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In this work, the results on the detection and identification of  Bacillus thuringiensis  ( Bt ) cells by using surface-enhanced Raman spectroscopy (SERS) are presented.  Bt  has been chosen as a harmless surrogate of the pathogen  Bacillus anthracis  ( Ba ) responsible for the deadly Anthrax disease, because of their genetic similarities. Drops of 200 μL of  Bt  suspensions, with concentrations 10 2  CFU/mL, 10 4  CFU/mL, 10 6  CFU/mL, were deposited on a SERS chip and sampled after water evaporation. To minimize the contribution to the SERS data given by naturally occurring interferents present in a real scenario, the SERS chip was functionalized with specific phage receptors BtCS33, that bind  Bt  (or  Ba ) cells to the SERS surface and allow to rinse the chip removing unwanted contaminants. Different chemometric approaches were applied to the SERS data to classify spectra from  Bt -contaminated and uncontaminated areas of the chip: Principal Component Regression (PCR), Partial Least Squares Regression (PLSR) and Data Driven Soft Independent Modeling of Class Analogy (DD-SIMCA). The first two was tested and trained by using data from both contaminated and un-contaminated chips, the last was trained by using data from un-contaminated chips only and tested with all the available data. All of them were able to correctly classify the SERS spectra with great accuracy, the last being suitable for an automated recognition procedure.

Bacillus thuringiensis Cells Selectively Captured by Phages and Identified by Surface Enhanced Raman Spectroscopy Technique