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Related Concept Videos

Methods of Classification and Identification01:28

Methods of Classification and Identification

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Bacterial identification relies on a diverse array of techniques to classify and understand microorganisms, each tailored to uncover specific characteristics. Traditional morphological approaches, while still valuable, are limited for closely related or structurally simple organisms. Modern methods integrate biochemical, serological, genetic, and advanced molecular tools to achieve greater accuracy.Morphological and Biochemical TechniquesMorphological characteristics, such as cell shape and...
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Array-based microbial identification upon extracellular aminoglycoside residue sensing.

Xizhe Li1, Bingyu Li1, Ruirui Liu2

  • 1Key Laboratory of Biomedical Information Engineering of Ministry of Education, Institute of Analytical Chemistry and Instrument for Life Science, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, 710049, Shaanxi, China.

Analytical and Bioanalytical Chemistry
|April 24, 2021
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Summary
This summary is machine-generated.

A new colorimetric sensor array (CSA) uses aminoglycoside antibiotics (AMGs) and silver nanoparticles to rapidly identify pathogenic microorganisms. This ultrasensitive method achieves excellent microbial discrimination at low concentrations, improving clinical diagnostics.

Keywords:
Bioanalytical methodsBiomedical analysisNanoparticlesOptical sensorsUV/VIS

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Area of Science:

  • Analytical Chemistry
  • Biotechnology
  • Microbiology

Background:

  • Rapid and sensitive identification of pathogenic microorganisms is crucial for effective clinical diagnosis and treatment.
  • Existing methods for microbial identification can be time-consuming or lack sufficient sensitivity.
  • Colorimetric sensor arrays (CSAs) offer a promising approach for rapid detection, but sensitivity remains a challenge.

Purpose of the Study:

  • To develop an ultrasensitive colorimetric sensor array (CSA) for rapid and accurate discrimination of pathogenic microorganisms.
  • To utilize the interaction between aminoglycoside antibiotics (AMGs) and silver nanoparticles decorated with β-cyclodextrin (AgNPs@β-CD) as the sensing mechanism.
  • To enhance the sensitivity of CSAs for microbial detection and characterization.

Main Methods:

  • Development of a CSA using four different AMGs as sensing elements and AgNPs@β-CD as a colorimetric probe.
  • Incubation of microorganisms to allow differential absorption of AMGs.
  • Detection of extracellular AMG residues via colorimetric changes in AgNPs@β-CD, indicative of localized surface plasmon resonance modification.
  • Application of chemometric methods for data analysis and microorganism discrimination.

Main Results:

  • The developed CSA demonstrated excellent discrimination among 20 different microorganisms.
  • High sensitivity was achieved, with successful discrimination at concentrations as low as 2 × 10^6 CFU/mL.
  • The CSA exhibited significantly lower detection concentrations compared to previous CSA technologies.
  • The method proved effective in measuring extracellular AMG residues, reflecting intercellular AMG uptake.

Conclusions:

  • The ultrasensitive CSA provides a portable and efficient tool for microbial discrimination.
  • This novel approach offers a new strategy to improve CSA sensitivity for microbial identification.
  • The method can be applied to quantify intercellular antibiotic uptake and screen for drugs that accumulate in pathogenic microorganisms.