix-assisted laser desorption ionization time-of-flight mass spectrometry identification of isolates from horses identified as <i>Enterobacter cloacae</i> by biochemical identification.

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