Principal Component Analysis (PCA) of MALDI-TOF for the Identification of Waterborne Pathogenic Bacteria
Tetty Aya Marie Pascale, Yao Djeha Rosine, Vakou N’dri Sabine, Yao Kouamé Eric, Coulibaly Kalpy Julien
Microbiology Research Journal International · pp. 1–16 · Published 21 Oct 2024
10.9734/mrji/2024/v34i111494Abstract
The study focuses on the application of Principal Component Analysis (PCA) combined with MALDI-TOF MS (Matrix-Assisted Laser Desorption/Ionization-Time of Flight Mass Spectrometry) for the identification of waterborne pathogenic bacteria in urban water networks. In this comprehensive research, 168 bacterial strains were meticulously isolated from the water networks of Abidjan, Côte d'Ivoire, a region known for its inadequate wastewater treatment infrastructure. The analysis aimed to rapidly and precisely identify these bacterial pathogens, leveraging the power of MALDI-TOF MS and the sophisticated data reduction capabilities of PCA. This approach not only accelerates the identification process but also enhances the accuracy of detecting various pathogens. The study identified a diverse range of pathogens, including Pseudomonas aeruginosa, Escherichia coli, Salmonella, Shigella, Vibrio cholerae, Morganella morganii, Proteus mirabilis, Acinetobacter baumannii, Klebsiella pneumoniae, Providencia rettgeri, Providencia stuartii, Aeromonas hydrophila, Bacillus cereus, Lysinibacillus fusiformis, Lysinibacillus sphaericus, and Staphylococcus aureus. These findings underscore the critical public health risks posed by microbial contamination in water networks, particularly in areas with deficient waste management systems. This study highlights the necessity for improved wastewater management practices, robust public health strategies, and regular monitoring to mitigate the risks associated with waterborne pathogens. Moreover, the integration of PCA with MALDI-TOF MS proves to be a powerful tool for enhancing the efficiency and accuracy of pathogen identification in environmental water samples, offering a promising solution for better public health protection and water quality management in urban settings.
Cited by 2
M. Alkaabi, Nabil Zouari, M. Ashfaq · Biotechnology Letters · 2025
Pankaj Bhatt, Ya-Bing Li, John W. Norton · Water Research · 2025
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