Validation of MALDI-TOF for the early detection of the ST175 high-risk clone of Pseudomonas aeruginosa in clinical isolates belonging to a Spanish nationwide multicenter study

Mulet, Xavier; Fernández-Esgueva, Marta; Norte, Cristina; Zamorano, Laura; Barrio-Tofiño, Ester del; Oliver, Antonio

doi:10.1016/j.eimce.2020.05.015

Cited by 3 publications

(2 citation statements)

References 13 publications

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“…Cabrolier et al described a specific peak at 7359 m/z that, combined with the absence of peaks at 7329 and 12154 m/z were specific of P. aeruginosa ST175 (Cabrolier et al, 2015). These results were further confirmed by Mulet et al, who also found the peak at 7359 m/z as a biomarker for P. aeruginosa ST175 and described another peak at 6911 m/z as specific for this ST (Mulet et al, 2021). In the present study, a peak at 6915 m/z has been described as a biomarker of the P. aeruginosa outbreak strains belonging to the same sequence type.…”

Section: Discussionmentioning

confidence: 77%

Rapid discrimination of Pseudomonas aeruginosa ST175 isolates involved in a nosocomial outbreak using MALDI-TOF Mass Spectrometry and FTIR Spectroscopy coupled with Machine Learning

Rodríguez‐Sánchez

Candela

Arroyo

et al. 2022

Preprint

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Objectives: Evaluation of Matrix-Assisted Laser Desorption Ionization-Time of Flight Mass Spectrometry (MALDI-TOF MS) and Fourier Transform Infrared-Spectroscopy (FTIR-S) as diagnostic alternatives to DNA-based methods for the detection of Pseudomonas aeruginosa sequence type (ST) 175 isolates involved in a hospital outbreak. Methods: Twenty-seven P. aeruginosa isolates from a 2014 outbreak in the Hematology department of our hospital were previously characterized by PFGE and WGS. Besides, 8 P. aeruginosa isolates were analyzed as unrelated controls. MALDI-TOF MS spectra were acquired by applying the colony on the MALDI target plate followed by 1 µl of formic acid 100% and 1 µl of HCCA matrix. For the analysis with FTIR-S, colonies were resuspended in 70% ethanol and sterile water according to the manufacturer instructions. Spectra from both methodologies were analyzed using Clover Biosoft® software, that allowed data modelling using different algorithms and validation of the classifying models. Results: Three outbreak-specific biomarkers were found at 5169, 6915 and 7236 m/z in MALDI-TOF MS spectra. Classification models based on these three biomarkers showed the same discrimination power displayed by PFGE. Besides, K-Nearest Neighbor algorithm allowed the discrimination of the same clusters provided by whole-genome sequencing and the validation of this model achieved 97.0% correct classification. On the other hand, FTIR-S showed a discrimination power similar to PFGE and reached correct discrimination of the different STs analyzed. Conclusions: The combination of both technologies evaluated, paired with Machine Learning tools, may represent a powerful tool for real-time monitoring of high-risk clones and isolates involved in nosocomial outbreaks.

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Section: Discussionmentioning

confidence: 77%

Rapid discrimination of Pseudomonas aeruginosa ST175 isolates involved in a nosocomial outbreak using MALDI-TOF Mass Spectrometry and FTIR Spectroscopy coupled with Machine Learning

Rodríguez‐Sánchez

Candela

Arroyo

et al. 2022

Preprint

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“…There are no officially/internationally recognised diagnostic tests. MALDI-TOF MS has been used to identify high-risk clones of P. aeruginosa with a sensitivity and specificity of 97.1% and 99.4%, respectively (Mulet et al, 2021). Culture using Pseudomonas-selective media has shown a high sensitivity (98-100%) but low specificity ranging between 40% and 72% (Weiser et al, 2014).…”

Section: Effectiveness Parameter 2 -Sensitivity and Specificity Of Di...mentioning

confidence: 99%

Assessment of listing and categorisation of animal diseases within the framework of the Animal Health Law (Regulation (EU) No 2016/429): antimicrobial‐resistant Pseudomonas aeruginosa in dogs and cats

