Adaptable microfluidic system for single-cell pathogen classification and antimicrobial susceptibility testing

Hui Li, Peter Torab, Kathleen E. Mach, Christine Surrette, Matthew R. England, David W. Craft, Neal J. Thomas, Joseph C. Liao, Chris Puleo, Pak Kin Wong

Research output: Contribution to journalArticlepeer-review

14 Scopus citations

Abstract

Infectious diseases caused by bacterial pathogens remain one of the most common causes of morbidity and mortality worldwide. Rapid microbiological analysis is required for prompt treatment of bacterial infections and to facilitate antibiotic stewardship. This study reports an adaptable microfluidic system for rapid pathogen classification and antimicrobial susceptibility testing (AST) at the single-cell level. By incorporating tunable microfluidic valves along with real-time optical detection, bacteria can be trapped and classified according to their physical shape and size for pathogen classification. By monitoring their growth in the presence of antibiotics at the single-cell level, antimicrobial susceptibility of the bacteria can be determined in as little as 30 minutes compared with days required for standard procedures. The microfluidic system is able to detect bacterial pathogens in urine, blood cultures, and whole blood and can analyze polymicrobial samples. We pilot a study of 25 clinical urine samples to demonstrate the clinical applicability of the microfluidic system. The platform demonstrated a sensitivity of 100% and specificity of 83.33% for pathogen classification and achieved 100% concordance for AST.

Original languageEnglish (US)
Pages (from-to)10270-10279
Number of pages10
JournalProceedings of the National Academy of Sciences of the United States of America
Volume116
Issue number21
DOIs
StatePublished - 2019

Keywords

  • antimicrobial susceptibility testing
  • diagnostics
  • infection
  • microfluidics
  • single-cell analysis

ASJC Scopus subject areas

  • General

Fingerprint Dive into the research topics of 'Adaptable microfluidic system for single-cell pathogen classification and antimicrobial susceptibility testing'. Together they form a unique fingerprint.

Cite this