Bioaerosol Analysis with Raman Chemical Imaging Microspectroscopy

Jul 14, 2009 - Science Applications International Corp., P.O. Box 68, Gunpowder Branch, ... data cube consisting of a Raman spectrum at every pixel...
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Anal. Chem. 2009, 81, 6981–6990

Bioaerosol Analysis with Raman Chemical Imaging Microspectroscopy Ashish Tripathi and Rabih E. Jabbour Science Applications International Corp., P.O. Box 68, Gunpowder Branch, Aberdeen Proving Ground, Maryland 21010-5424 Jason A. Guicheteau, Steven D. Christesen, Darren K. Emge, Augustus W. Fountain, Jerold R. Bottiger, Erik D. Emmons,† and A. Peter Snyder* Research and Technology Directorate, Edgewood Chemical Biological Center, Aberdeen Proving Ground, Maryland 21010-5424 Raman chemical imaging microspectroscopy is evaluated as a technology for waterborne pathogen and bioaerosol detection. Raman imaging produces a three-dimensional data cube consisting of a Raman spectrum at every pixel in a microscope field of view. Binary and ternary mixtures including combinations of polystyrene beads, Grampositive Bacillus anthracis, B. thuringiensis, and B. atrophaeus spores, and B. cereus vegetative cells were investigated by Raman imaging for differentiation and characterization purposes. Bacillus spore aerosol sizes were varied to provide visual proof for corroboration of spectral assignments. Conventional applications of Raman imaging consist of differentiating relatively broad areas of a sample in a microscope field of view. The spectral angle mapping data analysis algorithm was used to compare a library spectrum with experimental spectra from pixels in the microscope field of view. This direct one-to-one matching is straightforward, does not require a training set, is independent of absolute spectral intensity, and only requires univariate statistics. Raman imaging is expanded in its capabilities to differentiate and distinguish between discrete 1-6 µm size bacterial species in single particles, clusters of mixed species, and bioaerosols with interference background particles. The chemical imaging component of Raman microspectroscopy has matured at a relatively rapid pace since its introduction approximately a decade and a half ago.1,2 With respect to sample preparation and handling, Raman chemical imaging microspectroscopy is reagentless and simple. The relative purity of a substance can be obtained, and the individual components and structural details of a complex sample can be visualized in a noninvasive manner. A univariate or multivariate data analysis * To whom correspondence should be addressed. E-mail: peter.snyder@ us.army.mil. Phone: 410-436-2416. Fax: 410-436-1912. † National Research Council Postdoctoral Fellow. (1) Treado, P. J.; Morris, M. D. In Practical Spectroscopy Series: Microscopic and Spectroscopic Imaging of the Chemical State; Morris, M. D., Ed. Marcel Dekker: New York, NY, 1993, Vol. 16, Chapter 3, 71-108. (2) Schaeberle, M. D.; Kalasinsky, V. F.; Luke, J. L.; Lewis, E. N.; Levin, I. W.; Treado, P. J. Anal. Chem. 1996, 68, 1829–1833. 10.1021/ac901074c CCC: $40.75  2009 American Chemical Society Published on Web 07/14/2009

translation of the Raman spectra also can provide a chemical or biochemical interpretation of the sample. Superposition of the microscope’s bright field image with the sample characterization provided by the Raman spectra at every pixel produces a physical and chemical visual, or overlay, map of the entire field of view. This is a powerful concept, and these characteristics allow for many types of substances to be analyzed. Raman microspectroscopy and Raman imaging have been adapted to a wide variety of substance characterizations in the automotive fields,3-5 salt particles on quartz and organic films and filters,6 and pharmaceutical7-9 and medical10-16 fields. Samples are presented as pure substances in a partial or entire field of view and as multicomponent mixtures encompassing the entire field of view. These investigations have dealt with samples characterized as broad, continuous, homogeneous, and/or heterogeneous regions. Raman imaging uses the spectra for the discrimination of chemical and/or biochemical substances. For every pixel or binned pixel group in the microscope field of view, a complete (3) Morris, H. R.; Munroe, B.; Ryntz, R. A.; Treado, P. J. Langmuir 1998, 14, 2426–2434. (4) Morris, H. R.; Turner, J. F., II; Munro, B.; Ryntz, R. A.; Treado, P. J. Langmuir 1999, 15, 2961–2972. (5) Stellman, C. M.; Booksh, K. S.; Myrick, M. L. Appl. Spectrosc. 1996, 50, 552–557. (6) Nelson, M. P.; Zugates, C. T.; Treado, P. J.; Casuccio, G. S.; Exline, D. L.; Schlaegle, S. L. Aerosol Sci. Technol. 2001, 34, 108–117. (7) Nishikida, K.; Lowry, S. Suppl. Spectrosc. 2006, 44–50. (8) Slobodan, S.; Clark, D. A. Appl. Spectrosc. 2006, 60, 494–502. (9) Lin, W.-Q.; Jiang, J.-H.; Yang, H.-F.; Ozaki, Y.; Shen, G.-L.; Yu, R.-Q. Anal. Chem. 2006, 78, 6003–6011. (10) Timlin, J. A.; Carden, A.; Morris, M. D.; Rajachar, R. M.; Kohn, D. H. Anal. Chem. 2000, 72, 2229–2236. (11) Kline, N. J.; Treado, P. J. J. Raman Spectrosc. 1997, 28, 119–124. (12) Nijssen, A.; Bakker Schut, T. C.; Heule, F.; Caspers, P. J.; Hayes, D. P.; Neumann, M. H.; Puppels, G. J. J. Invest. Dermatol. 2002, 119, 64–69. (13) van der Poll, S. W. E.; Bakker Schut, T. C.; van der Laarse, A.; Puppels, G. J. J. Raman Spectrosc. 2002, 33, 544–551. (14) de Jong, B. W. D.; Bakker Schut, T. C.; Maquelin, K.; van der Kwast, T.; Bangma, C. H.; Kok, D.-J.; Puppels, G. J. Anal. Chem. 2006, 78, 7761– 7769. (15) Koljenovic, S.; Bakker Schut, T.; Vincent, A.; Kros, J. N.; Puppels, G. J. Anal. Chem. 2005, 77, 7958–7965. (16) Koljenovic, S.; Bakker Schut, T. C.; Wolthuis, R.; Vincent, A. J. P. E.; Hendriks-Hagevi, G.; Santos, L.; Kros, J. M.; Puppels, G. J. Anal. Chem. 2007, 79, 557–564.

