Challenges in biofilm quantification and the emerging role of hyperspectral imaging

Title : Challenges in biofilm quantification and the emerging role of hyperspectral imaging

Abstract:

Biofilms are structured multicellular bacterial communities embedded in a self-produced extracellular matrix that can adhere to any biotic or abiotic surface. Biofilms associated infections, occurring in wounds, dental plaques, urinary tract and its persistence on medical devices. Bacteria within biofilms exhibit enhanced tolerance to antibiotics and external stressors. According to the National Institute of Health (NIH), approximately 65% of microbial infection and 80% of chronic infections are associated with biofilm formation. Yet despite decades of research, there is no universally reliable assay to quantify biofilm biomass. The standard microtiter plate assay using crystal violet (CV) staining is fundamentally semi-quantitative and error prone. Several studies have highlighted the limitations of CV staining for biofilm quantification. To address this issue, we employed emerging spectroscopic technique hyperspectral imaging (HSI) platform to analyse biofilm formation on abiotic surface. This study reports biofilm detection/ quantification of Acinetobacter baumannii using HSI. A. baumannii is a ‘critical’ nosocomial pathogen having robust biofilm forming ability on biotic or abiotic surfaces. Biofilm of A. baumannii (ATCC 19606 and 2 field isolates) developed on sterile abiotic in-house fabricated stainless-steel coupon (SS304) in 24-well tissue culture plate. Biofilm formation on coupon validated performing scanning electron microscopy (SEM), observed bacterial adherence on metal surface and the biofilm matrix. Hyperspectral data acquired at 24 h and 48 h incubation period to monitor biofilm biomass on coupon. Spectral signatures analysed using machine learning approaches, including SVM, AE+MLP, and AE+CNN, for biofilm detection. Among these, SVM achieved the highest accuracy of 97.3% in distinguishing biofilm from blank surfaces.

Keywords: Acinetobacter baumannii, Biofilm, Antimicrobial resistance, Crystal violet assay, Hyperspectral imaging, Machine learning.

Biography:

Abhishek Kandikatla, PhD scholar at SRM University, AP, Andhra Pradesh, India. His work focuses on multidrug resistance (MDR) and Carbapenem resistant (CR) Acinetobacter baumannii, particularly its biofilm formation, detection, and therapeutic targeting. He employ Non-destructive, non-invasive techniques such as, hyperspectral imaging integrating machine learning to study biofilm detection and quantification in non-invasive diagnostic approach. His research also explores molecular mechanism of biofilm disruption of A. baumannii.