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Plasmid Stability Analysis with Open-Source Droplet Microfluidics
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High-Speed, Label-Free Antimicrobial Susceptibility Testing in Picoliter Droplets: Combining Cage-Based Phase

Chenyi Lei1, Lulu Xu1, Chufan Xiao1

  • 1Institute of Biopharmaceutical and Health Engineering, Tsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen, Guangdong 518055, PR China.

Analytical Chemistry
|March 20, 2026
PubMed
Summary
This summary is machine-generated.

A new automated antimicrobial susceptibility testing (AST) system, CYSDrop AST, offers rapid, low-cost bacterial drug analysis. This high-throughput method significantly reduces time and cost for identifying effective antibiotic treatments, aiding in combating antimicrobial resistance.

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Area of Science:

  • Microbiology
  • Biotechnology
  • Medical Diagnostics

Background:

  • Antimicrobial resistance (AMR) is a growing global health threat.
  • Current antimicrobial susceptibility testing (AST) methods are often expensive and time-consuming.
  • There is a critical need for rapid, cost-effective AST solutions.

Purpose of the Study:

  • To develop an automated, label-free, high-throughput AST system for antibacterial drug analysis.
  • To reduce the cost and time required for AST.
  • To provide a tool for guiding antibiotic use and optimizing treatment strategies for multidrug-resistant infections.

Main Methods:

  • Development of the Cage-Based Phase Contrast Microscopy with You Only Look Once-Segment Anything Model (YOLO-SAM) Algorithm Droplets AST (CYSDrop AST) system.
  • Utilizing low-cost T-junction microfluidic chips for single-cell encapsulation in picoliter droplets.
  • Quantitative analysis of bacterial load using YOLO-SAM algorithm for droplet discrimination.

Main Results:

  • CYSDrop AST achieved a per-assay cost reduced to one-third of traditional methods.
  • Total sample-to-result time was shortened to 4 hours.
  • Demonstrated 100% categorical agreement with the broth microdilution (BMD) method for colistin susceptibility testing of *E. coli* strains.
  • Achieved high consistency (89.6%) with manual annotation and near-perfect performance in discriminating positive/negative droplets (AUC = 0.994, AP = 0.988).
  • Successfully tested colistin resistance in urine samples.

Conclusions:

  • CYSDrop AST is a rapid, automated, and cost-effective solution for antimicrobial susceptibility testing.
  • The system accurately determines bacterial susceptibility and is valuable for guiding the use of last-line antibiotics.
  • This technology can optimize therapeutic strategies for patients with multidrug-resistant infections.