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Raman spectrum is obtained. This procedure results in a Raman spectral hypercube comprising the x and y dimensions of distance in the field of view and the spectral wavenumber intensity information in the third dimension. Spectral matching routines can be used to identify the contents of the binned pixels if the Raman spectrum is a member of a previously measured spectral library. Spectral angle mapping is a commonly used univariate correlation technique.6,17 This method is used to compare a library spectrum with experimental spectra from pixels in the microscope field of view. This direct one-to-one matching is straightforward, does not require a training set, is independent of absolute spectral intensity, and only requires univariate statistics. The number and types of spectra in the library have no effect on individual experimental spectrum matching with a library spectrum. Raman microspectroscopy is firmly established as a tool to investigate and characterize pure bacterial preparations.8,18-24 However, in addition to Raman microspectroscopy, three recent reports showed the feasibility of applying Raman chemical imaging microspectroscopy for the visualization of bacteria on a microscope slide using a combination of optical, fluorescence, and Raman spectroscopy.23,25,26 Roesch et al.23 obtained Raman spectra in a field of view with a pure suspension of Bacillus sphaericus. Details were resolved with respect to confocal Raman spectra taken at depth and area intervals inside a single bacterium. However, the Raman chemical image was obtained from only three distinct spectral peaks. Kalasinsky et al.25 performed an image analysis by fusion of the Raman chemical image with the bright field image, fluorescence image, and morphological information of single Bacillus globigii bacteria. B. anthracis (BA) was also investigated with a superposition of the Raman chemical image and a dark field reflectance optical image. Tripathi et al.26 investigated Raman imaging of a mixture of Bacillus atrophaeus (BG) and E. coli (EC) in the 550-1800 cm-1 wavenumber region. A preliminary proof of principle was obtained that showed Raman spectral differences in a microscope field of view containing discrete, isolated bacteria. This visual analysis used a priori knowledge that discrete spherical (BG spores) and rod-shaped (EC) bacteria were present. To the best of the authors’ knowledge, the two (17) Helm, D.; Labischinski, H.; Naumann, D. J. Microbiol. Methods 1991, 14, 127–142. (18) Hutsebaut, D.; Maquelin, K.; De Vos, P.; Vandenabeele, P.; Moens, L.; Puppels, G. J. Anal. Chem. 2004, 76, 6274–6281. (19) Naumann, D., In Infrared and Raman Spectroscopy of Biological Materials; Gremlich, U.; Yan, B., Eds.; Marcel Dekker, Inc.: New York, NY, 2001; Chapter 9, 323-377. (20) Schuster, K. C.; Urlaub, E.; Gapes, J. R. J. Microbiol. Methods 2000, 42, 29–38. (21) Harz, M.; Rosch, P.; Peschko, K.-D.; Ronneberger, O.; Burkhardt, H.; Popp, J. Analyst 2005, 130, 1543–1550. (22) Rosch, P.; Schmitt, M.; Kiefer, W.; Popp, J. J. Mol. Struct. 2003, 661662, 363–369. (23) Roesch, P.; Harz, M.; Schmitt, M.; Peschke, K.-D.; Ronneberger, O.; Burkhardt, H.; Motzkus, H.-W.; Lankers, M.; Hofer, S.; Thiele, H.; Popp, J. Appl. Environ. Microbiol. 2005, 71, 1626–1637. (24) Rosch, P.; Harz, M.; Peschke, K.-D.; Ronneberger, O.; Burkhardt, H.; Schule, A.; Schmauz, G.; Lankers, M.; Hofer, S.; Thiele, H.; Motzkus, H.-W.; Popp, J. Anal. Chem. 2006, 78, 2163–2170. (25) Kalasinsky, K. S.; Hadfield, T.; Shea, A. A.; Kalasinsky, V.; Nelson, M. P.; Neiss, J.; Draush, A. J.; Vanni, G. S.; Treado, P. J. Anal. Chem. 2007, 79, 2658–2673. (26) Tripathi, A.; Jabbour, R. E.; Treado, P. J.; Neiss, J. H.; Nelson, M. P.; Jensen, J. L.; Snyder, A. P. Appl. Spectrosc. 2008, 62, 1–9.

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reports25,26 were the first to investigate relatively crowded biological fields of view with Raman imaging containing discrete particles. Here, no a priori knowledge of morphology was used to differentiate objects in a microscope field of view. Raman chemical images of bacteria, their mixtures, and interferential matrices were processed and reduced with no bias and no a priori spectral information. In addition, mixtures of Bacillus subtilis and B. thuringiensis spore aerosols of different particle sizes mixed with background subway aerosol particulates were investigated in order to simulate practical outdoor, field implications for biological characterization by full spectral matrix Raman imaging. The techniques and data analysis methods herein are suggested to have utility in the delineation of solid mixtures such as counterfeit, impure, or adulterated ingredients in complex pharmaceutical formulations. Recent clandestine activities have replaced the active pharmaceutical ingredients and major foodstuff components with cheaper, untested, and unapproved alternative or substitute ingredients in a number of commercial formulations.27 Glycerin, heparin, and pet food,27 herbal dietary supplements,28 and infant milk powder29 commercial products were deliberately tampered and/or altered prior to mass distribution. Melamine was an adulterant in pet foods that was shown to kill thousands of cats and dogs in the U.S.27 The U.S. Pharmacopeia has suggested the formation of a standardized spectral library of pharmaceutical compounds, excipients, fillers, binders, and tablet components.27 A recent report30 provides evidence of successful investigations in the Raman imaging of 6% melamine by weight mixed with wheat flour. The ring breathing mode at 670 cm-1 is the most intense Raman peak31 of melamine, and a Raman image of a microscope slide field of view was produced on the basis of that single band. Further evidence is presented herein to support full spectrum Raman imaging methodology as an important adjunct to combat the threat of adulterated pharmaceutical formulations based on location, supply distribution, storage, and a formulation process. The present work also provides evidence that Raman imaging has the ability to detect and identify individual bacterial cells in a mixture of microorganisms and an intense Raman scattering interference,32 polystyrene (PS). One micrometer diameter PS spheres are similar in size to the bacterial cells but have a relatively stronger Raman scattering signal. This provided an analysis for the interference potential of PS in the elucidation of the presence and identity of bacterial analyte(s). The bright field image allows for a visual isolation of individual particles, while the Raman imaging component provides species discrimination and the ability to color-code individual particles in a bacterial mixture. Raman imaging is demonstrated for the first time to identify several Bacillus spores of similar diameter and vegetative cells in (27) Cox, B.; Eglovich, J. S. In The Gold Sheet; McCaughan, M., Ed.; F-D-C Reports:Rockville, MD, 2008; 42(12). (28) Singh, S.; Prasad, B.; Savaliya, A. A.; Shah, R. P.; Gohil, V. M.; Kaur, A. Trends Anal. Chem. 2009, 28, 13–28. (29) Yang, S.; Ding, J.; Zheng, J.; Hu, B.; Li, J.; Chen, H.; Zhou, Z.; Qiao, X. Anal. Chem. 2009, 81, 2426–2436. (30) Liu, Y.; Chao, K.; Kim, M. S.; Tuschel, D.; Olkhovyk, O.; Priore, R. J. Appl. Spectrosc. 2009, 63, 477–480. (31) Koglin, E.; Kip, B. J.; Meier, R. J. J. Phys. Chem. 1996, 100, 5078–5089. (32) Xie, C.; Dinno, M. A.; Li, Y.-Q. Opt. Lett. 2002, 27, 249–251.

