Species-specific discrimination of bacterial biofilms using a ratiometric fluorescence sensor array and machine learning.

ABSTRACT: Biofilms are intricate bacterial communities encased in a self-produced extracellular matrix (ECM) of DNA, lipids, proteins, and polysaccharides. The diverse ECM composition across bacterial species significantly influences the progression of biofilm-associated infections, making precise identification crucial for effective treatment. Traditional methods such as biochemical assays, MALDI-TOF mass spectrometry, DNA sequencing and culturing provide valuable insights but have notable drawbacks, including time-consuming procedures, high costs, and the need for specialized equipment and trained personnel. These limitations hinder the rapid and widespread adoption of biofilm identification in clinical settings, underscoring the need for more streamlined, accurate, and accessible methods. In this

SUBMITTER: Gupta R 

PROVIDER: S-EPMC12658472 | biostudies-literature | 2026 Feb

REPOSITORIES: biostudies-literature