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Waterborne pathogens detection technologies: advances, challenges, and future perspectives.

Yoong-Ling Oon1,2, Yoong-Sin Oon1,2, Muhammad Ayaz2,3,4

  • 1Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou), Guangzhou, China.

Frontiers in Microbiology
|December 11, 2023
PubMed
Summary

Waterborne pathogens cause 485,000 annual deaths and $12 billion in losses. This review covers detection technologies from traditional methods to advanced biosensors and AI, highlighting their pros, cons, and future directions for water safety.

Keywords:
LAMPNGSPCRartificial intelligencebiosensornucleic acid amplificationpathogen detection techniquewater microbiology

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Area of Science:

  • Environmental Microbiology
  • Public Health
  • Analytical Chemistry

Background:

  • Waterborne pathogens, such as Escherichia coli, cause significant global mortality (485,000 deaths annually) and economic losses (nearly $12 billion USD per annum) due to diarrheal diseases.
  • International organizations like the WHO and UNICEF emphasize the need for efficient and innovative pathogenic detection technologies to ensure water safety.
  • Traditional culture-based methods for pathogen detection are time-consuming and may lack sensitivity for early-stage contamination.

Purpose of the Study:

  • To comprehensively review and critically analyze the evolution of waterborne pathogenic bacteria detection technologies.
  • To evaluate the merits, constraints, research gaps, and future perspectives of various detection techniques, including traditional, current, and emerging methods.
  • To provide insights into the applicability of these techniques for field settings and timely water quality monitoring.

Main Methods:

  • Review of traditional culture-based methods.
  • Analysis of current molecular techniques, including qualitative real-time PCR, digital PCR, ELISA, loop-mediated isothermal amplification, and next-generation sequencing (NGS).
  • Examination of emerging techniques such as biosensors and artificial intelligence (AI) integration.

Main Results:

  • Advancements in digital droplet PCR, NGS, and biosensors have significantly enhanced the sensitivity and specificity of pathogen detection.
  • The integration of AI with detection technologies improves accuracy and enables real-time analysis of large datasets.
  • Molecular methods and biosensors show promise for water quality monitoring, especially in resource-limited areas, though practical field implementation faces challenges.

Conclusions:

  • Emerging technologies like NGS and biosensors, coupled with AI, are revolutionizing waterborne pathogen detection, offering improved accuracy and speed.
  • Despite advancements, challenges remain in developing robust, cost-effective, and user-friendly techniques for routine on-site water quality monitoring.
  • Future research should prioritize practical field applicability and the integration of AI to enhance global water safety and public health.