Data from: Portable bacteria-capturing chip for direct surface-enhanced Raman scattering identification of urinary tract infection pathogens

Acute urinary tract infections (UTIs) are one of the most common nosocomial bacterial infections, which affect almost 50% of the population at least once in their lifetime. UTIs may lead to lethal consequences if they are left undiagnosed and untreated properly. Early, rapid and accurate uropathogens detection methods play a pivotal role in clinical process. In this work, a portable bacteria-grasping surface-enhanced Raman scattering (SERS) chip for identification of three species of uropathogens (E. coli CFT 073, P. aeruginosa PAO1, and P. mirabilis PRM1) directly from culture matrix was reported. The chip was firstly modified with a positively-charged NH3+ group, which enable itself grasp the negatively-charged bacterial cells through the electrostatic adsorption principle. After the bacterial cells were captured by the chip, concentrated Ag nanoparticles (NPs) were used to obtain their Raman fingerprint spectra with recognizable characteristic peaks and good reproducibility. With the help of chemometric method such as discriminant analysis (DA), the SERS based chip allows a rapid, successful identification of three species of UTI bacteria with a minimal bacterial concentration (105 cells/mL) required for clinical diagnostics. In addition, this chip could spot the bacterial SERS fingerprints information directly from LB culture medium and artificial urine without sample pre-treatment. The portable bacteria-grasping SERS based chip provides a possibility for fast and easy detection of uropathogens, and viability of future development in healthcare applications.

Identifier
DOI https://doi.org/10.5061/dryad.mr677g8
PID https://nbn-resolving.org/urn:nbn:nl:ui:13-8r-fgny
Metadata Access https://easy.dans.knaw.nl/oai?verb=GetRecord&metadataPrefix=oai_datacite&identifier=oai:easy.dans.knaw.nl:easy-dataset:116491
Provenance
Creator Yang, Danting; Zhou, Haibo; Dina, Nicoleta E.; Haisch, Christoph
Publisher Data Archiving and Networked Services (DANS)
Publication Year 2018
Rights info:eu-repo/semantics/openAccess; License: http://creativecommons.org/publicdomain/zero/1.0; http://creativecommons.org/publicdomain/zero/1.0
OpenAccess true
Representation
Resource Type Dataset
Discipline Life Sciences; Medicine