Laser-induced breakdown spectroscopy (LIBS) is a powerful analytical technique to detect the elemental composition of solids, liquids, and gases in real time. For example, recent advances in UV-VIS LIBS have shown great promise for applications in chemical, biological, and explosive sensing. The extension of conventional UVVIS LIBS to the near-IR (NIR), mid-IR (MIR) and long wave infrared (LWIR) regions (~1-12 μm) offers the potential to provide additional information due to IR atomic and molecular signatures. In this work, a Q-switched Nd: YAG laser operating at 1064 nm was employed as the excitation source and focused onto several chlorate and nitrate compounds including KClO3, NaClO3, KNO3, and NaNO3 to produce intense plasma at the target surface. IR LIBS studies on background air, KCl , and NaCl were also included for comparison. All potassium and sodium containing samples revealed narrow-band, atomic-like emissions assigned to transitions of neutral alkali-metal atoms in accordance with the NIST atomic spectra database. In addition, first evidence of broad-band molecular LIBS signatures from chlorate and nitrate compounds were observed at ~10 μm and ~7.3 μm, respectively. The observed molecular emissions showed strong correlation with FTIR absorption spectra of the investigated materials.
Mass spectrometry based proteomic approaches are showing promising capabilities in addressing various biological
and biochemical issues. Outer membrane proteins (OMPs) are often associated with virulence in gram-negative
pathogens and could prove to be excellent model biomarkers for strain level differentiation among bacteria. Whole
cells and OMP extracts were isolated from pathogenic and non-pathogenic strains of Francisella tularensis,
Burkholderia thailandensis, and Burkholderia mallei. OMP extracts were compared for their ability to differentiate
and delineate the correct database organism to an experimental sample and for the degree of dissimilarity to the
nearest-neighbor database strains. This study addresses the comparative experimental proteome analyses of OMPs
vs. whole cell lysates on the strain-level discrimination among gram negative pathogenic and non-pathogenic
strains.
Raman microspectroscopy and principal component analysis are used to decipher unique biomolecular information by
monitoring the effect of residence time of Bacillus spores suspended in deionized water. Suspensions of viable spores of
Bacillus anthracis Sterne (BA), Bacillus atrophaeus (BG), and Bacillus thuringiensis were prepared and spectrally
monitored from initial deposition (time zero) and intermittently for seven days. Questions addressed include if spectral
variations are significant with bacterial species and residence time under non-germination conditions, is the
discrimination capability affected, and are there markers indicating pre-germination activity. Clear spectral distinction
for the spore suspensions was observed with respect to residence time, however, when the residence time data were
combined, discrimination analyses showed significant overlap between the BA and BG spores. Temporal spectral
analyses at select wavenumbers suggest an increase in pre-germination activity from the freshly suspended to one day
suspensions.
Laser-induced breakdown spectroscopy (LIBS) has shown great promise for applications in chemical,
biological, and explosives (CBE) sensing and has significant potential for real time standoff detection and
analysis. We have studied LIBS emissions in the mid-infrared (MIR) spectral region for potential
applications in CBE sensing. Detailed MIR-LIBS studies were performed for several energetic materials
for the first time. In this study, the IR signature spectral region between 4 - 12 um was mined for the
appearance of MIR-LIBS emissions that are directly indicative of oxygenated breakdown products as well
as partially dissociated and recombination molecular species.
Raman microspectroscopy is used to probe the age and milieu parameters for suspensions of bacteria for their
detection in water backgrounds. No studies have been reported on the fate of Raman signatures over time for
biologicals stored in water matrices. A FALCON II Raman Chemical Imaging System (ChemImage, Pittsburgh, PA)
and 532 nm laser excitation source acquired the Raman spectra. MATLAB principal components (PC) analysis
software was employed for data reduction. Suspensions of Bacillus atrophaeus, Bacillus thuringiensis, and three
strains of E. coli (EC) were prepared in distilled and recipe tap water. Aliquots at 5 min, 5 hr, and 1, 2, and 7 days at
25 C were dried on microscope slides in replicate. Adequate spectral differences were observed for all three
organism species. Microscope analysis showed that freshly suspended Bacillus spores and EC vegetative cells, in
both water matrices, remained as spores after seven days. Agar plate growth procedures showed that the bacteria
were still viable even after seven days resting in both water matrices. All three bacterial species were separated
based on PC analysis; however, the three EC strains coalesced. The water matrix parameter was inconsistent in its
ability to separate the Raman spectra in PC plots of the five bacteria. Within each group, the time parameter poorly
separated the bacterial resting suspensions as the aging proceeded. A Mahalanobis linkage distance analysis
(dendrogram) for all three species and strains in both water matrices confirmed a random order for all five
suspension times.
Raman chemical imaging microspectroscopy (RCIM) is being evaluated as a technology for waterborne
pathogen detection. Binary and ternary mixtures including combinations of polystyrene beads, Grampositive
Bacillus anthracis and B. atrophaeus spores, B. cereus vegetative cells, and Gram-negative E. coli
cells were investigated by RCIM for differentiation and characterization purposes. We have demonstrated
the ability of RCIM, in combination with Pearson's cross correlation and multivariate principal components
analysis data reduction techniques, to differentiate these components in the same field of view (FOV).
