Multivariate analysis of liquid biopsies for real-time detection of patients with biofilm-associated infections (BAI)

J. C. Liao, S. J. Zou, Y. L. Deng, Y. Jiang, S. L. Chua, B. L. Khoo

Research output: Journal article publicationJournal articleAcademic researchpeer-review

12 Citations (Scopus)

Abstract

Biofilm-associated infections (BAI) are chronic infections that are refractory to standard antibiotic therapy and challenging to diagnose. Detecting biofilms in patients remains a major challenge in the clinical field. Here, we introduced a microfluidic-based label-free and multivariate analysis (LF-MA) platform to assess biofilm-associated infection disease via multivariate analysis of severity parameters for point-of-care (POC) management. The integrated LF-MA platform consisted of two components: Biofilm Enrichment Device (BED) and Severity Detection Device (SDD), and allowed simultaneous real-time biofilm enrichment and viscosity-based BAI severity detection. High recovery efficiencies (>80 %) were observed for both gram-positive and gram-negative strains. A novel biosensor HMS indicator (Healthy: 1–3+, Mild: 1–3-, Severe: 1 + 3-) was developed to evaluate the severity of BAI based on microbeads distribution in target outletsSDD (for viscosity assessment) and the presence of biofilms. The one-step strategy was validated with patient-derived clinical isolates and could be completed within 2 h. We envisioned that the ease of operations and derived HMS biosensor indicator could facilitate new patient-centric approaches for rapid and multivariate assessment of patients with BAI.

Original languageEnglish
Article number139595
JournalChemical Engineering Journal
Volume453
DOIs
Publication statusPublished - 1 Feb 2023

Keywords

  • Biofilm-associated infections
  • Disease detection
  • Multivariate analysis
  • Personalized treatment
  • Viscosity

ASJC Scopus subject areas

  • General Chemistry
  • Environmental Chemistry
  • General Chemical Engineering
  • Industrial and Manufacturing Engineering

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