A PORTABLE RAMAN SYSTEM FOR THE IDENTIFICATION OF FOODBORNE PATHOGENIC BACTERIA ABSTRACT

Transcription

1 A PORTABLE RAMAN SYSTEM FOR THE IDENTIFICATION OF FOODBORNE PATHOGENIC BACTERIA B. STEVEN LUO and MIN LIN 1 Canadian Food Inspection Agency Animal Diseases Research Institute 3851 Fallowfield Road, Ottawa, Ontario K2H 8P9, Canada Accepted for Publication December 12, 2007 ABSTRACT Raman spectroscopy is emerging as an important nondestructive, noninvasive, analytical tool for the analysis of biologic materials. This study presents a procedure to make use of commercial off-the-shelf components to construct a portable dispersive Raman system and evaluates it for discrimination of bacteria by surface-enhanced Raman scattering (SERS). The system consists of a semiconductor laser (784.8 nm), a fiber optic probe (~135 mm focal spot), a mini spectrometer and a computer. UV-visible spectroscopy and transmission electron microscopy analysis of four silver colloid preparations produced in this study, together with the SERS spectra of Listeria innocua adsorbed on colloidal particles, indicated that silver colloids with the extinction maximum at >415 nm (particle size >75 nm) and a larger long wavelength tail are capable of promoting SERS of bacteria. The SERS spectra of Listeria monocytogenes, Escherichia coli O157:H7 and Salmonella enterica were acquired with the system, leading to an unambiguous identification of these bacterial foodborne pathogens on the basis of their unique spectral bands. This study demonstrated the feasibility of constructing a low-cost compact Raman system using commercially available components to perform the SERS analysis of bacteria. PRACTICAL APPLICATIONS Commercial off-the-shelf components such as a semiconductor laser, a fiber optic probe and a mini spectrometer can be used to construct a portable, low-cost dispersive Raman system. Such system allows for the acquisition of SERS spectra of bacteria adsorbed on silver colloidal nanoparticles, as exemplified by three important bacterial foodborne pathogens L. monocytogenes (serotype 4b), E. coli O157:H7 and S. enterica (serotype Typhimurium DT 104). An unambiguous identification of these pathogens was achieved based 1 Corresponding author. TEL: ; FAX: ; linm@inspection.gc.ca Journal of Rapid Methods & Automation in Microbiology 16 (2008) All Rights Reserved , Canadian Food Inspection Agency Journal compilation 2008, Wiley Periodicals, Inc.

2 RAMAN SYSTEM FOR IDENTIFICATION OF PATHOGENIC BACTERIA 239 on their unique spectral bands, indicating that an inexpensive dispersive Raman system such as the one described here may be built for the rapid characterization of bacteria isolates from food, clinical and environment samples using SERS spectral fingerprints. INTRODUCTION Bacterial pathogens transmitted commonly through foods are responsible for a significant portion of food-related illnesses (Mead et al. 1999) and pose a high risk to public health. Pathogenic strains from Campylobacter, Salmonella, Listeria and Escherichia coli are well recognized as important foodborne pathogens. Although recent data showed a decline in the incidence of infections with these pathogens in the U.S.A. (Centers for Disease Control and Prevention 2005), bacterial foodborne illnesses are still a global health concern and present a continuous challenge for food safety. Assurance of food safety, and prevention and control of bacterial foodborne diseases necessarily rely on the ability to detect the pathogens especially in a low number in foods. Increasing investigations on rapid, sensitive and specific detection of bacterial foodborne pathogens have advanced the development of detection methods from conventional culture plating techniques to newer techniques such nucleic acid-based methods (e.g., polymerase chain reaction and DNA microarray), antibody-based immunologic methods (e.g., enzyme-linked immunosorbent assay) and biosensors that combine specific molecular recognition with a physical transducer (Swaminathan and Feng 1994; Deisingh and Thompson 2004; Rasooly and Herold 2006). Raman spectroscopy, based on molecular vibrations, is emerging as an important nondestructive, noninvasive, analytical tool for biologic materials including whole bacteria (Cotton 1988; Nelson and Sperry 1991; Naumann 2001; Maquelin et al. 2002) because of the high specificity and high resolution of vibrational spectra and weak background signal from the aqueous environment. In practice, the Raman effect is relatively weak, and only ~1 in10 8 incident photons are inelastically scattered in Raman scattering. Enhancement in signal by six orders of magnitude or even more can be achieved by absorbing the analytes (molecules) on nanoparticles such as silver colloidal particles, a method referred to as surface-enhanced Raman scattering (SERS) (Moskovits 1985; Aroca 2006). SERS is even capable of detecting a single molecule (Kneipp et al. 1997; Nie and Emory 1997). Alternatively, Raman signal can also be enhanced by up to fold by resonance Raman (RR) scattering such as ultraviolet RR (UVRR) (Nelson and Sperry 1991). Following the first published paper in 1980 by Howard et al. (1980) demonstrating the ability of Raman spectroscopy to detect and identify bacteria in water using