Conventional applications of RCIM consist of differentiating relatively broad areas in a FOV. Here, RCIM
is expanded in its capabilities to differentiate and distinguish between different micron size species in
single particles and clusters of mixed species.
Relatively few reports have investigated the determination and classification of pathogens such as the
National Institute of Allergy and Infectious Diseases (NIAID) Category A Bacillus anthracis spores and
cells (BA), Yersinia species, Francisella tularensis (FT), and Category B Brucella species from FTIR
spectra. We investigated the classification ability of the Fourier transform infrared (FTIR) spectra of viable
pathogenic and non-pathogenic NIAID Category A and B bacteria. The impact of different growth media,
growth time and temperature, rolling circle filter of the data, and wavelength range were investigated for
their microorganism differentiation. Various 2-D PC plots provided differential degrees of separation with
respect to the four viable, bacterial genera including the BA sub-categories of pathogenic spores, vegetative
cells, and nonpathogenic vegetative cells. FT spectra were separated from that of the three other genera.
The BA pathogenic spore strains 1029, LA1, and Ames were clearly differentiated from the rest of the
dataset. Yersinia species were distinctly separated from the remaining dataset and could also be classified
by growth media. This work provided evidence that FTIR spectroscopy can separate the four major
pathogenic bacterial genera of NIAID Category A and B biological threat agents.
Raman spectroscopy has been evaluated as a candidate technology for waterborne pathogen detection. Parameters have
been investigated that influence the fidelity of Raman spectra of microorganisms and protein biological substances
including bacterial species and strains, susceptibility to laser induced photodamage, composition of water matrix, and
organism aging in water. An important operating parameter is the laser induced photodamage threshold of a variety of
biological materials. The laser induced photodamage may be minimized by operating a 532 nm continuous wave laser
excitation at laser power densities below 2300 W/cm2 for Gram-positive Bacillus atrophaeus (BG) vegetative cells, 2800
W/cm2 for BG spores, and 3500 W/cm2 for Gram-negative E. coli organisms. Multivariate principal components
analysis was able to discriminate six Gram-positive and Gram-negative organisms as well as five proteins between 5K
and 65K mass units. B. thuringiensis, B. cereus, BG spore and vegetative preparations, and E. coli showed minimal
aging effects when suspended in distilled and tap water. In general, Raman microspectroscopy of biological substances
exhibited minimal spectral variability due to the age of a resting suspension, water matrix, and bacterial strain. The
observed signature variability did not prevent the differentiation and characterization of bacterial genus and species and
protein substances using Raman spectroscopy.
Raman spectroscopy is being evaluated as a candidate technology for waterborne pathogen detection and
the fidelity of the Raman spectra of microorganisms with respect to their differentiation at the single cell
level are investigated. Individual entities are investigated in the microscope field of view (FOV) by Raman
chemical imaging microscopy (RCIM). The size of a substance was not found to cause spectral confusion
when collating individual entities in the FOV by multivariate principal components (PCA) and RCIM
methods. Polystyrene (PS) beads in 1-3 micron sizes were collectively grouped together by PCA. Distilled
and recipe tap water matrices produced the proper identification of the PS beads throughout the FOV, and
all PS beads in a FOV were grouped together by PCA. A mixture of Gram-positive Bacillus atrophaeus
spores and Gram-negative E. coli cells were differentiated and distinguished by RCIM.
Improvements were made to a pyrolysis-gas chromatography-ion mobility spectrometry stand-alone biodetector to provide more pyrolyzate compound information to the IMS detector module. Air carrier gas flowing continuously through the pyrolysis tube, the rate of air flow, and pyrolysis rate were found to improve the relative quality and quantity of pyrolyzate compounds detected by the IMS detector compare to earlier work. These improvements allowed a greater degree of confidence in the correlation of biological aerosols obtain in outdoor testing scenarios to a standard GC-IMS biological aerosol dataset. The airflow improvement allowed more biomarker compounds to be observed in the GC-IMS data domain for aerosols of Gram-negative Erwinia herbicola (EH) and ovalbumin protein as compared to previous studies. Minimal differences were observed for Gram-positive spores of Bacillus subtilis var. globigii (BG) from that of earlier work. Prior outdoor aerosol challenges dealt with the detection of one organism, either EH or BG. Biological aerosols were disseminated in a Western Canadian prairie and the Py-GC-IMS was tested for its ability to detect the biological aerosols. The current series of outdoor trials consisted of three different biological aerosol challenges. Forty-two trials were conducted and a simple area calculation of the GC-IMS data domain biomarker peaks correlated with the correct bioaerosol challenge in 30 trials. In another 7 trials, the status of an aerosol was determined to be biological in origin. Two additional trials had no discernible, unambiguous GC-IMS biological response, because they were black water sprays. Reproducible limits of detection were at a concentration of less than 0.5 bacterial analyte-containing particles per liter of air (ACPLA). In order to realize this low concentration, an aerosol concentrator was used to concentrate 2000 liters of air in 2.2 minutes. Previous outdoor aerosol trials have shown the Py-GC-IMS device to be a credible detector with response to determining the presence of a biological aerosol. The current series of outdoor trials has provided a platform to show that the Py-PC-IMS can provide information more specific than a biological or non-biological analysis to an aerosol when the time of dissemination is unknown to the operator. The Py-GC-IMS is shown to be able to discriminate between aerosols of a Gram-positive spore, a Gram-negative bacterium and a protein.
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