Synergizing Nanomaterials and Artificial Intelligence in Advanced Optical Biosensors for Precision Antimicrobial Resistance Diagnosis.

Journal: ACS synthetic biology
Published Date: Jun 6, 2024

Abstract

Antimicrobial resistance (AMR) poses a critical global One Health concern, ensuing from unintentional and continuous exposure to antibiotics, as well as challenges in accurate contagion diagnostics. Addressing AMR requires a strategic approach that emphasizes early stage prevention through screening in clinical, environmental, farming, and livestock settings to identify nonvulnerable antimicrobial agents and the associated genes. Conventional AMR diagnostics, like antibiotic susceptibility testing, possess drawbacks, including high costs, time-consuming processes, and significant manpower requirements, underscoring the need for intelligent, prompt, and on-site diagnostic techniques. Nanoenabled artificial intelligence (AI)-supported smart optical biosensors present a potential solution by facilitating rapid point-of-care AMR detection with real-time, sensitive, and portable capabilities. This Review comprehensively explores various types of optical nanobiosensors, such as surface plasmon resonance sensors, whispering-gallery mode sensors, optical coherence tomography, interference reflection imaging sensors, surface-enhanced Raman spectroscopy, fluorescence spectroscopy, microring resonance sensors, and optical tweezer biosensors, for AMR diagnostics. By harnessing the unique advantages of these nanoenabled smart biosensors, a revolutionary paradigm shift in AMR diagnostics can be achieved, characterized by rapid results, high sensitivity, portability, and integration with Internet-of-Things (IoT) technologies. Moreover, nanoenabled optical biosensors enable personalized monitoring and on-site detection, significantly reducing turnaround time and eliminating the human resources needed for sample preservation and transportation. Their potential for holistic environmental surveillance further enhances monitoring capabilities in diverse settings, leading to improved modern-age healthcare practices and more effective management of antimicrobial treatments. Embracing these advanced diagnostic tools promises to bolster global healthcare capacity to combat AMR and safeguard One Health.

Authors

  • Bakr Ahmed Taha
    Department of Electrical, Electronic and Systems Engineering, cFaculty of Engineering and Built Environment, Universiti Kebangsaan Malaysia, UKM, 43600, Bangi, Malaysia.
  • Naser M Ahmed
    Department of Laser and Optoelectronics Engineering, Dijlah University College, 00964 Baghdad, Iraq.
  • Rishi Kumar Talreja
    Vardhman Mahavir Medical College and Safdarjung Hospital, New Delhi 110029, India.
  • Adawiya J Haider
    Applied Sciences Department/Laser Science and Technology Branch, University of Technology, 00964 Baghdad, Iraq.
  • Yousif Al Mashhadany
    Department of Electrical Engineering, College of Engineering, University of Anbar, Anbar, Iraq. yousif.mohammed@uoanbar.edu.iq.
  • Qussay Al-Jubouri
    Department of Communication Engineering, University of Technology, 00964 Baghdad, Iraq.
  • Aqilah Baseri Huddin
    Department of Electrical, Electronic and Systems Engineering, Faculty of Engineering and Built Environment, Universiti Kebangsaan Malaysia UKM, 43600 Bangi, Malaysia.
  • Mohd Hadri Hafiz Mokhtar
    Department of Electrical, Electronic and Systems Engineering, Faculty of Engineering and Built Environment, Universiti Kebangsaan Malaysia UKM, 43600 Bangi, Malaysia.
  • Sarvesh Rustagi
    Sarvesh Rustagi, School of Applied and Life Sciences, Dehradun, Uttarakhand.
  • Ajeet Kaushik
    NanoBioTech Laboratory, Health Systems Engineering, Department of Environmental Engineering, Florida Polytechnic University, Lakeland, Florida 33805, USA.
  • Vishal Chaudhary
    Research Cell and Department of Physics, Bhagini Nivedita College, University of Delhi, New Delhi, India.
  • Norhana Arsad
    Department of Electrical, Electronic and Systems Engineering, Faculty of Engineering and Built Environment, Universiti Kebangsaan Malaysia UKM, 43600 Bangi, Malaysia.

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