3 240 B.S. LUO and M. LIN UVRR, a number of studies employing the Raman spectroscopic technique for the microbiologic analysis (i.e., detection, identification and characterization) of bacteria in forms of single cells, colonies or aqueous culture (after drying) have been reported in the literature (Manoharan et al. 1990; Goodacre et al. 1998; Maquelin et al. 2000, 2003, 2006; Schuster et al. 2000; Kirschner et al. 2001; Grow et al. 2003; Yang and Irudayaraj 2003; Hutsebaut et al. 2004; Jarvis and Goodacre 2004; Zeiri et al. 2004; Harz et al. 2005; Mello et al. 2005; Premasiri et al. 2005; Sengupta et al. 2005; Zeiri and Efrima 2005; Gaus et al. 2006; Oust et al. 2006). Various types of Raman configurations were used in these studies including Raman microscopy, SERS, UVRR and Fourier transform Raman spectroscopy, spanning the UV-visible to near infrared region of the electromagnetic spectrum. All the Raman systems described to date for the analysis of bacteria are laboratory-based, sophisticated, analytical instruments that are not suitable for field or on-site applications in an effort to prevent the spread of bacterial pathogens from the environment to foods or water to consumers. There are very few commercially available compact Raman systems that are specifically designed and evaluated for the identification of foodborne bacterial microorganisms. In this study, we presented a procedure to build a portable dispersive Raman system in house using off-the-shelf components, commercially available, such as a mini spectrometer with a charged coupled device (CCD) array detector, a wavelength stabilized semiconductor laser and a fiber optic probe, to optimize and evaluate it for bacterial identification. By the incorporation of the SERS technique and a low Raman background sample-supporting matrix into it, this system is capable of discriminating several important bacterial foodborne pathogens. MATERIALS AND METHODS Bacterial Culture Bacterial species Listeria innocua, Listeria monocytogenes LI0521 (serotype 4b), Escherichia coli O157:H7 ATCC and Salmonella enterica SA serovar Typhimurium DT104 (S. Typhimurium) were used in this study. Brain heart infusion broth was used to culture Listeria species; Luria Bertani broth was used to grow E. coli O157:H7 and S. Typhimurium. The number of bacteria, following a 16- to 18-h growth at 37C, was determined as described (Lin et al. 2006). For the Raman spectroscopic analysis, bacteria from the culture were washed three times with 10 mm phosphate-buffered saline (PBS), ph 7.2 by centrifugation and then resuspended in PBS to give a concentration of cells/ml.

