Bacterial Cellulose Nanocrystals (BCNCs) are biocompatible cellulose nanomaterials that can host guest nanoparticles and recognition elements (e.g., proteins, antibodies, aptamers, etc.) of unique properties to develop hybrid nanocomposites of wide-ranging applications. We combined magnetic iron oxide (Fe3O4) nanoparticles (NPs) and plasmonic gold NPs (AuNPs) with BCNCs to develop hybrid Au@Fe3O4@BCNC nanocomposites and evaluated their applicability as surface-enhanced Raman scattering (SERS) substrates in the detection of malachite green isothiocyanate (MGITC). Using the nanocomposites as SERS substrates, Rapid and sensitive detection of MGITC at concentrations as low as 10-10 M was achieved. To further advance the concept of BCNC based biosensors, we modified the BCNCs surface with lectin and applied the lection modified BCNCs (con A@BCNCs) to isolate bacteria cells. Lectins are a large family of proteins that can specifically bind to the carbohydrate components on the surface of bacterial cell walls. Concanavalin A (Con A), a legume sourced lectin, has a high affinity for the D-mannose and α-glucose functional groups on all bacterial surfaces. Then, AuNPs were decorated onto the fibers of con A@BCNCs for label-free SERS detection of bacteria. Using this detection assay, a total of nineteen bacterial species of both gram-positive and gram-negative bacteria were detected. The large SERS spectral database of 19 bacterial species was analyzed using support vector machine (SVM), an optimization-based machine learning technique that works as a binary classifier. The SVM classifier showed a high overall accuracy of 87.7% in discriminating between bacterial species. Scanning electron microscopy (SEM) was used to visualize the association of bacteria to the aggregated con A@BCNC substrates before and after coating with AuNPs. The sensitivity of this detection assay was tested with Escherichia coli K12 and was found to be 103 CFU mL-1. Overall, the combination of bacterial cellulose-based SERS substrates to extract SERS spectral features and machine learning-based techniques to analyze large spectral datasets have great potential for environmental analysis.

Bacterial cellulose nanocrystals as low-cost surface enhanced Raman scattering (SERS) substrates for environmental sensing applications

ACS Spring 2022

The official archive and repository for all ACS Meetings & Expositions abstracts and select posters or presentations.