a microscope field of view with no morphological considerations in the presence of similar size interference and aerosol background particles in the liquid and aerosol states with univariate statistical methods. EXPERIMENTAL SECTION Bacterial Sample Preparations. Bacillus cereus ATCC 11778 (BC) was obtained freeze-dried from the American type culture collection (ATCC) (Manassas, VA 20108). The culture was transferred every 24 h in Nutrient agar (Becton-Dickinson, Sparks Glencoe, Baltimore, MD 21152) at 30 °C until a steady state of growth was reached. BG Nakamura (formerly Bacillus subtilis var. niger) ATCC 9372 was grown on new sporulation medium (BectonDickinson) at 37 °C and incubated for various harvest times. A stock preparation of BA Sterne strain was removed from freezer storage, streaked onto Nutrient agar, and incubated at 35 °C for 1 to 2 days, and the cells were harvested. Secondary cultures of the organisms were streaked onto multiple plates of Sheep’s Blood agar (Tryptic Soy agar (TSA) with 5% sheep’s blood, SBA) for 1 to 2 days. The strain was acquired from the United States Army Medical Research Institute for Infectious Diseases, Aberdeen Proving Ground, MD, 21010-5424. SBA was purchased directly from Culture Media and Supplies (Oswego, IL 60543). The harvested BA preparation was examined with a phase contrast microscope.33 The Bacillus thuringiensis israeliensis (BT) spores were obtained from the Critical Reagents Program, ECBC, Aberdeen Proving Ground, MD. They were grown in Modified G-medium. The growth medium was prepared by dissolving 2 g of yeast extract and 2 g each of (NH4)2SO4 and K2HPO4 in 1 L of distilled water and autoclaved. A sterile 1 L salt solution was prepared by adding 250 mg of CaCl2, 500 mg of CuSO4, 5 mg of FeSO4, 2 g of MgSO4, 500 mg of MnSO4, and 50 mg of ZnSO4 into 1 L of distilled water with subsequent autoclaving. The salt solution (100 mL) was added to the 1 L solution containing yeast extract after cooling. The culture was allowed to sporulate in the modified G-medium for 7 days. The culture was spun down and washed two times with water and then spun down again and resuspended in water. EC strain ATCC 29425 was grown on Tryptic soy agar (Difco) at 37 °C and processed as presented elsewhere.26 Enumeration and Gram staining procedures were performed on plate count agar (Difco Laboratories, Detroit, MI 48201), and each Bacillus preparation was determined to consist of over 85% of the desired growth stage (vegetative/spore) in the microscope field of view. All cells and spores harvested at various growth phases were washed three times with nano-Millipore distilled water, centrifuged, pelleted, and stored at -20 °C. The lyophilized bacterial samples were prepared as 1 mg/mL suspensions in distilled water for Raman spectral experiments. Polystyrene was purchased from Polysciences, Inc. (Warrington, PA 18976) as 1 µm (part number 07310), 2.0 µm (part number 19814), and 3.0 µm (part number 17134) microsphere beads, and all were 2.6% solid latex. (33) Nicholson, W. L.; Setlow, P. In Molecular Biological Methods for Bacillus; Harwood C. R.; Cutting, S. M., Eds.; John Wiley and Sons: Chichester, England, 1990; pp 391-450.

Raman Instrumentation and Analysis. A FALCON II Raman Chemical Imaging System (ChemImage, Pittsburgh, PA 15208) equipped with a 532 nm laser excitation source and a chargecoupled device (CCD) multichannel detector was used to acquire the Raman spectra. An Osram mercury lamp (part number HBO103W/2) was used as a fluorescence source. A liquid crystal tunable filter allows wavenumber selections at a peak bandwidth, or peak width at half height, of 8 cm-1. Pixels of the CCD detector were binned into 3 × 3 groups or binned pixel groups. A 50× magnification objective was used for this work. All biological samples in the microscope field of view were photobleached for approximately 5 min before Raman spectral data acquisition. The laser power on the sample was measured between 18.8 and 29.3 mW26 with a resultant estimated power density between 777 and 1279 W/cm2, respectively. One binned pixel group covers a 0.33 × 0.33 µm square-shaped area in the microscope field of view, and this is equal to 0.11 µm2. A Bacillus spore has an average area of 1.2 µm2, and a Bacillus rod has an average area of 3 µm2 34,35 in the experimental field of view. Therefore, the area of a binned pixel group is approximately 10% and 4% of that of a Bacillus spore and rod, respectively, and an experimental Raman spectrum represents only a portion of a single cell or spore (data not shown). Multiple binned pixel groups by definition represent a single cell, and on average, approximately 10 and 25 binned pixel groups encompass a typical Bacillus spore and rod cell, respectively. Sample Handling. The suspensions consisted of a mixture of one or two different bacteria with or without PS beads in distilled water (18.3 MΩ). Additionally, for the purpose of library construction, suspensions of the bacteria and polystyrene microspheres were individually prepared. A 5 µL aliquot of each sample was spotted from a suspension on an aluminum coated microscope slide (EMF-Corp.) and allowed to dry. Comparable volumes of background water control samples were also spotted. The field of view for all experiments was chosen in the central region of the dried spot. The edges of a spot experienced bacteria aggregation while the central region of the spot displayed a dispersion of bacteria. Aerosol Preparations. The aerosols were prepared using an Ink Jet Aerosol Generator (IJAG) fabricated at ECBC.36,37 The IJAG uses ink jet printer technology for the production of wellcontrolled and well-characterized aerosol samples. The IJAG is comprised of a dispenser containing a print head, particle counter, and drying oven. A personal computer was interfaced to control the electronic and airflow requirements. The print head cartridge is the 12-nozzle model used in Hewlett-Packard Thinkjet and Quietjet printers. Cartridges were purchased empty and loaded with a slurry of water and the analyte of which particles are to be made at a concentration appropriate for the final particle size desired. The droplets emitted by this (34) Principles of Bacteriology, Virology, and Immunity; Wilson, G. S., Miles, A., Eds. The Williams and Wilkins Co.: Baltimore, MD, 1975, Vol. 1, pp 10931101. (35) Bergey’s Manual of Determinative Bacteriology, 7th ed.; Breed, R. S., Murray, E. G. D., Smith, N. R., Eds. The William and Wilkins Co: Baltimore, MD, 1957. (36) Bottiger, J. R.; Stuebing, E. W.; Deluca, P. J. In Proc. First Joint Conference on Point Detection for Chemical and Biological Defense, Science and Technology Corp.: Hampton, VA, 2000; pp 294-308. (37) Bottiger, J. R.; Deluca, P. J.; Stuebing, E. W.; Vanreenen, D. R. J. Aerosol Sci. 1998, 29, S965–S966.