4 RAMAN SYSTEM FOR IDENTIFICATION OF PATHOGENIC BACTERIA 241 Silver Colloid Preparation Citrate-reduced silver colloids were prepared for SERS essentially as described by Munro et al. (1995), a modified method of Lee and Meisel (1982). Briefly, deionized water (100 ml) was heated in a flask with vigorous stirring on a Corning stirrer/hot plate (Model PC-620, Fisher Scientific Ltd., Ottawa, Ontario, Canada) at the maximum heating level. At 45C, 2 ml of 9 mg/ml AgNO 3 (Sigma, St. Louis, MO) was added. When the solution temperature reached 100C (boiling), 2 ml of 1% (w/v) trisodium citrate (Sigma) was added. The heating level was then reduced to a level that maintained solution boiling. The flask was covered with an aluminum foil to minimize evaporation loss of water. After the reduction for 90 min, silver colloids formed in the flask were placed in an ice bath for quick cooling to stop the reduction reaction. The silver colloids were stored at 4C until use. Variation in the levels of heating and stirring during the reduction process was employed to obtain four preparations of silver colloids, A D. These silver colloids were evaluated for their SERS effect on a nonpathogenic Listeria species, L. innocua. UV-visible Spectroscopy and Transmission Electron Microscopy (TEM) The UV-visible absorption spectra of silver colloids, at a dilution of 1:20 in deionized water, were acquired on a BioMate 3 spectrophotometer (Thermo Electron, Madison, WI). The silver colloids were also examined by TEM on a Hitachi H-7000 Electron Microscope (Tokyo, Japan) with a voltage of 75 kv and a magnification of 50,000. Copper grids of 400 mesh that had been coated with a Formvar film followed by a carbon layer were immersed into a drop of 0.1% (w/v) poly (l-lysine) (molecular weight: 70,000~150,000) for 1 min and then into a drop of silver colloids for 5 min. Both poly (l-lysine) and colloid drops were retained on a piece of Parafilm (VWR International Ltd., Mississauga, Ontario, Canada). The colloid particles adsorbed onto a carbon-coated cooper grid were air-dried prior to being examined by TEM. Raman System Commercial off-the-shelf components were examined and selected to construct a portable Raman system that could be of use on sites for the microbiologic analysis. For the light source, a semiconductor laser (model DLZ R) was obtained from LaserPath Technologies, Inc. (Oviedo, FL). This device ( mm in dimension) generates an excitation laser light with a peak wavelength of nm (stabilized using volume Bragg grating) and a full width at half maximum (FWHM) linewidth of 0.15 nm, which could resolve spectral features apart twice laser linewidths (i.e., 0.3 nm), in terms of wave number as 4.9 cm -1. The laser delivers a continuously adjustable power output up to 410 mw. A female SMA 905 connector in

5 242 B.S. LUO and M. LIN the output port of the laser source was used to connect a fiber optic probe (model RPB) purchased from InPhotonics, Inc. (Norwood, MA) for directing the light to the samples. The probe contains a long-pass filter with an optical density of >6 at 785 nm (i.e., an attenuation of >10-6 at the wavelength of the laser), a focal lens with a focal length of 7.5 mm, giving a light spot of about 135 mm, and two optic fibers with male SMA 905 connectors (to the laser device and a spectrometer, respectively). A mini spectrometer (model HR2000) ( mm in dimension) with reflective grating and charged coupled device (CCD) was bought from Ocean Optics (Dunedin, FL). The spectrometer was configured to have a grating of H6 with 1,200/mm groove density, CCD of Sony ILX511 with 2,048 pixels and a 50-mm entrance slit, which yields a spectral range of 160~2,400 cm -1 and a spectral resolution of <9 cm -1 suitable for the analysis of biologic materials (Naumann 2001). The spectrometer was interfaced with a computer via an analog-to-digital converter, and the spectral data acquisition was accomplished using the software OOIBase32 (Ocean Optics) for further analysis. SERS Spectra Acquisition The SERS spectra were acquired on the Raman system described above. On an area of a CaF 2 optical window (Crystran Ltd., Dorset, U.K.), 6 ml of the bacterial cell suspension (~ cells) was mixed with the silver colloids that had been preaggregated with NaCl (Jarvis and Goodacre 2004) in a 2:1 ratio (v/v) of colloids to NaCl (0.05 M). The mixture was air-dried for 2 3 h and used to produce a SERS spectrum using the following parameters: the optical power on the samples at 75 mw to avoid damaging biologic materials; an integration time of 5 s, an average of 60 spectra and an average of adjacent 7 pixels using a boxcar smooth. The excitation light was focused on the edges of the samples, with the aid of an xyz translation stage, to obtain maximum signals. RESULTS Test of the Raman System Figure 1 shows the Raman system constructed in this study. When the incident photons from the laser are directed through the fiber optic probe onto a testing sample placed on a low background CaF 2 optical window or in a quartz cuvatte in the sample housing unit, the inelastic scattering of photons (Raman signal) is collected by the probe back to the spectrometer, which disperses different spectral components of the scattered light. The spectral data are recorded using the OOIBase32 computer software and analyzed later. The output power from the laser source, as measured at the laser head with an optical power meter PEM001 (Melles Griot, Inc., Carlsbad, CA), was

