title: Waterborne pathogen detection using Raman spectroscopy.
abstract: Raman spectroscopy is being evaluated as a candidate technology for waterborne pathogen detection. We have investigated the impact of key experimental and background interference parameters on the bacterial species level identification performance of Raman detection. These parameters include laser-induced photodamage threshold, composition of water matrix, and organism aging in water. The laser-induced photodamage may be minimized by operating a 532 nm continuous wave laser excitation at laser power densities below 2300 W/cm(2) for Grampositive Bacillus atrophaeus (formerly Bacillus globigii, BG) vegetative cells, 2800 W/cm(2) for BG spores, and 3500 W/cm(2) for Gram-negative E. coli (EC) organisms. In general, Bacillus spore microorganism preparations may be irradiated with higher laser power densities than the equivalent Bacillus vegetative preparations. In order to evaluate the impact of background interference and organism aging, we selected a biomaterials set comprising Gram-positive (anthrax simulants) organisms, Gram-negative (plague simulant) organisms, and proteins (toxin simulants) and constructed a Raman signature classifier that identifies at the species level. Subsequently, we evaluated the impact of tap water and storage time in water (aging) on the classifier performance when characterizing B. thuringiensis spores, BG spores, and EC cell preparations. In general, the measured Raman signatures of biological organisms exhibited minimal spectral variability with respect to the age of a resting suspension and water matrix composition. The observed signature variability did not substantially degrade discrimination performance at the genus and species levels. In addition, Raman chemical imaging spectroscopy was used to distinguish a mixture of BG spores and EC cells at the single cell level.
authors.affiliation: Science Applications International Corp., P.O. Box 68, Gunpowder Branch, Aberdeen Proving Ground, Maryland 21010-5424, USA.
authors.forename: Ashish
authors.initials: A
authors.lastname: Tripathi
authors.forename: Rabih E
authors.initials: RE
authors.lastname: Jabbour
authors.forename: Patrick J
authors.initials: PJ
authors.lastname: Treado
authors.forename: Jason H
authors.initials: JH
authors.lastname: Neiss
authors.forename: Matthew P
authors.initials: MP
authors.lastname: Nelson
authors.forename: Janet L
authors.initials: JL
authors.lastname: Jensen
authors.forename: A Peter
authors.initials: AP
authors.lastname: Snyder
mesh_terms: D000465:Algorithms; D001419:Bacteria / Q000302:isolation & purification*; D015169:Colony Count, Microbial / Q000379:methods*; D004784:Environmental Monitoring / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013059:Spectrum Analysis, Raman / Q000379:methods*; D014871:Water Microbiology; D014873:Water Pollutants / Q000032:analysis*; D014881:Water Supply / Q000032:analysis*
chemical_list: D014873:Water Pollutants