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<p>Antimicrobial susceptibility testing (AST) technologies that rapidly identify pathogenic bacteria and their resistance phenotypes are critical in addressing the antimicrobial resistance crisis, enabling timely and precise antibiotic treatment decisions. We present a modular automated platform based on nanoplasmonic colorimetry in microfluidics for parallel bacterial identification and phenotypic profiling of AST (QolorPhAST), achieving an eightfold enhancement in detection rapidity. QolorPhAST reduces drug susceptibility profiling times in direct specimens from days to minutes, bypassing overnight cultures and pathogen isolation typically required in standard clinical AST workflows. The approach was validated with a broad range of microbial pathogens, spanning 10 bacterial species and 34 strains across various antibiotic concentrations to identify pathogens and antibiotic minimal inhibitory concentrations in a multiplexed fashion. In a proof-of-concept clinical study, QolorPhAST was tested with a cohort of blinded patient samples suspected of urinary tract infections, achieving 100% accuracy in species identification, an average categorical agreement of 91.81% and an average essential agreement of 86.4%, with a turnaround time of 36 min from specimen introduction to result. The study suggests that QolorPhAST, with its ease of use and cost-effectiveness, can be a transformative solution to address the antimicrobial resistance burden.</p>

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Ultra-rapid nanoplasmonic colorimetry in microfluidics for antimicrobial susceptibility testing directly from specimens

  • 期刊论文

  • 发表日期：

    2026年2月2日

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  • Mahsa Jalali,
  • Tamer AbdElFatah,
  • Carolina del Real Mata,
  • Imman I. Hosseini,
  • Sripadh Guptha Yedire,
  • Geoffrey A. McKay,
  • Rachel Corsini,
  • Roozbeh Siavash Moakhar,
  • Hamed Shieh,
  • Grace Reszetnik,
  • Seyed Vahid Hamidi,
  • Cedric P. Yansouni,
  • Dao Nguyen,
  • Sara Mahshid

摘要

Antimicrobial susceptibility testing (AST) technologies that rapidly identify pathogenic bacteria and their resistance phenotypes are critical in addressing the antimicrobial resistance crisis, enabling timely and precise antibiotic treatment decisions. We present a modular automated platform based on nanoplasmonic colorimetry in microfluidics for parallel bacterial identification and phenotypic profiling of AST (QolorPhAST), achieving an eightfold enhancement in detection rapidity. QolorPhAST reduces drug susceptibility profiling times in direct specimens from days to minutes, bypassing overnight cultures and pathogen isolation typically required in standard clinical AST workflows. The approach was validated with a broad range of microbial pathogens, spanning 10 bacterial species and 34 strains across various antibiotic concentrations to identify pathogens and antibiotic minimal inhibitory concentrations in a multiplexed fashion. In a proof-of-concept clinical study, QolorPhAST was tested with a cohort of blinded patient samples suspected of urinary tract infections, achieving 100% accuracy in species identification, an average categorical agreement of 91.81% and an average essential agreement of 86.4%, with a turnaround time of 36 min from specimen introduction to result. The study suggests that QolorPhAST, with its ease of use and cost-effectiveness, can be a transformative solution to address the antimicrobial resistance burden.