6 RAMAN SYSTEM FOR IDENTIFICATION OF PATHOGENIC BACTERIA 243 FIG. 1. A SCHEMATIC REPRESENTATION OF THE POTABLE RAMAN SYSTEM CONSTRUCTED IN THE STUDY USING COMMERCIAL OFF-THE-SHELF COMPONENTS Details of each component are described in the text. CCD, charged coupled device; ADC, analog-to-digital converter. 415 mw at the maximum laser driving current. The power loss between the output port of the laser and the probe head was less than 32%. The output power at the probe head was stable within 1% over a 1-h period. The spectrometer was precalibrated by the manufacturer and verified for its spectral reading accuracy after being integrated into the system by using HG-1 MercuryArgon Calibration Source according to the supplier s procedure (Ocean Optics). The system was validated for its wavelength accuracy by acquiring the Raman spectra for chloroform (CHCl 3 ) and carbon tetrachloride (CCl 4 ) (Fig. 2) both measured in a 10-mm quartz cuvette (VWR, Mississauga, Ontario, Canada) that had been placed in a compact sample holder (InPhotonics, Inc.). Table 1 summarizes the Raman peak positions (i.e., Raman shift in terms of wave numbers) of both solvents obtained with the system in comparison to the published references. Only a small difference (D=2 3 cm -1 )in peak position was found between those obtained here and the references. Characterization of Silver Colloids for SERS Four batches of citrate-reduced silver colloids were prepared in this study and characterized by TEM (Fig. 3a) and UV-visible spectroscopy (Fig. 3b) to determine the colloid morphology and spectroscopic characteristics, in order to find their correlations with the SERS effect. TEM revealed a variation in sizes and shapes of the colloidal silver particles from the four batches (A D) (Fig. 3a). The particle size was estimated with the ImageJ 1.37a software (National Institutes of Health, Bethesda, MD) (Abramoff et al. 2004) and

7 244 B.S. LUO and M. LIN FIG. 2. RAMAN SPECTRA OF CHCl 3 AND CCl 4 The spectra were acquired on the Raman system constructed in this study. TABLE 1. RAMAN PEAKS OF CHCl 3 AND CCl 4 MEASURED WITH THE SYSTEM DESCRIBED IN THIS STUDY IN COMPARISON TO THE PUBLISHED REFERENCES Peaks (cm -1 ) (this study) Peaks (cm -1 ) (Skoog et al. 1997; McCreery 2000) Delta (cm -1 ) CHCl CCl presented in Table 2. The UV-visible spectra were used to characterize the colloidal particles, and its FWHM represented the size distribution of the particles (Mie 1908). The colloidal particles from all the batches displayed broad, asymmetrically shaped UV-visible spectral bands ( nm) with a redshift in the wavelength of the extinction maximum (peak) and a broadened shoulder in the red wavelength side of the peak from batches A to D (Fig. 3b, Table 2). The spectroscopic characteristics indicated an increase in size of the spherical particles from batches A to D, which was consistent with the TEM data (Table 2). The observation that the four batches of silver colloids were distinct in both morphology and their UV-visible spectral properties provided a basis for being worthy of evaluating their SERS effect. The four batches of silver colloids (A D) were evaluated for their surface enhancement effect by acquiring the SERS spectra of L. innocua adsorbed on silver nanoparticles (Fig. 4a). Batches C and D resulted in strong Raman signals with similar signal to noise ratios in the wave number range from 400

8 RAMAN SYSTEM FOR IDENTIFICATION OF PATHOGENIC BACTERIA 245 FIG. 3. ANALYSIS OF COLLOIDAL SILVER PARTICLES BY ELECTRON MICROSCOPY AND UV-VISIBLE SPECTROSCOPY Four batches (A D) of silver colloids were prepared as described in Materials and Methods, examined for particle shapes and sizes using a transmission electron microscope (a), and analyzed for their UV-visible spectra using a spectrophotometer (b). The spectra shown here have been normalized for each colloid preparation.

