A Nanoconfined, Hydrogel-Partitioned LAMP Platform for Rapid, Extraction-Free Quantification of Mycoplasma pneumoniae

Xiaoyang Jin1,2, Yuxuan Li3,4, Yajun Guo2

  • 1The School of Laboratory Medicine and Life Sciences, Wenzhou Medical University, Wenzhou 325027, China.

Insights

We developed gLAMP-X, a rapid, extraction-free method for quantifying Mycoplasma pneumoniae (M. pneumoniae). This innovative technique offers accurate pathogen detection from throat swabs in just 20 minutes.

Area of Science:

  • Molecular Biology
  • Diagnostic Technologies
  • Microbiology

Background:

  • Accurate quantification of Mycoplasma pneumoniae (M. pneumoniae) is crucial for assessing disease severity and treatment effectiveness.
  • Current methods like quantitative polymerase chain reaction (qPCR) require DNA extraction and calibration, while digital polymerase chain reaction (dPCR) is expensive and less accessible.

Purpose of the Study:

  • To develop a rapid, extraction-free, and accessible platform for accurate M. pneumoniae quantification.
  • To introduce gLAMP-X, a novel hydrogel-limited amplification (gLAMP) system for direct detection from clinical samples.

Main Methods:

  • Developed gLAMP-X, an extraction-free lysis and hydrogel-partitioned loop-mediated isothermal amplification (LAMP) platform.
  • Utilized a polyethylene glycol (PEG)-based nanoporous hydrogel to create nanoscopic microreactors for digital-like counting.
  • Optimized conditions for rapid amplification and endpoint fluorescent cluster detection.

Main Results:

  • gLAMP-X achieved a limit of detection of 1.7 copies/μL within 20 minutes.
  • Demonstrated 100% sensitivity and 98.1% specificity in analyzing 90 pediatric throat swabs.
  • Showed strong quantitative agreement with established qPCR methods.

Conclusions:

  • gLAMP-X provides a fast, sensitive, and specific method for M. pneumoniae quantification directly from clinical throat swabs.
  • The extraction-free and accessible nature of gLAMP-X addresses limitations of current diagnostic techniques.
  • This platform holds potential for improved point-of-care diagnostics and disease management.

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