Identification of pathogenic and nonpathogenic Leptospira species of Brazilian isolates by Matrix Assisted Laser Desorption/Ionization and Time Flight mass spectrometry

Karcher, Daniel; Grenfell, Rafaella C.; Moreno, Andréa Micke; Moreno, Luisa Zanolli; Vasconcellos, Sílvio Arruda; Heinemann, Marcos Bryan; Almeida, João Nóbrega de; Juliano, Luiz; Juliano, María A.

doi:10.1016/j.bjm.2018.03.005

Cited by 2 publications

(3 citation statements)

References 16 publications

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“…To identify all the clinical isolates to species level, we would need to create a better library with a larger number of reference strains. Other authors have also described MALDI-TOF MS for the identification of Leptospira, and it is possible to extend this method with ClinPro Tools software version 3.0 to allow for the identification of Leptospira up to the serovar level [14][15][16][17]. This method could be useful in the future to identify Leptospira protein profiles and analyze possible relationships with virulence factors.…”

Section: Discussionmentioning

confidence: 99%

“…The results were displayed numerically (scores) and interpreted according to the level of identification reliability suggested by the manufacturer (scores >2 indicate identification of the species; scores between 1.7 and 1.9 indicate identification of the genus; and scores <1.7 indicate no identification). The mass spectra of both reference strains and clinical isolates were imported into BioNumerics 7.1 software, and a phylogenetic tree was drawn using the UPGMA method [14][15][16][17].…”

Section: Leptospira Identification Using Maldi-tof Msmentioning

confidence: 99%

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First Report on Leptospira Species Isolated from Patients in Slovenia

Ružić-Sabljić,

Podgoršek,

Strašek Smrdel

et al. 2023

Microorganisms

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Leptospirosis is an important worldwide zoonosis, and it has also been reported in Slovenia. The cultivation of Leptospira from human material is difficult. Despite that, we successfully isolated 12 human Leptospira strains isolated from patients between 2002 and 2020 and used various methods for the phenotypic and genotypic characterization of the strains, including matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF) using our own MALDI-TOF data library, melting temperature analysis of the amplified lfb1 gene, determination of Leptospira serogroups using rabbit immune sera, NotI-RFLP of the whole Leptospira genome, multilocus sequence typing (MLST) of seven housekeeping genes, and whole-genome sequencing (WGS)-based typing. We confirmed the presence of four pathogenic Leptospira species (L. kirschneri, L. interrogans, L. borgpetersenii, and L. santarosai) and three serogroups: Grippotyphosa, Icterohaemorrhagiae, and Sejroe. MALDI-TOF identified three of seven isolates at the species level and four isolates at the genus level. Serovars of 8 of the 10 strains were determined using NotI-RFLP. MLST showed that the clinical isolates belonged to sequence types ST17, ST110, and ST155. WGS confirmed the analysis of Leptospira strains using conventional methods. In addition, WGS provided better taxonomic resolution for isolate DDA 10944/10.

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Section: Discussionmentioning

confidence: 99%

Section: Leptospira Identification Using Maldi-tof Msmentioning

confidence: 99%

First Report on Leptospira Species Isolated from Patients in Slovenia

Ružić-Sabljić,

Podgoršek,

Strašek Smrdel

et al. 2023

Microorganisms

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show abstract

“…The data preprocessing steps, including baseline correction, smoothing and recalibration, were performed according to the literature [24][25][26]. For the baseline correction, a polynomial function fitted to a subsection of the baseline was used.…”

Section: Maldi-tof Ms Data Analysismentioning

confidence: 99%

Rapid and accurate detection of Shiga toxin-producing Escherichia coli (STEC) serotype O157 : H7 by mass spectrometry directly from the isolate, using 10 potential biomarker peaks and machine learning predictive models

Manfredi

Rocca

Zintgraff

et al. 2023

Journal of Medical Microbiology

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Introduction. The different pathotypes of Escherichia coli can produce a large number of human diseases. Surveillance is complex since their differentiation is not easy. In particular, the detection of Shiga toxin-producing Escherichia coli (STEC) serotype O157 : H7 consists of stool culture of a diarrhoeal sample on enriched and/or selective media and identification of presumptive colonies and confirmation, which require a certain level of training and are time-consuming and expensive. Hypothesis. Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) is a quick and easy way to obtain the protein spectrum of a microorganism, identify the genus and species, and detect potential biomarker peaks of certain characteristics. Aim. To verify the usefulness of MALDI-TOF MS to rapidly identify and differentiate STEC O157 : H7 from other E. coli pathotypes. Methodology. The direct method was employed, and the information obtained using Microflex LT platform-based analysis from 60 clinical isolates (training set) was used to detect differences between the peptide fingerprints of STEC O157 : H7 and other E. coli strains. The protein profiles detected laid the foundations for the development and evaluation of machine learning predictive models in this study. Results. The detection of potential biomarkers in combination with machine learning predictive models in a new set of 142 samples, called ‘test set‘, achieved 99.3 % (141/142) correct classification, allowing us to distinguish between the isolates of STEC O157 : H7 and the other E. coli group. Great similarity was also observed with respect to this last group and the Shigella species when applying the potential biomarkers algorithm, allowing differentiation from STEC O157 : H7 Conclusion. Given that STEC O157 : H7 is the main causal agent of haemolytic uremic syndrome, and based on the performance values obtained in the present study (sensitivity=98.5 % and specificity=100.0 %), the implementation of this technique provides a proof of principle for MALDI-TOF MS and machine learning to identify biomarkers to rapidly screen or confirm STEC O157 : H7 versus other diarrhoeagenic E. coli in the future.

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Identification of pathogenic and nonpathogenic Leptospira species of Brazilian isolates by Matrix Assisted Laser Desorption/Ionization and Time Flight mass spectrometry

Cited by 2 publications

References 16 publications

First Report on Leptospira Species Isolated from Patients in Slovenia

First Report on Leptospira Species Isolated from Patients in Slovenia

Rapid and accurate detection of Shiga toxin-producing Escherichia coli (STEC) serotype O157 : H7 by mass spectrometry directly from the isolate, using 10 potential biomarker peaks and machine learning predictive models

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