9 246 B.S. LUO and M. LIN TABLE 2. UV-VISIBLE SPECTRAL DATA AND SILVER PARTICLE SIZE DISTRIBUTION Batches A B C D lmax (nm) FWHM (nm) Range of half maximum (nm) 372~ ~ ~ ~528 Size of silver sphere (nm) Minimum Maximum Mean FWHM, full width at half maximum. to 1,800 cm -1, whereas batches A and B gave rise to very weak or negligible SERS effects. Silver colloids (batches C and D) with lmax values of 415~425 nm were superior to those from batches A and B (lmax = 403~409 nm) in SERS on the present Raman system. An additional borohydride-reduced silver colloid preparation with the absorption maximum at 395 nm (particle sizes in the range of nm) also showed no SERS signal in L. inncocua (data not shown). Thus, the batch D silver colloids were used throughout the remaining study unless otherwise noted. The SERS spectrum of L. innocua, as the result of enhancement effect from colloidal silver particles, was further demonstrated in Fig. 4b. No Raman signal was observed between 400 and 1,800 cm -1 for L. innocua alone, for colloids mixed with PBS or for colloids only. A peak at 322 cm -1, common to all the four spectra (Fig. 4b), indicated the signal from the CaF 2 matrix (Maquelin et al. 2002) used to support the samples, whereas a peak signal at 242 cm -1 was shown to be from silver colloids because this band was not found in the spectrum of L. innocua in the absence of colloids. These peaks are consistent with those reported for CaF 2 (Maquelin et al. 2002) and silver colloids (Leopold et al. 2004; Zeiri and Efrima 2005). The stability of the colloid preparation is an important factor in acquiring a reproducible SERS spectra of a bacterium on the Raman system. No change in the UV-visible absorption spectra of the silver colloids was observed after being stored at 4C for a year. The SERS spectrum of L. innocua obtained with 6-month aged colloids of batch D were essentially the same (within experimental errors) as that acquired with freshly prepared colloids (Fig. 4c). These results indicate that the silver colloids prepared in this study are stable for SERS experiments for at least 6 months. SERS Spectroscopic Analysis of Bacterial Foodborne Pathogens The ability of the present Raman system to identify and discriminate between bacteria based on their SERS spectra was evaluated by the analysis of

10 RAMAN SYSTEM FOR IDENTIFICATION OF PATHOGENIC BACTERIA 247 FIG. 4. RAMAN SIGNAL ENHANCEMENT FOR BACTERIA WITH COLLOIDAL SILVER PARTICLES (a) The surface-enhanced Raman scattering (SERS) spectra of Listeria innocua adsorbed on silver particles from each of the four batches of silver colloids (A D); (b) the SERS enhancement effect of the batch D silver colloid observed with L. innocua adsorbed on silver particles, L. innocua alone, phosphate-buffered saline (PBS) plus the colloid and the colloid alone; (c) the SERS spectra of L. innocua adsorbed on colloidal silver particles from a fresh or 6-month-old colloid preparation (batch D).

11 248 B.S. LUO and M. LIN TABLE 3. SPECTRAL BANDS IN THE SURFACE-ENHANCED RAMAN SCATTERING SPECTRA ACQUIRED IN THIS STUDY FOR THREE BACTERIAL PATHOGENS (LISTERIA MONOCYTOGENES SEROTYPE 4B, ESCHERICHIA COLI O157:H7 AND SALMONELLA ENTERICA SEROTYPE TYPHIMURIUM DT 104) AND THEIR TENTATIVE ASSIGNMENTS Listeria (cm -1 ) E. coli (cm -1 ) Salmonella (cm -1 ) Tentative assignment Reference for band assignment 627 Phenylalanine (skeletal) Maquelin et al Tyrosine (skeletal) Maquelin et al Glycosidic ring/adenine/ch 2 rocking Maquelin et al. 2000, 2002; Jarvis and Goodacre 2004; Jarvis et al ~877 ~893 COC stretching/tryptophan Vohnik et al. 1998; Maquelin et al N-C stretching Vohnik et al ,029 1,027 Phenylalanine Vohnik et al ,097 C-C skeletal and COC Maquelin et al stretching from glycosidic link ~1,124 ~1,126 C-N and C-C stretching/tryptophan Vohnik et al. 1998; Maquelin et al ,331 CH 2 deformation Vohnik et al ,458 ~1,420 ~1,420 CH 2 deformation Vohnik et al. 1998; Maquelin et al ,585 Guanine, adenine (ring stretching) Maquelin et al three important bacterial foodborne pathogens: L. monocytogenes (serotype 4b), E. coli O157:H7 and S. enterica (serotype Typhimurium DT 104). Table 3 summarizes the SERS spectral bands observed for each bacterial species used in the study and the tentative assignments for these bands based on the published data. Several unique SERS peaks at 627, 732, 957, 1,097, 1,331 and 1,458 cm -1 were observed with L. monocytogenes, whereas E. coli O157:H7 displayed a unique peak at 877 cm -1. All these unique peaks were absent in S. Typhimurium. It is interesting to note the presence of a predominant peak at 732 cm -1 in L. monocytogenes, in contrast to a relatively small peak at 723 and 720 cm -1 for E. coli O157:H7 and S. Typhimurium, respectively. Each species displayed a distinct spectrum (Fig. 5) and unique spectral bands (Table 3) on the basis of which these pathogens under study were correctly identified. DISCUSSION We have constructed a portable Raman system using commercial off-theshelf components and evaluated it, together with the silver colloid-based SERS