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cartridge are about 50 µm in diameter and, for a dried residue particle, 5 µm in diameter. The analyte concentration should be approximately 0.1%. The loaded cartridge is mounted on the top of the dispenser and fires droplets downward through the oven which is a 5/8 in. brass tube wrapped in heat tape and held at 121 °C. As the droplets of slurry travel through the oven, the water evaporates and the nonvolatile contents coagulate into compact and roughly spherical aggregates before reaching the oven tube exit. The particle transit time is about two seconds. Heated air at 1 L/min transports the droplets through the oven, and a 0.3 L/min counter flow through a small aperture at the oven entrance is used to remove the small satellite particles that are formed when the ink jet nozzle initially fires. A laser particle counter just below the counter flow aperture monitors the actual particle rate for comparison to the user’s set rate. Particle generation rates from arbitrarily slow to about 1 kHz are supported. Three materials were used for bioaerosol investigations. BG and BT were used for biological aerosol experiments. The third material was collected with an aerosol-to-water reference collector during a month-long series of detector field trials in the Washington, DC subway system. Before each aerosol deposition, the particle size distribution was checked by directing the IJAG output to the intake of an Aerodynamic Particle Sizer, TSI Model 3321. Depositions of aerosol particles onto an aluminized substrate were achieved by affixing a funnel with a 1 mm hole at the IJAG oven exit. The funnel was held 1 to 2 mm above the substrate surface while generating 10 000 particles at 100 particles/second. Most of the particles impacted and stuck to the substrate in a spot directly underneath the funnel, but many followed the deflected air and came to rest on the surface in a circular pattern radiating from the spot and decreasing in density with distance from the central spot. Subsequently, an aerosol of the second material was laid down similarly at a spot a short distance (∼3 mm) from the first spot. Thus, along a line connecting the spots, both aerosols were present in varying proportions. The region between the two spots offered microscope field of views that showed mixtures of the two aerosols. Raman Chemical Imaging. In this study, Raman spectra were acquired from 500 to 1850 cm-1 at 10 cm-1 increments resulting in 136 individual wavenumber image frames. Upon laser irradiation, intensity was obtained at each binned pixel group for a given Raman shift. A separate image of the microscope field of view was captured for each Raman shift or wavenumber position, and the complete set of images resulted in a Raman hyperspectral cube. For each image, 28 900 binned pixel groups captured a sample Raman intensity at the selected wavenumber with a total integration time of 120 s per image. Two separate image frames per wavenumber were acquired and subsequently added together. A 9 h 4 min collection time was used to generate the 136 image Raman hyperspectral cube for one microscope field of view. The spectral data was filtered for cosmic rays, and the Raman hyperspectral cube was corrected temporally for alignment. A second order polynomial fit was used to minimize the spectral baseline. Each binned pixel group spectrum was passed through a second order, seven point Savitzky-Golay smoothing routine. A first derivative was applied to the smoothed spectrum, and that processed spec6984

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trum was utilized for further analysis. All separate images were added together for the interpretation of the visual field of view. This integrated image was subsequently used for the characterization and identification analyses of the raw field of view. The first derivative data reduction was used because it enhanced the differences between the experimental spectra of the bacteria to a relatively greater extent and reduced the broad background feature not removed by the polynomial fit (vide infra). Raman Spectral Library Construction. A field of view containing a population with a minimum of seven particles of a single analyte (bacteria or polystyrene) was selected. The resulting Raman spectral hypercube was processed, and the spectra acquired were extracted. An average of the extracted spectra from particles was chosen as the library spectrum for that particular analyte. This procedure was repeated for separate suspensions of the five bacteria and polystyrene microspheres. The EC organism was not used herein for direct experimentation investigations. However, the EC spectrum was included in the library to provide a Gram negative organism for differentiation purposes for the Gram positive Bacilli. Raman Spectral Data Reduction and Analysis. The Raman imaging classification was conducted using the spectral angle mapping38,39 algorithm in which each wavenumber intensity of an experimental spectrum was compared to the respective wavenumber intensity of a selected library spectrum contained in a binned pixel group. A least-squares analysis was conducted for linearity, and the r2 regression coefficient value was derived for a goodness of fit. The r value, or correlation coefficient, has trigonometric significance. It is related to the angle between a library spectrum vector and the experimental spectrum vector in multivariate dataspace. Both the experimental and library spectral vectors were plotted in a multidimensional space defined by individual wavenumbers as orthogonal, independent dimensions. The cosine of the angle between these two vectors is equal to the r value.36,37 This procedure was repeated for every binned pixel group Raman spectrum in every field of view for every library spectrum. The r value was used as a measure of similarity between an experimental and library spectrum. The r value also is used to compare and determine the similarity between an experimental spectrum and the members of the Raman spectral library. The highest r value over 0.5 was determined to be a match. RESULTS AND DISCUSSION The complex Raman spectra of bacteria and the large degree of spectral similarity between bacterial species make identification of the components of biological mixtures via spectral deconvolution highly problematic. Isolation of single cells or particles for separate Raman analysis provides for a greater probability of identification and discrimination against possible contamination substances, and this is an important reason why spectral angle mapping was used. However, successful detection depends in part on the dwell time of the detector for acceptable signal-to-noise (38) An Introduction to Multivariate Statistical Analysis, 2nd ed.; Anderson, R. W., Ed.; John Wiley and Sons, 1984, pp 59-68. (39) Manolakis, D.; Shaw, G. IEEE Signal Processing Magazine 2002, 19, 29– 43.

Table 1. Cross Correlation Coefficient (r) Values amongst the Library Member Conventional Raman Spectra

BA BG BT BC EC PS

BA

BG

BT

BC

EC

PS

1.00 0.76 0.85 0.85 0.81 0.03

0.76 1.00 0.85 0.54 0.59 0.17

0.85 0.85 1.00 0.78 0.81 0.06

0.85 0.54 0.78 1.00 0.92 0.03

0.81 0.59 0.81 0.92 1.00 0.07

0.03 0.17 0.06 0.03 0.07 1.00

Table 2. Cross Correlation Coefficient (r) Values amongst the Library Member First Derivative Raman Spectra

BA BG BT BC EC PS

Figure 1. Raman library (a) conventional spectra and (b) first derivative spectra of Bacillus anthracis (BA), B. atrophaeus (BG), and B. thuringiensis (BT) spores; B. cereus (BC) and E. coli (EC) vegetative cells; and PS beads.

