MALDI-TOF MS: a rapid microbiological confirmation technique for food and water analysis

Capocefalo, Matteo; Ridley, Emma V.; Tranfield, Erika Y.; Thompson, K. Clive

doi:10.1016/b978-0-12-416999-9.00009-5

Cited by 4 publications

(3 citation statements)

References 82 publications

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“…The samples were prepared by full protein extraction and analysed according to the Bruker Daltonics instructions. As described in previous studies (Barbuddhe et al, 2008;Hsueh et al, 2014;Capocefalo et al, 2016,), this full protein extraction 6 was crucial to obtain reliable Listeria identification to the species level (data not shown). Briefly, colonies were transferred into a 2-ml screw-cap extraction tube (Eppendorf, Germany) containing 300 μl of distilled water and then mixed with 900 μl of absolute ethanol by pipetting.…”

mentioning

confidence: 85%

MALDI-TOF mass spectrometry-based identification of Listeria species in surveillance: A prospective study

Thouvénot

Valès

Bracq-Dieye

et al. 2018

Journal of Microbiological Methods

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mentioning

confidence: 85%

MALDI-TOF mass spectrometry-based identification of Listeria species in surveillance: A prospective study

Thouvénot

Valès

Bracq-Dieye

et al. 2018

Journal of Microbiological Methods

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“…The choice to adopt an analytical strategy that combines a culture method and MALDI-ToF MS characterization contributed to minimizing Legionella related risks. In the last two decades, this protein-based recognition technique has been successfully exploited to easily and quickly identify bacteria and other microorganisms [ 62 , 63 , 64 ]: it represents a valuable alternative to the conventional phenotypic, biochemical and molecular methods, which is also thanks to its reliability and the remarkable cost-effectiveness.…”

Section: Discussionmentioning

confidence: 99%

Water Safety Plan, Monochloramine Disinfection and Extensive Environmental Sampling Effectively Control Legionella and Other Waterborne Pathogens in Nosocomial Settings: The Ten-Year Experience of an Italian Hospital

et al. 2023

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Legionella contamination control is crucial in healthcare settings where patients suffer an increased risk of disease and fatal outcome. To ensure an effective management of this health hazard, the accurate application of a hospital-specific Water Safety Plan (WSP), the choice of a suitable water disinfection system and an extensive monitoring program are required. Here, the ten-year experience of an Italian hospital is reported: since its commissioning, Legionellosis risk management has been entrusted to a multi-disciplinary Working Group, applying the principles of the World Health Organization’s WSP. The disinfection strategy to prevent Legionella and other waterborne pathogens relies on the treatment of domestic hot water with a system ensuring the in situ production and dosage of monochloramine. An average of 250 samples/year were collected and analyzed to allow an accurate assessment of the microbiological status of water network. With the aim of increasing the monitoring sensitivity, in addition to the standard culture method, an optimized MALDI-ToF MS-based strategy was applied, allowing the identification of Legionella species and other relevant opportunistic pathogens. Data collected so far confirmed the effectiveness of this multidisciplinary approach: the fraction of positive samples never overcame 1% on a yearly basis and Legionnaires’ Disease cases never occurred.

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“…Matrix-assisted laser desorption ionization mass spectrometry (MALDI-MS) has emerged as a powerful technique widely employed for microbial analysis. − It allows for the rapid and accurate identification of microorganisms based on their unique mass spectral fingerprints. In seconds, mass spectra can be acquired for bacterial or fungal colonies, providing a characteristic pattern of peaks for the classification of microbial species.…”

Section: Introductionmentioning

confidence: 99%

Machine Learning Assisted MALDI Mass Spectrometry for Rapid Antimicrobial Resistance Prediction in Clinicals

Gao,

Li,

Yang

et al. 2024

Anal. Chem.

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Antimicrobial susceptibility testing (AST) plays a critical role in assessing the resistance of individual microbial isolates and determining appropriate antimicrobial therapeutics in a timely manner. However, conventional AST normally takes up to 72 h for obtaining the results. In healthcare facilities, the global distribution of vancomycin-resistant Enterococcus fecium (VRE) infections underscores the importance of rapidly determining VRE isolates. Here, we developed an integrated antimicrobial resistance (AMR) screening strategy by combining matrix-assisted laser desorption ionization mass spectrometry (MALDI-MS) with machine learning to rapidly predict VRE from clinical samples. Over 400 VRE and vancomycin-susceptible E. faecium (VSE) isolates were analyzed using MALDI-MS at different culture times, and a comprehensive dataset comprising 2388 mass spectra was generated. Algorithms including the support vector machine (SVM), SVM with L1-norm, logistic regression, and multilayer perceptron (MLP) were utilized to train the classification model. Validation on a panel of clinical samples (external patients) resulted in a prediction accuracy of 78.07%, 80.26%, 78.95%, and 80.54% for each algorithm, respectively, all with an AUROC above 0.80. Furthermore, a total of 33 mass regions were recognized as influential features and elucidated, contributing to the differences between VRE and VSE through the Shapley value and accuracy, while tandem mass spectrometry was employed to identify the specific peaks among them. Certain ribosomal proteins, such as A0A133N352 and R2Q455, were tentatively identified. Overall, the integration of machine learning with MALDI-MS has enabled the rapid determination of bacterial antibiotic resistance, greatly expediting the usage of appropriate antibiotics.

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MALDI-TOF MS: a rapid microbiological confirmation technique for food and water analysis

Cited by 4 publications

References 82 publications

MALDI-TOF mass spectrometry-based identification of Listeria species in surveillance: A prospective study

MALDI-TOF mass spectrometry-based identification of Listeria species in surveillance: A prospective study

Water Safety Plan, Monochloramine Disinfection and Extensive Environmental Sampling Effectively Control Legionella and Other Waterborne Pathogens in Nosocomial Settings: The Ten-Year Experience of an Italian Hospital

Machine Learning Assisted MALDI Mass Spectrometry for Rapid Antimicrobial Resistance Prediction in Clinicals

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