12 RAMAN SYSTEM FOR IDENTIFICATION OF PATHOGENIC BACTERIA 249 FIG. 5. TYPICAL SURFACE-ENHANCED RAMAN SCATTERING SPECTRA OF LISTERIA MONOCYTOGENES (SEROTYPE 4B), ESCHERICHIA COLI O157:H7 AND SALMONELLA ENTERICA (SEROTYPE TYPHIMURIUM DT 104) The spectra of these bacteria each adsorbed on silver particles (batch D) were acquired as described in Materials and Methods on the Raman system constructed in this study. technique, for the analysis of foodborne bacterial pathogens. The system was validated to be functional as it reproducibly generated the Raman spectra of CHCl 3 and CCl 4 typical for these organic solvents. Difference (D =2 3 cm -1 ) between peak positions of these solvents observed here and those described in the literatures (Table 1) was marginal and could be used for correcting a measured spectrum. The low background observed in the Raman spectra of CHCl 3 and CCl 4 (Fig. 2) indicated a high attenuation of elastically scattered light within the fiber optic probe and a low level of the stray light in the spectrometer, which are essential for a Raman system to generate a quality spectrum. Utilization of the SERS technique with bacterial cells adsorbed on silver colloidal nanoparticles was necessary for producing the Raman spectrum of a bacterium on the system. Silver colloids (average sizes in the range of nm) with lmax values of >415 nm and a larger tail at the long wavelength side of absorption peaks promoted the SERS enhancement with excitation at 785 nm on the current system. This is in contrast to the results of previous studies showing that (1) silver particles with lmax values of 402~404 nm, corresponding to the particle size of 20- to 40-nm diameter, gave higher SERS intensities than those (lmax = 410 nm) with excitation at nm (Munro et al. 1995) and (2) a strong SERS signal for E. coli was observed with silver particles of ~10 nm using excitation at 532 nm (Jarvis et al. 2004). It could be explained that a different excitation wavelength of 785 nm used in this study accounts for the observed SERS effect with colloids