(S/N) characteristics, bacterial concentration, and spectral reproducibility. The size of the particle also contributes to the spectral noise. For a given number of spectral scans, larger particles inherently provide better S/N ratios. Raman imaging is explored for single bacterial cell detection with respect to fundamental figures of merit and interference features in a field of view. It should be noted that Helm et al.17 used Fourier transform infrared (FT-IR) spectroscopy with spectral angle mapping to differentiate between bacterial species and strains. When the entire spectra were used, the mapping values were relatively poor. However, when only select portions of the FT-IR spectra were investigated, relatively better mapping statistics and differentiation of the 97 bacterial strains were obtained. The Raman spectra, residing in the z dimension of a hyperspectral cube, were used to detect and identify the biological and PS analytes with respect to the library spectra. Raman Spectral Library Members. Figure 1a presents Raman spectra of the bacteria and PS beads acquired by Raman imaging. As expected, many of the peaks exhibited by the bacteria are similar; however, the subtle differences are enough to enable a relative degree of differentiation between the spectra. The peaks are consistent with those documented in the literature with respect to the major biomolecules and functional groups found in Grampositive Bacillus and Gram-negative E. coli organisms.23,40-43 Observed features include tryptophan aromatic amino acid residue (40) Movasaghi, Z.; Rehman, S.; Rehman, I. U. Appl. Spectrosc. Rev. 2007, 42, 493–541.

BA

BG

BT

BC

EC

PS

1.00 0.65 0.79 0.87 0.77 0.13

0.65 1.00 0.80 0.50 0.57 0.41

0.79 0.80 1.00 0.82 0.80 0.23

0.87 0.50 0.82 1.00 0.89 0.01

0.77 0.57 0.80 0.89 1.00 -0.07

0.12 0.41 0.23 0.01 -0.07 1.00

(770 cm-1), tyrosine amino acid residue (830-840 cm-1), calcium dipicolinate (1010-1020, 1110, 1390, and 1450-1460 cm-1), amide III (1220-1260 cm-1), amide I (1650-1690 cm-1), and lipid and protein CH2 deformation (1450-1460 cm-1). Polystyrene, on the other hand, is quite distinguishable not only in vibrational modes but also in intensity as well. One notable difference between PS and the bacteria is that essentially no vibrational modes are observed in the 1650-1750 cm-1 region for PS. PS further distinguishes itself by the very strong phenyl stretch at 1000 cm-1. Despite these differences, each peak in the PS spectrum has a similar feature, either as a distinct peak or shoulder, in the bacterial spectra. A spectral angle mapping analysis was conducted for the cross correlation of the five pure bacterial species and polystyrene reference library spectra. Table 1 shows that the r values are less than or equal to 0.85 for all correlations with two different bacteria except that of BC and EC (0.92). Since both BC and EC are in the vegetative state, it is reasonable to assume that the predominant peaks in both spectra reflect the common functional groups, metabolic biochemical molecules, and structural biomacromolecules in their cellular milieus. Refer to Figure S-1 (see the Supporting Information) for the cross correlation mapping of the library conventional spectra with each other. Given this relatively high cross correlation within the library bacteria, a first derivative approach was conducted on the spectra. Figure 1b shows the first derivative of the Raman spectra for the library members, and Table 2 shows their cross correlation values using the mapping statistical analysis. Refer to Figure S-2 (see the Supporting Information) for the cross correlation mapping of the library first derivative spectra with each other. Overall, much better statistical separations are observed for the bacterial library pairs. Therefore, the first derivative spectra were used for all statistical analyses. (41) Puppels, J. G.; Olminkhof, J. H. F.; Segers-Nolten, G. M. J.; Otto, C.; de Mul, F. F. M.; Greve, J. Exp. Cell Res. 1991, 195, 361–367. (42) Esposito, A. P.; Talley, C. E.; Huser, T.; Hollars, C. W.; Schaldach, C. M.; Lane, S. M. Appl. Spectrosc. 2003, 57, 868–871. (43) Farquharson, S.; Grigely, L.; Khitrov, V.; Smith, W.; Sperry, J. F.; Fenerty, G. J. Raman Spectrosc. 2004, 35, 82–86.

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Figure 2. Images of a mixture of BA spores and PS beads in a microscope field of view. The top row presents Raman chemical images for BA, BG, BT, BC, EC, and PS. An analysis between the experimental spectrum in each pixel and each of the six library members was performed by spectral angle mapping to yield the colored regions in the BA, BG, and PS images. All six images are superimposed on the bright field image to produce an overlay image.

One reason spectral angle mapping analysis was chosen was because of the simplicity in the data interpretation. The experimental spectrum for each pixel or binned pixel group was compared to each library spectrum for a best fit analysis. No a priori knowledge and no operator intervention were required. Multivariate analysis, on the other hand, requires the operator to choose a set of principal components that will be used to represent the entire dataspace. Principal components analysis is used for differentiation of chemical features while spectral angle mapping is used to determine the identity of a particular particle in a field of view. Subsequent to principal components analysis, loading plots are usually compared to library spectra, and this is what a spectral angle mapping analysis provides. Principal components analysis does not interrogate individual entities in a microscope field of view, while spectral angle mapping provides that type of desired analysis. Polystyrene (PS) beads were chosen as a standard for bacterial analysis and identification because they can be obtained in welldefined sizes similar to that of bacteria, they possess strong Raman scattering, and they produce a clear, visual presence in a microscope field of view. Raman Chemical Imaging Microspectroscopy of Polystyrene and BA Spores: Single Bacterial Cell Analysis. Figure 2 shows the bright field image of a mixture of 1 µm PS beads and BA spores. The similarity in diameters and shapes would normally prove problematic for conventional, entire field of view identification measurements; however, differentiation is achieved with Raman imaging microscopy. The data reduction background and color scheme for the spectral angle mapping results are presented for an understanding and interpretation. A palette of colors is used where each library member was assigned a color to highlight its presence based on the spectral data reduction results. The experimental spectrum in each binned pixel group was investigated for a mapping r value based on the comparison to a BA library spectrum. Two criteria were used to determine if a binned pixel group contained a spectrum that matched that of a library member. First, the r value was chosen to be greater than 0.5 for the bacterial species and 0.8 for the PS beads in order to 6986

