title: Detection of extremely low concentration waterborne pathogen using a multiplexing self-referencing SERS microfluidic biosensor.
abstract: BACKGROUND
  It is challenging to achieve ultrasensitive and selective detection of waterborne pathogens at extremely low levels (i.e., single cell/mL) using conventional methods. Even with molecular methods such as ELISA or PCR, multi-enrichment steps are needed which are labor and cost intensive. In this study, we incorporated nano-dielectrophoretic microfluidic device with Surface enhanced Raman scattering (SERS) technique to build a novel portable biosensor for easy detection and characterization ofEscherichia coli O157:H7at high sensitivity level (single cell/mL).
  
  
  RESULTS
  A multiplexing dual recognition SERS scheme was developed to achieve one-step target detection without the need to separate target-bound probes from unbound ones. With three different SERS-tagged molecular probes targeting different epitopes of the same pathogen being deployed simultaneously, detection of pathogen targets was achieved at single cell level with sub-species specificity that has not been reported before in single-step pathogen detection.
  
  
  CONCLUSIONS
  The self-referencing protocol implements with a Nano-dielectrophoretic microfluidic device potentially can become an easy-to-use, field-deployable spectroscopic sensor for onsite detection of pathogenic microorganisms.
authors.affiliation: Agricultural and Biosystems Engineering Department, Iowa State University, Ames, IA 50011 USA.
authors.forename: Chao
authors.initials: C
authors.lastname: Wang
authors.affiliation: Chemistry department, Kansas State University, Manhattan, KS 66506 USA.
authors.forename: Foram
authors.initials: F
authors.lastname: Madiyar
authors.affiliation: Agricultural and Biosystems Engineering Department, Iowa State University, Ames, IA 50011 USA.
authors.forename: Chenxu
authors.identifier: 0000-0001-8229-6439
authors.initials: C
authors.lastname: Yu
authors.affiliation: Chemistry department, Kansas State University, Manhattan, KS 66506 USA.
authors.forename: Jun
authors.initials: J
authors.lastname: Li