Hiring in life sciences? Share your open positions with our professional community. Read more Close

Advertisement

Filtration-Based SERS With In Situ Gold Growth in Bacterial Microenvironment for Rapid Detection of Low-Level Bacteria.

Created on 17 Aug 2026

Authors

Eun-Bi Jang, Ji Young Lee, Hoeil Chung, Min-Young Lee

Published in

Small methods. Pages e70972. Aug 16, 2026. Epub Aug 16, 2026.

Abstract

Rapid bacterial detection and timely antimicrobial susceptibility assessment are essential for effective infection management, yet remain challenging under clinically relevant low-concentration conditions. Here, we present a filtration-based surface-enhanced Raman scattering (SERS) platform based on a microenvironment engineering strategy, in which plasmonic nanostructures are dynamically formed within the bacterial microenvironment. Using a gold nanostructured glass microfiber membrane, the platform enables large-volume sample processing through size-selective bacterial capture, followed by in situ gold growth that generates bacteria-centered plasmonic hotspots directly around bacterial cells. This architecture fundamentally overcomes the intrinsic hotspot-bacteria mismatch in conventional substrate-based SERS systems, enabling highly sensitive and selective detection while effectively suppressing nonspecific interference in complex biological matrices. To further address sampling limitations at low concentrations, a minimal pre-culture strategy was introduced to enhance bacterial surface occupancy, improving the detection limit from 103 to 101 CFU/mL. In addition, SERS signal intensity directly reflects bacterial viability, allowing rapid differentiation of antimicrobial responses and enabling susceptibility assessment within 2 h. By integrating physical enrichment with microenvironment-driven signal amplification, this platform simultaneously achieves low-level detection and rapid antimicrobial susceptibility testing within a single system. These results highlight its potential as a next-generation integrated diagnostic platform for clinical sample analysis.

PMID:
42605179
Bibliographic data and abstract were imported from PubMed on 17 Aug 2026.

Read full publication at:
Please sign in to see all details.

Advertisement

Stats

  • Community rating n/a 0 votes
  • Reviewers' rating n/a 0 votes
  • Your rating

1-terrible, 9-excellent. How would you rate this publication? Sign in in to submit your rating.

  • Recommendations n/a n/a positive of 0 vote(s)
  • Views 9
  • Comments 0

Recommended by

  • No recommendations yet.

Post a comment

You need to be signed in to post comments. You can sign in here.

Comments

There are no comments yet.

Advertisement