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remove noisy spectra and background. A threshold of r > 0.8 for PS was chosen, because it was treated as an interference and not as an analyte. The second criterion was that the highest r value between a library member and an experimental spectrum under consideration determined the identity of the experimental spectrum. The experimental spectrum was assigned the color of the matching library spectrum. The results of the library matching to all of the binned pixel group spectra are shown in the upper row in Figure 2 as six Raman images. Matching of the spectra to the BA library spectrum produced four distinct regions, while matching to that of BG produced a few random pixels. The PS beads resulted in strong signals observed in the far upper right Raman image. When all six Raman images are superimposed with the bright field image, an overlay occurs as observed in Figure 2 (bottom right). The overlay clearly differentiates the BA spore yellow regions from the blue PS beads. As observed in the overlay, the colored area surrounding the PS beads is greater than the size of the PS beads themselves. This is an effect of the strong intensity of the PS Raman scattering resulting in pixel bleeding. The blue regions in the overlay do not appear to be mixed with another color. This can be explained by the fact that the PS spectrum is sufficiently different from the other library spectra (Figure 1a,b), and the mapping r values were indeed the highest for a PS library comparison. In the upper center of the bright field image, there is a cluster that consists of four particles in a line. It is very difficult to differentiate these particles from the bright field image. The overlay identifies these four particles as one BA spore (point 1) and three PS spheres (points 2-4) (vide infra). The overlay can provide an accounting for the relative merit of the Raman imaging process when compared to the actual bright field image. The three yellow areas in the left part of the overlay adequately describe the BA spores from the surrounding PS beads. The multiple numbers of the two species were able to be noted and distinguished by Raman imaging. The color coding of the particles in the overlay in Figure 2 originates from the averaged Raman first derivative spectra shown in Figure 3. Figure 3a shows the overlay from Figure 2 where a circle is placed on top of each of the four yellow BA particles. Each circle contains a number of binned pixel groups, and each group contains a complete Raman spectrum of that specific area in the overlay. The Raman spectra inside a circle were averaged and transformed to the first derivative, and that average first derivative Raman spectrum is colored in the bottom of Figure 3b with the same color of the respective circle in Figure 3a. The spectra in the other three circles were treated in a similar fashion. The four colored spectra in the bottom of Figure 3b were averaged to yield the superimposed, bold, black spectrum. Note the relative degree of noise and variance in the individual spectra in the bottom of Figure 3b. These spectra originate from discrete single cells compared to that from particles composed of many cells, and the latter situation produced better S/N characteristics (vide infra). It was expected that very similar Raman spectra would be observed by the same substance even from discrete, different particle sizes and different sites in the field of view. Figure 3c,d was treated in a similar fashion as that of Figure 3a,b, respectively, and the bold averaged, first derivative spectrum in Figure 3b could

Figure 3. (a, c) Overlay from Figure 2 is shown with 4 and 20 circles, respectively, drawn around individual particles. (b, d) Top of each panel: BA and PS library first derivative spectra, respectively; Bottom of each panel: superimposed spectra which are the average of the first derivative spectra in the binned pixel groups contained in each color-coded circle in (a) and (c), and the bold black traces are the average of the respective group of averaged, color-coded first derivative spectra. (e) The right inset shows the overlay. The left red circle in the upper right side in the overlay outlines the BA particle of the cluster, and the right purple circle outlines the three PS particles. Bottom: averaged, first derivative spectra from the two separate circles and from both circles combined in the overlay. Table inset: cross correlation r values for the comparison between the bottom three spectra and the six library spectra.

be distinguished from that in Figure 3d for the PS bead portion of the field of view. Spectra for particles #2-4 (blue oval to the right of the yellow colored particle in the upper right-hand region in Figure 3c) also are included in the collection of spectra in the bottom of Figure 3d. The S/N of the individual Raman spectra for PS, as shown in the bottom of Figure 3d, is significantly better than that for the BA spores. This is most likely due to the relatively strong Raman scattering efficiency of PS. A better accounting of the average experimental spectra (two bold spectra in Figure 3) is their relative match to the six library spectra. The bold, average spectrum in Figure 3b was compared to the six library spectra. The comparisons of the bold average spectrum in Figure 3b to the BA, BG, BT, BC, EC, and PS library spectra are r ) 0.79, 0.72, 0.71, 0.68, 0.63, and 0.43. Even though the BG and BT r values are relatively close to that of BA, the BA library spectrum provides the highest r at 0.79 to the averaged

experimental spectrum. Similar treatment of the 18 experimental, averaged spectra of PS into the averaged, bold spectrum in Figure 3d yields r values for BA, BG, BT, BC, EC, and PS of 0.22, 0.44, 0.26, 0.10, 0.01, and 0.95. Clearly, this analysis provides an excellent match to the PS beads with the average experimental spectrum in Figure 3d. Refer to Figure S-3 (see the Supporting Information) for the cross correlation mapping of the library spectra with the BA and PS bold averaged experimental spectra. The power of a binned pixel group analysis for Raman spectra and Raman imaging in general is shown in Figure 3e. The top two spectra are again the library Raman spectra of the PS beads and BA spores. In the overlay image inset, a region is outlined (marked by an arrow) that contains a BA spore (#1 in Figure 2) on the left side and PS beads (#2-4 in Figure 2) on the right side. The left red circle has an average Raman spectrum plotted in the bottom of Figure 3e and labeled BA. The spectrum from the right purple circle is plotted in the bottom of Figure 3e and labeled PS. When the spectra from both circles are averaged together, the green labeled BA + PS spectrum is obtained, and this is a very close match to the PS bead Raman spectrum. The table inset in Figure 3e lists the library spectra and their r values when cross correlated to each of the extracted, average spectra in the bottom of Figure 3e. Note that the BA spectrum from the left circle (#1 in Figure 2) provides an r value of 0.75 while the other two spectra yield relatively lower values. PS features dominate in the other two cases with r values of 0.94 (PS spectrum) and 0.84 for the BA + PS spectrum. Matches to the other three bacteria were lower. Careful attention is necessary when making distinctions between adjacent or clustered particles in a mixture using Raman imaging. This is especially true for a strong Raman scattering substance such as PS adjacent to a relatively weaker Raman scattering substance such as a biological particle. Either an addition of spectra or possible domination of one spectrum over another is possible in a mixture sample. Depending on the S/N, bulk averaging of the spectra in a region in a field of view vs isolating specific pixels needs to be addressed so as not to cause a mixing of spectra of different substances. Ternary Mixture. A mixture of PS beads, BC vegetative cells, and BG spores were prepared and analyzed by Raman imaging. Figure 4a shows the overlay image containing many particles. Cross correlation results for BA, BT, and EC showed very few scattered pixels in their Raman images (data not shown). Figure 4a shows a significant amount of BG (red color) and BC (green color), and PS provides very strong blue-labeled particles. The color-coded, averaged first derivative Raman spectra for each of the circled, red-colored regions in Figure 4a are shown in Figure 4b. Note that the overall average spectrum (bold black spectrum) is very similar to the upper library spectrum of BG spores. Spectra extracted from the circled, green-colored regions in Figure 4c are shown in Figure 4d. Here again, the experimental first derivative spectra provide a close match to the library spectra of the BC vegetative cells. The circled blue regions in Figure 4e have spectra that provide an excellent match to the library spectrum of the PS beads in Figure 4f. All three species had extensive sampling of Raman spectra for inclusion into their overall average spectra. Analytical Chemistry, Vol. 81, No. 16, August 15, 2009

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Figure 4. (a, c, e), Overlay resulting from the Raman images of BA, BG, BT, BC, EC, and PS and the bright field image (data not shown) from a mixture of PS beads, BC vegetative cells, and BG spores. Circles highlight the presence of BG, BC, and PS, respectively. (b, d, f), First derivative spectra of BG, BC, and PS, respectively. The collection of first derivative spectra in the lower group of spectra in each panel represents the average spectra from each circled area in the corresponding overlay image. The bold black traces are the averaged first derivative spectra.