13 250 B.S. LUO and M. LIN being different in size (i.e., lmax) from those previously reported (Munro et al. 1995). One important mechanism responsible for these SERS observations is that molecules experience the amplified electromagnetic field produced at the surface of metal nanoparticles when the wavelength of the excitation incident light is close to a surface plasmon resonance (SPR). Thus, the colloidal silver particles such as batches C and D with broad absorption tails extending to the wavelength of the excitation laser are expected to produce an SPR leading to the observed SERS effect. The combining influence on SERS from the sizes of colloidal metal nanoparticles and the excitation wavelengths has been described by Creighton et al. (1979) and Zhang et al. (2005). These studies suggested that if a fixed excitation wavelength was to be used in the SERS study, the enhancement condition might be optimized by varying the parameter of particle sizes. The present study has successfully applied this strategy to the optimization of SERS condition by generating and screening several batches of silver nanoparticles of different sizes to match the frequency of a plasmon resonance with the laser frequency, resulting in two out of four silver colloid preparations having the SERS effect. A Raman band at 242 cm -1 observed in all the SERS measurements was attributed to the presence of silver colloidal nanoparticles. It was observed that a higher magnitude of intensity at 242 cm -1 would produce a stronger SERS signal for a bacterium as illustrated with L. innocua. The maximum of this peak can be attained by directing the focusing point of the laser to certain areas, especially at the edge of the sample. These areas may be considered to be hot spots, contributing to a strong SERS signal. This observation suggests that the peak at 242 cm -1 is a useful reference guide for focusing the laser light onto bacterial samples when performing SERS measurements. The Raman spectra of whole microbial cells contain information on the molecular composition of cells, which are composed of DNA, RNA, proteins, lipids and carbohydrate (Naumann 2001), and the SERS spectra would provide information only on those components that were activated by metal nanoparticles. The compact Raman system described here possessed the capability to generate quality spectra for bacterial discrimination as exemplified with three important bacterial foodborne pathogens, L. monocytogenes, E. coli O157:H7 and S. enterica serovar Typhimurium DT104, comparable to expensive analytical Raman microscopes used by others for the microbiologic analysis. E. coli O157:H7 and S. Typhimurium were similar in SERS spectra to Klebsiella spp., while the SERS spectra of L. monocytogenes were similar to those of gram-positive Enterococcus spp. (Jarvis and Goodacre 2004). Previous SERS studies of bacteria gave various assignments of the peaks around the region of cm -1. Jarvis and Goodacre (2004) suggested that a glycosidic ring mode from the cell wall peptidoglycan building block, N-acetyl-dglucosamine (NAG), contributed to an intense peak at ~730 cm -1 in both

14 RAMAN SYSTEM FOR IDENTIFICATION OF PATHOGENIC BACTERIA 251 gram-positive Enterococcus and gram-negative Proteus. In other SERS studies of bacteria, it was suggested that adenine produced the band at ~735 cm -1 (Farquharson et al. 2001; Guzelian et al. 2001) or 720 cm -1 (Maquelin et al. 2002). In addition, the peak at 720 cm -1 was assigned to CH 2 rocking mode in another Raman study of bacteria (Maquelin et al. 2000). Given that there is a higher content of peptidoglycan (rich in NAG) in a gram-positive bacterium (e.g., L. monocytogenes) than in a gram-negative bacterium (e.g., E. coli O157:H7 or S. Typhimurium) and that the presence of adenine in the surface composition of an intact cell is unlikely, it is suggested that the band at 732 cm -1 observed in L. monocytogenes is because of the glycosidic ring mode of NAG; this band may have been shifted to cm -1 in the microenvironments of E. coli O157:H7 and S. Typhimurium. Although the spectra of E. coli O157:H7 and S. Typhimurium were similar (not identical), they were strikingly different from that of L. monocytogenes. This may not be surprising because E. coli O157:H7 and S. Typhimurium are gram-negative bacteria, while L. monocytogenes is gram-positive. This is in contrast to a report that the normal Raman spectra of gram-positive and -negative bacteria are similar (Maquelin et al. 2000). Furthermore in UVRR spectra, the spectral bands were almost the same with respect to their positions for gram-positive and -negative bacteria but different in relative intensities (Manoharan et al. 1990; Wu et al. 2001). The results of this and other studies indicate that the SERS technique is more sensitive and specific for the detection and identification of bacteria over normal Raman and UVRR and further support the notion that the SERS spectra of bacteria could serve as whole-organism fingerprints in the identification of a targeted bacterium (Jarvis and Goodacre 2004). In summary, we have presented a procedure to construct a portable dispersive Raman system using commercial off-the-shelf components primarily for the identification of bacterial pathogens previously isolated from foods. Direct detection of bacteria in foods with the system can be a tremendous challenge and is not feasible with the assay format used at present because of the complex nature of food matrices. As demonstrated with the culture samples of L. monocytogenes, E. coli O157:H7 and S. Typhimurium, SERS spectra generated by this Raman system allowed for the discrimination of these bacterial species on the basis of their distinct spectral bands, suggesting the potential application of this compact Raman system to the identification of unknown bacteria isolated from foods, clinical samples and environments. ACKNOWLEDGMENTS We acknowledge John Devenish for help in bacterial culture and identification; Hanhong Dan, Maria Mallory and Linru Wang for technical support and discussion; and Beverly Phipps-Todd for assistance in TEM.

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