Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Microbial Biosensors01:17

Microbial Biosensors

91
Microbial biosensors are analytical devices that utilize living microbes to detect specific substances through measurable signals. These devices consist of two main components: biosensing organisms and signal-transducing elements. Biosensing organisms, such as Escherichia coli or Saccharomyces cerevisiae, are typically housed in multiwell plates connected to transducers, enabling rapid, real-time detection of target analytes.Signal Generation MechanismWhen a target analyte—such as...
91
Automated Microbial Diagnostics01:24

Automated Microbial Diagnostics

79
Automated diagnostic analyzers have transformed clinical microbiology by providing rapid and reliable methods for pathogen identification and antibiotic susceptibility testing. Among these systems, the Vitek 2 is widely used because it automates the traditionally labor-intensive processes of microbial identification (ID) and antibiotic susceptibility testing (AST), delivering standardized and timely results that are essential for effective patient care.Microbial Identification with ID CardsThe...
79

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Simultaneous Dual-Gene Detection of <i>Escherichia coli</i> O157:H7 Based on a CRISPR/Cas13-Mediated Biosensor.

JACS Au·2026
Same author

Antiviral resistance testing for DNA viruses in immunocompromised patients: Mechanisms, clinical utility, and limitations.

Diagnostic microbiology and infectious disease·2026
Same author

An Environmentally Resilient, Metal-Organic Framework-Armored CRISPR/Cas12a Sensing Reactor (ENCASE) for the Ultra-Stable and On-Site Detection of <i>Salmonella typhimurium</i> in the Food Supply Chain.

ACS sensors·2026
Same author

Identifying intra-hospital Norovirus GII transmission using whole-genome sequencing.

Genome medicine·2026
Same author

A visual-colorimetric-photothermal multimodal immunoassay for sensitive and quantitative detection of Escherichia coli.

Talanta·2025
Same author

Immobilization of PETase on Magnetic Nanoparticles Enhances Their Stability and Activity for Efficient Degradation of Polyethylene Terephthalate.

ACS applied materials & interfaces·2025
Same journal

The ACS at 150: The History of Analytical Chemistry Publications and a Century of Progress.

Analytical chemistry·2026
Same journal

Machine Learning-Enabled Image Analysis of Complex Chemical Mixtures: Synthetic Urine Droplets as a Test System.

Analytical chemistry·2026
Same journal

H<sub>2</sub>O<sub>2</sub>/Viscosity Tandem-Locked Fluorescent Probes Based on an In Situ Fluorophore Synthesis Strategy for Colitis Imaging and Diagnosis.

Analytical chemistry·2026
Same journal

TopoStitcher: A Geometric-Topological Structure-Guided Stitching Framework for Single-Molecule Localization Microscopy.

Analytical chemistry·2026
Same journal

Noninvasive SERS Immunosensing of Tyrosinase for Melanoma Monitoring via Microneedle Sampling Integrated with Satellite-Structured Bifunctional Nanozymes.

Analytical chemistry·2026
Same journal

Label-Free Electrochemical CRISPR Platform Gated by Allosteric Transcription Factors for Ultrasensitive Small-Molecule Detection.

Analytical chemistry·2026
See all related articles

Related Experiment Video

Updated: May 6, 2026

Bacterial Detection & Identification Using Electrochemical Sensors
09:30

Bacterial Detection & Identification Using Electrochemical Sensors

Published on: April 23, 2013

28.5K

Metabolism-Driven Colorimetric "Read-to-Answer" Sensor Array for Bacterial Discrimination and Antimicrobial

Xiaodong Lin1, Kairui Zhai1, Benjamin M Liu2,3,4,5,6

  • 1Department of Bioengineering, University of California Riverside, Riverside, California92521, United States.

Analytical Chemistry
|July 30, 2025
PubMed
Summary
This summary is machine-generated.

This study presents a novel colorimetric sensor for rapid bacterial identification and antimicrobial susceptibility testing (AST) using gold nanoparticles. The "read-to-answer" platform offers a user-friendly and accurate solution for clinical diagnostics.

More Related Videos

Colorimetric Detection of Bacteria Using Litmus Test
10:05

Colorimetric Detection of Bacteria Using Litmus Test

Published on: September 17, 2016

9.4K
Experimental Protocol for Detecting Cyanobacteria in Liquid and Solid Samples with an Antibody Microarray Chip
10:57

Experimental Protocol for Detecting Cyanobacteria in Liquid and Solid Samples with an Antibody Microarray Chip

Published on: February 7, 2017

9.2K

Related Experiment Videos

Last Updated: May 6, 2026

Bacterial Detection & Identification Using Electrochemical Sensors
09:30

Bacterial Detection & Identification Using Electrochemical Sensors

Published on: April 23, 2013

28.5K
Colorimetric Detection of Bacteria Using Litmus Test
10:05

Colorimetric Detection of Bacteria Using Litmus Test

Published on: September 17, 2016

9.4K
Experimental Protocol for Detecting Cyanobacteria in Liquid and Solid Samples with an Antibody Microarray Chip
10:57

Experimental Protocol for Detecting Cyanobacteria in Liquid and Solid Samples with an Antibody Microarray Chip

Published on: February 7, 2017

9.2K

Area of Science:

  • Biotechnology
  • Nanotechnology
  • Clinical Diagnostics

Background:

  • Rapid and reliable bacterial identification and antimicrobial susceptibility testing (AST) are crucial for effective clinical treatment but remain challenging due to sample complexity.
  • Current methods often lack speed, user-friendliness, or direct correlation with bacterial metabolic activity.

Purpose of the Study:

  • To develop a colorimetric sensing platform for simultaneous bacterial identification and AST in clinical samples.
  • To leverage bacterial metabolism-driven gold nanoparticle (AuNP) synthesis for generating distinct colorimetric signals.
  • To create a user-friendly, robust, and accessible diagnostic tool for clinical and field settings.

Main Methods:

  • Developed a sensing platform based on bacterial metabolism-driven synthesis of gold nanoparticles (AuNPs) mediated by hydrogen peroxide (H2O2).
  • Utilized differences in bacterial metabolic activity to generate unique colorimetric signals.
  • Integrated the sensing system with linear discriminant analysis (LDA) for automated data interpretation and high-resolution profiling.

Main Results:

  • Achieved 100% classification accuracy for seven bacterial species in serum and urine samples.
  • Successfully differentiated nine strains of *Escherichia coli*.
  • Demonstrated high accuracy (97.62%) in assessing antibiotic resistance profiles for six clinical isolates.

Conclusions:

  • The developed colorimetric sensing platform accurately identifies bacterial species and determines antimicrobial susceptibility by converting metabolic signatures into diagnostic outcomes.
  • This "read-to-answer" sensor array provides a user-friendly, robust, and rapid alternative to conventional methods.
  • The technology holds significant potential for broad applicability in clinical diagnostics and field-based microbial analysis.