An r value analysis of the bold, averaged spectra in Figure 4b,d was performed. The average r values for the bold spectrum in Figure 4b when matched to the BA, BG, BT, BC, EC, and PS library spectra are 0.69, 0.89, 0.79, 0.56, 0.54, and 0.56, respectively. The match to the BG library spectrum is the highest. A similar, respective analysis for the bold spectrum in Figure 4d yields 0.83, 0.62, 0.85, 0.89, 0.76, and 0.38. The match to the BC library spectrum is the highest. In a similar manner for PS, the r values are 0.23, 0.44, 0.29, 0.12, 0.01, and 0.95, and note that the biological species have r < 0.44. Refer to Figure S-4 (see the Supporting Information) for the cross correlation mapping of the library spectra with the bold averaged experimental spectra of BG, BC, and PS. BG Bioaerosols. Roesch et al.24 simulated an aerosol situation by smearing agar plates colonies of Micrococcus luteus on a microscope slide mixed with melamine resin, polymethylmethacrylate, and TiO2. Those four species constituted the conventional Raman spectral database for subsequent experimental spectral matching. Subway environments present an example scenario where biological detection and identification of analytical technologies may be useful. Mixtures of Bacillus spores and Washington, DC subway aerosol particles were made in order to provide an initial determination on the effect of contamination in an aerosol form on the discrimination ability of the Raman imaging technique. Different aerosols were deposited onto the surface of an aluminum coated glass slide in succession to create a mixture on the slide. In order to identify each aerosol particle in a mixture of several species by visual means, the particles were made to be of different sizes, with nonoverlapping size distributions. This method represented a “ground truth” by visual discrimination. Figure 5a provides a bright field image from a sample slide where aerosol particles (small dark circles) lie adjacent and among 6988

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Figure 5. (a) Microscope bright field image from a mixture of 3 µm diameter BG and Washington, DC subway aerosol particles. All particles were in the plane of focus in the field of view. (b) Fluorescence image of Figure 5a. (c), Same microscope field of view except the focus was biased for aerosol particles above the plane of focus in Figure 5a. (d) Fluorescence image of Figure 5c.

the Bacillus particles (large gray circles). BG and the subway aerosol particles had mean diameters of 6.9 and 5.0 µm, respectively. The fluorescence image in Figure 5b clearly shows intense UV fluorescence for the three large Bacillus particles labeled #1-3, and the many smaller, dark-colored particles exhibit no fluorescence. The latter most likely contain saturated species with very little aromatic compounds. Careful inspection of the fluorescence image also shows some circular indentations about the perimeter of each Bacillus particle. These indentations are the result of the aerosol particles situated on the periphery and on top of the biological particles as clearly observed in Figure 5a. The partially superimposed aerosol particles obscure the fluorescence at the edges of the Bacillus particles. The Raman images for BA, BC, EC, and PS contained essentially no colored regions or pixels (data not shown). However, the BG spores show very strong signals in the overlay plot in Figure 6a. Very few pixels for BT were observed, and they did not display defined, continuous regions of pixels (data not shown). The overlay plot provides a clear distinction between the BG spore and subway aerosol particles. The overlay shows strong Raman signatures in Bacillus particles #1 and 2; however, particle #3 shows a significantly weaker response with small clusters of pixels of Raman activity for BG spores (red color). The origin of this latter phenomenon was investigated further. The bright field and fluorescence images in Figure 5a,b are presented where the Bacillus particles are in focus with aerosol particles also in the same focal plane. Figure 5c,d show the same field of view where the focus was on aerosol particles above the biological particles. The aerosol particles are near the edge and in the center of Bacillus particles #1 and 3, respectively; however, only Bacillus particle #3 is visually obscured by an aerosol particle. Aerosol particle #1a in Figures 5a and 6a imparts minimal visual perturbation of the Bacillus spectra in those pixels as can be seen by the red perimeter coloration in the overlay. However, the aerosol particle above Bacillus #3 is significant in size and occupies a major portion of the pixel space. This is the most plausible reason for a less than satisfactory accounting for the Raman imaging of Bacillus particle #3 in the overlay in Figure 6a. The

Figure 6. (a, c) Overlay image resulting from the Raman images of BA, BG, BT, BC, EC, and PS (data not shown) and the microscope bright field image (Figure 5a) from a mixture of 3 µm diameter BG and Washington, DC subway aerosol particles. Circles highlight the presence of BG and aerosol particles in a and c, respectively. (b, d) The collection of first derivative spectra represent the average spectra from each circled area in the corresponding overlay image. The bold black traces are the averaged first derivative spectra.

Raman imaging of Bacillus particle #3 in the overlay (Figure 6a) apparently was compromised by the superimposed subway aerosol particle (Figure 5c,d). The absence of the visual appearance of the aerosol particle above Bacillus particle #3 in Figure 5b is most likely due to the antumbra effect (shadow effect) of the subway aerosol particle. Nevertheless, there are clusters of pixels that are in close proximity with respect to each other (yellow circle on particle #3 in Figure 6a) to indicate the presence of a BG particle similar in size to particles #1 and 2. Direct spectral obscuration, interference, or peak additions from the subway aerosol particle above BG particle #3 is minimal because of the relative absence of peaks in the subway aerosol Raman spectrum in Figure 6d. Therefore, differentiation was effected by the significant differences between the BG and aerosol first derivative Raman spectra as shown in Figure 6. Note that all major regions in each set of particles are sampled (colored circles in Figure 6a,c). A correlation coefficient analysis of the averaged BG spectrum (bold black trace) in Figure 6b with BA, BG, BT, BC, EC, and PS are 0.54, 0.82, 0.69, 0.39, 0.45, and 0.38. The experimental spectrum matches well for a BG determination and a similar analysis with that of the averaged first derivative spectrum of the subway particles yields r < 0.41 for all six library members. Refer to Figure S-5 (see the Supporting Information) for the cross correlation mapping of the library spectra with the bold experimental averaged spectra of BG and the aerosol particles. Additional types of ambient aerosols may provide more information as to their interference effect on the Raman imaging spectra of a single biological particle in a microscope field of view when the particles are colocated. Aerosol Mixtures of BG and BT Spores. A BG aerosol with a mean diameter of 3.5 µm was sprayed on a microscope slide. The spray was terminated, and the nozzle was moved laterally one inch. A BT aerosol with a mean diameter of 6.3 µm was sprayed onto the slide. Because the individual Bacilli have very similar diameters, their particle sizes were deliberately made different in order to visually distinguish them under the microscope. The overlap region was investigated for a mixture analysis.