Nielsen¹,

Bicout²,

Calistri³

et al. 2022

EFS2

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Pseudomonas aeruginosa (P. aeruginosa) was identified among the most relevant antimicrobial‐resistant (AMR) bacteria in the EU for dogs and cats in a previous scientific opinion. Thus, it has been assessed according to the criteria of the Animal Health Law (AHL), in particular criteria of Article 7 on disease profile and impacts, Article 5 on its eligibility to be listed, Annex IV for its categorisation according to disease prevention and control rules as in Article 9, and Article 8 for listing animal species related to the bacterium. The assessment has been performed following a methodology previously published. The outcome is the median of the probability ranges provided by the experts, which indicates whether each criterion is fulfilled (lower bound ≥ 66%) or not (upper bound ≤ 33%), or whether there is uncertainty about fulfilment. Reasoning points are reported for criteria with uncertain outcome. According to the assessment here performed, it is uncertain whether AMR P. aeruginosa can be considered eligible to be listed for Union intervention according to Article 5 of the AHL (33–90% probability). According to the criteria in Annex IV, for the purpose of categorisation related to the level of prevention and control as in Article 9 of the AHL, the AHAW Panel concluded that the bacterium does not meet the criteria in Sections 1, 2, 3 and 4 (Categories A, B, C and D; 0–5%, 1–5%, 5–33% and 5–33% probability of meeting the criteria, respectively) and the AHAW Panel was uncertain whether it meets the criteria in Section 5 (Category E, 33–90% probability of meeting the criteria). The animal species to be listed for AMR P. aeruginosa according to Article 8 criteria are mainly dogs and cats.

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Rapid Discrimination of Pseudomonas aeruginosa ST175 Isolates Involved in a Nosocomial Outbreak Using MALDI-TOF Mass Spectrometry and FTIR Spectroscopy Coupled with Machine Learning

Candela,

Arroyo,

Sánchez-Cueto

et al. 2023

Transboundary and Emerging Diseases

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The goal of this study was to evaluate matrix-assisted laser desorption ionization–iime of flight mass spectrometry (MALDI-TOF MS) and Fourier-transform infrared spectroscopy (FTIR-S) as diagnostic alternatives to DNA-based methods for the detection of Pseudomonas aeruginosa sequence type (ST) 175 isolates involved in a hospital outbreak. For this purpose, 27 P. aeruginosa isolates from an outbreak detected in the Hematology department of our hospital were analyzed by the above-mentioned methodologies. Previously, these isolates had been characterized by pulse-field gel electrophoresis (PFGE) and whole-genome sequencing (WGS). Besides, eight P. aeruginosa isolates were analyzed as unrelated controls. MALDI-TOF MS spectra were acquired by transferring several colonies onto the MALDI target and covering them with 1 µl of formic acid 100% and 1 µl of α-ciano-3,4-hidroxicinamic acid matrix. For the analysis with FTIR-S, colonies were resuspended in 70% ethanol and sterile water according to the manufacturer’s instructions. Spectra from both methodologies were analyzed using Clover Biosoft Software, which allowed data modeling using different algorithms and validation of the classifying models. Three outbreak-specific biomarkers were found at 5,169, 6,915, and 7,236 m/z in MALDI-TOF MS spectra. Classification models based on these three biomarkers showed the same discrimination power displayed by PFGE. Besides, K-nearest neighbor algorithm allowed the discrimination of the same clusters provided by WGS and the validation of this model achieved 97.0% correct classification. On the other hand, FTIR-S showed a discrimination power similar to PFGE and reached correct discrimination of the different STs analyzed. In conclusion, the combination of both technologies evaluated, paired with machine learning tools, may represent a powerful tool for real-time monitoring of high-risk clones and isolates involved in nosocomial outbreaks.

show abstract

Validation of MALDI-TOF for the early detection of the ST175 high-risk clone of Pseudomonas aeruginosa in clinical isolates belonging to a Spanish nationwide multicenter study

Cited by 3 publications

References 13 publications

Rapid discrimination of Pseudomonas aeruginosa ST175 isolates involved in a nosocomial outbreak using MALDI-TOF Mass Spectrometry and FTIR Spectroscopy coupled with Machine Learning

Rapid discrimination of Pseudomonas aeruginosa ST175 isolates involved in a nosocomial outbreak using MALDI-TOF Mass Spectrometry and FTIR Spectroscopy coupled with Machine Learning

Assessment of listing and categorisation of animal diseases within the framework of the Animal Health Law (Regulation (EU) No 2016/429): antimicrobial‐resistant Pseudomonas aeruginosa in dogs and cats

Rapid Discrimination of Pseudomonas aeruginosa ST175 Isolates Involved in a Nosocomial Outbreak Using MALDI-TOF Mass Spectrometry and FTIR Spectroscopy Coupled with Machine Learning

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