Application of miniaturized most probable number method for bacterial detection in water samples: detection of multi-drug-resistant <i>Ralstonia insidiosa</i> in drinking water

The detection of bacterial contamination in drinking water is essential for monitoring the spread of foodborne diseases. We developed a simple, portable, and low-cost method of mini most probable number (mini MPN) to semi-enumerate bacterial suspension in water as a drinking water analogue. In this study, there is no significant difference between mini MPN and the standard method, technique plate count (TPC), at 10 and 100 CFU/ml <i>Klebsiella pneumoniae</i> suspension with a <i>P</i>-value of 0.28. For the ease-of-use aspect of this method, we tested several variables to prove it can be mass-applied in society. The usage of a sterile-plastic pipette, sample inoculation conducted in a biosafety cabinet (BSC), the usage of a 3-month storage medium, and incubation temperature conducted at room temperature compared to aseptic standard laboratory technique showed <i>P</i>-value > 0.05. In a trial for this method, we used commercialized drinking water for bacterial enumeration and characterization. We found multi-drug resistant (MDR) <i>Ralstonia insidiosa</i> which was resistant to at least four antimicrobial classes, including aminoglycosides, penicillins, cephalosporin, and carbapenem. Vitek 2 Compact was used for bacterial identification and antimicrobial susceptibility testing. A virulence test in <i>Omphisa fuscidentalis</i> larvae showed <i>R. insidiosa</i> strain D had a low virulence.

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Journal
Journal of Water and Health
Published
2024-08-16
DOI
https://doi.org/10.2166/wh.2024.086
Citations
1
Primary Topic
Mycobacterium research and diagnosis
Type
article
Field-Weighted Citation Impact
0.39

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article

Application of miniaturized most probable number method for bacterial detection in water samples: detection of multi-drug-resistant Ralstonia insidiosa in drinking water

Maulin Inggraini, Reza Anindita, Ni Putu Ratna Ayu Krishanti, Melda Yunita et al.
1 citations
Journal of Water and Health
Mycobacterium research and diagnosis
0.39
article

Application of miniaturized most probable number method for bacterial detection in water samples: detection of multi-drug-resistant Ralstonia insidiosa in drinking water

Maulin Inggraini, Reza Anindita, Ni Putu Ratna Ayu Krishanti, Melda Yunita, Sipriyadi Sipriyadi, Tzu‐Wen Huang, Siti Nurfajriah, Noor Andryan Ilsan
article en
1 citations

Abstract

The detection of bacterial contamination in drinking water is essential for monitoring the spread of foodborne diseases. We developed a simple, portable, and low-cost method of mini most probable number (mini MPN) to semi-enumerate bacterial suspension in water as a drinking water analogue. In this study, there is no significant difference between mini MPN and the standard method, technique plate count (TPC), at 10 and 100 CFU/ml <i>Klebsiella pneumoniae</i> suspension with a <i>P</i>-value of 0.28. For the ease-of-use aspect of this method, we tested several variables to prove it can be mass-applied in society. The usage of a sterile-plastic pipette, sample inoculation conducted in a biosafety cabinet (BSC), the usage of a 3-month storage medium, and incubation temperature conducted at room temperature compared to aseptic standard laboratory technique showed <i>P</i>-value > 0.05. In a trial for this method, we used commercialized drinking water for bacterial enumeration and characterization. We found multi-drug resistant (MDR) <i>Ralstonia insidiosa</i> which was resistant to at least four antimicrobial classes, including aminoglycosides, penicillins, cephalosporin, and carbapenem. Vitek 2 Compact was used for bacterial identification and antimicrobial susceptibility testing. A virulence test in <i>Omphisa fuscidentalis</i> larvae showed <i>R. insidiosa</i> strain D had a low virulence.

Journal of Water and HealthVol. 22(9)
University of Pattimura (ID), National Research and Innovation Agency (ID), Taipei Medical University (TW), University of Bengkulu (ID)
Badan Riset dan Inovasi Nasional
Clean water and sanitation
Openalex Percentile: Top 35%
Mycobacterium research and diagnosis
0.39
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