Figure 7. Images of separately deposited 6 µm diameter BT and 3 µm diameter BG aerosol particles on a microscope slide. Refer to Figure 2 for details.

The BT particle diameter is twice that of BG, and neighboring (adjacent) and colocated (superimposed) deposition of BG and BT can occur. Observation of the bright field image in Figure 7 shows three large particles and a host of smaller particles. It can be surmised that the larger particles are BT and the smaller ones originate from BG. It is also possible that the larger BT particles may separate or eject smaller BT particles or individual cells upon impact on the slide. Figure 7 provides interrogations for each of the six library members in the top row of Raman images. Raman spectral presence is only observed for BT and BG. When all six images are superimposed on the bright field image, an overlay image is produced in the bottom right in Figure 7. Note that an independent corroboration of the nature of the particles is obtained by the fluorescence image. All particles that are colored BG (red) and BT (purple) also produce ultraviolet fluorescence, and this is an expected observation. An analysis yields three relatively large BT particles (purple color) where two of them have adjacently located and possibly superimposed smaller BG particles. Particle #1 shows an isolated BT cluster, and particle #2 presents two BG particles (#4 and 5) where particle #5 is adjacent to the larger BT particle #2. There is a slight purple color on the outer edges of BG particles #4 and 5. This may indicate the likelihood of a break up of the BT particle where BG particles #4 and 5 are superimposed on two smaller BT particles. It appears that there are a number of BG particles superimposed on the upper left side of BT particle #3, because there are a number of red colored clusters of pixels superimposed on the purple background of what appears to be a continuous region of different size BT particles. This observation is similar to that of particle #3 in Figure 5c,d where a BG particle was superimposed on an inert aerosol particle. Figure 8 shows the first derivative Raman spectra for the redcolored (Figure 8a) and purple-colored (Figure 8c) regions. The relatively high density of cells in each particle provides very good S/N characteristics for the experimental spectra for both BG and BT particles. Excellent matches are observed for each respective set of experimental spectra in Figure 8b,d, their averaged (bold trace) Raman spectra, and their respective library spectra. The highlighted smaller red regions in Figure 8a yield very good spectral comparisons with each other in the bottom of Figure 8b. Analytical Chemistry, Vol. 81, No. 16, August 15, 2009

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Figure 8. Overlay images (a, c) are that from Figure 7. Regions are highlighted with circles in the overlay images, and their respective experimental first derivative averaged Raman spectra (b, d) are presented. The bold average spectra are shown.

Note that the seven purple regions highlighted in Figure 8c all provide a very close spectral fit to each other in the bottom of Figure 8d. These regions include colored circles containing all or a portion of particles #4-7 which indicate definite BT character directly adjacent to the red-colored BG particles. An outlier spectrum in Figure 8b,d is not observed from any respective circle in Figure 8a,c. Therefore, it is highly likely that BG particles #4 and 5 and the cluster of BG particles adjacent to particle #3 in Figure 7 are all superimposed on smaller BT particles that may have separated from the initially larger aerosol particle. The cross correlation indices of the bold average BG experimental spectra in Figure 8b are 0.68, 0.91, 0.83, 0.58, 0.64, and 0.32 for the BA, BG, BT, BC, EC, and PS library spectra, respectively. All the redcolored regions in Figure 8a clearly indicate BG (r ) 0.91). The same respective set of correlation coefficient values for Figure 8d is 0.78, 0.87, 0.96, 0.77, 0.78, and 0.26. The r ) 0.96 value indicates the clear presence of BT in all of the purple-colored regions in Figure 8c. Refer to Figure S-6 (see the Supporting Information) for the cross correlation mapping of the library spectra with the bold experimental averaged spectra of BG and BT. CONCLUSIONS Using the spectral angle mapping method, Raman chemical imaging microscopy is shown as a potential, competitive technology for pathogen detection and classification/identification. The Raman spectra of microorganisms clearly show differentiation at the single cell level in a microscope field of view. Binary and

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ternary mixtures of Gram-positive Bacillus spores, Bacillus vegetative cells, and PS beads were differentiated and distinguished by Raman imaging. The presence of the strong Raman scattering PS beads did not confuse the analysis of the biological component(s) in mixtures. The ability to define and differentiate micrometersized particles in a microscope field of view provides promise for the differentiation of individual, adjacent, species using Raman imaging spectroscopy. Even highly complex/congested fields of view produced no significant detriment to the determination of the different substances where many micrometer-sized particles formed multiple clusters. More difficult challenges for Raman imaging microspectroscopy include scenarios such as a sample containing a mixture of different Bacillus spores. Different Bacillus spores are very similar in diameter, and it may be a significant challenge to differentiate between them from their Raman spectra. It was shown that aerosols of bacterial particles were amenable to Raman imaging analysis. Even at different particle sizes, deposition of BG and BT spore aerosol clusters did not provide a straightforward visual determination from a Raman imaging overlay plot. An unbiased spectral angle mapping analysis determined that the larger BT particles partially separated into smaller BT particles with subsequent BG deposition on top of the smaller BT particles. Modern instruments and biosensors have made important contributions in rapid, cursory analysis and detailed, comprehensive, yet time-consuming procedures for laboratory and field sample determinations. As such, systems may be categorized as triggers, detectors, classifiers, or identifiers. As a result of the work herein, we believe there is a strong incentive for exploiting Raman sensors as classifiers to the genus and species levels. ACKNOWLEDGMENT The authors thank Drs. Janet L. Jensen and James O. Jensen of the U.S. Army ECBC for technical discussions and comments. The authors wish to thank the Defense Threat Reduction Agency (DTRA), Joint Service Agent Water Monitor Program for providing the resources for this work. This research was performed while E.D. Emmons held a National Research Council Research Associateship Award at the U.S. Army Edgewood Chemical Biological Center. SUPPORTING INFORMATION AVAILABLE Additional information as noted in text. This material is available free of charge via the Internet at http://pubs.acs.org. Received for review May 17, 2009. Accepted July 3, 2009. AC901074C