Anal. Chem. 2000, 72, 5529-5534
Multidimensional Information on the Chemical Composition of Single Bacterial Cells by Confocal Raman Microspectroscopy K. Christian Schuster,†,‡ Ingo Reese,§ Eva Urlaub,§ J. Richard Gapes,‡ and Bernhard Lendl*,†
Institute of Analytical Chemistry, Vienna University of Technology, Getreidemarkt 9/151,1060 Wien, Austria, Institute of Chemical Engineering, Fuel and Environmental Technology, Vienna University of Technology, Getreidemarkt 9/159, 1060 Wien, Austria, and Jobin-Yvon/Dilor GmbH, Neuhofstrasse 9, D-64625 Bensheim, Germany
In many biotechnological processes, living microorganisms are used as biocatalysts. Biochemical engineering science is becoming more aware that individual cells of an organism in a process can be fairly inhomogeneous regarding their properties and physiological status. Raman microspectroscopy is a novel approach to characterize such differentiated populations. Cells of the anaerobic bacterium Clostridium beijerinckii were dried on transparent support surfaces. The laser beam of a confocal Raman microscope was focused on individual cells viewed through the objective. Single bacterial cells in size ∼1 µm and sample mass ∼1 pg could be analyzed within a few minutes, when placed on a calcium fluoride support and using excitation at 632.8 nm. Spectral features could be attributed to all major cell components. Cells from a morphologically differentiated culture sample showed different compositions, indicating the presence of subpopulations. As a reference, the storage polymer granulose was detected. The multidimensional information in Raman spectra gives a global view on all major components of the cell at once, complementing other more specific information-rich methods for single-cell analysis. The method can be used, for example, to study heterogeneities in a microbial population.
Productive biotechnological processes depend on optimized performance of the utilized biocatalyst, which is often a living microorganism. The biochemical pathways in microorganisms are complex, and the metabolic activities inside the cells are difficult to measure. However, it is possible to simplify the models for pathways as functioning in certain sets or patterns of metabolic activity, termed the “physiological states”. Microorganisms appear to switch between these states, and for process monitoring, it is one major aim to assess this physiological status, so that process control can influence it in a desired way. For many processes, it is known that the microbial population is not a homogeneous mass of cells, but that groups of cells can * Corresponding author. E-mail:
[email protected]. † Institute of Analytical Chemistry, Vienna University of Technology. ‡ Institute of Chemical Engineering, Vienna University of Technology. § Jobin-Yvon/Dilor GmbH. 10.1021/ac000718x CCC: $19.00 Published on Web 10/14/2000
© 2000 American Chemical Society
exist in different physiological states. Most on-line analysis methods give only average data over this diverse population. Analysis methods on the single-cell level, such as flow cytometry1 and microscopy with image analysis,2 are only recently being applied to bioprocesses.2-4 These methods employ chemical (reactive) staining for specific detection of one or a few selected cell components. Very recently, mass spectrometric techniques (mostly based on matrix-assisted laser desorption/ionization, MALDI) have been developed to analyze single eukaryotic cells for specific components.5-7 We present here a new approach based on Raman microspectroscopy. Our model process is the acetone-butanol (ABE) fermentation, a promising biotechnological process to convert renewable resources and agricultural wastes into basic chemicals and liquid fuels.8-12 The process utilizes bacteria from the genus Clostridium which grow under anaerobic conditions (under exclusion of oxygen). These organisms are characterized by a complex cell cycle: In a typical batch fermentation, in the initial growth and division stage, the cells produce organic acids butyrate and acetate. Later, the cells stop growing and differentiate into larger so-called Clostridial forms often containing the starchlike storage material granulose, and forespore-forming cells, and start producing solvents (acetone and butanol). Under certain conditions, the differentiation is visible under the light microscope (Figure 5 inset). The different coexisting cell types presumably perform different metabolic pathways.8,9 The connections between cell cycle and process performance are not fully understood yet, even though for some strains common regulatory genes for solvent (1) Shapiro, H. M. Practical Flow Cytometry, 3rd ed.; Wiley-Liss: New York, 1995. (2) Pons, M. N.; Vivier, H. In Relation Between Morphology and Process Performance; Schu ¨ gerl, K., Ed.; Advances in Biochemical Engineering/ Biotechnology Vol. 60; Springer: Berlin, Heidelberg, 1998; pp 61-93. (3) Zhao, R.; Natarajan, A.; Srienc, F. Biotechnol. Bioeng. 1999, 62, 609-617. (4) Hewitt, C. J.; Nebe-von Caron, G.; Nienow, A. W.; McFarlane, C. M. J. Biotechnol. 1999, 75, 251-264. (5) Li, L.; Garden, R. W.; Sweedler, J. V. Trends Biotechnol. 2000, 18 (4), 151-160. (6) Redeker, V.; Toullec, J. Y.; Vinh, J.; Rossier, J.; Soyez, D. Anal. Chem. 1998, 70 (9), 1805-1811. (7) Whittal, R. M.; Keller, B. O.; Li, L. Anal. Chem. 1998, 70 (24), 53445347. (8) Jones, D. T.; Woods, D. R. Microbiol. Rev. 1986, 50 (4), 484-524. (9) Du ¨ rre, P. Appl. Microbiol. Biotechnol. 1998, 49 (6), 639-648. (10) Schuster, K. C. J. Mol. Microbiol. Biotechnol. 2000, 2 (1), 3-4. (11) Nimcevic, D.; Gapes, J. J. Mol. Microbiol. Biotechnol. 2000, 2 (1), 15-20.
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production and sporulation have been identified.9 Especially in the long-term continuous process described by Gapes et al.,11,13 the relationship between morphology as visible in the light microscope and physiological status is very complex. Characterization of the physiological states is classically done by analyzing the metabolic products, acids and solvents, in the fermentation medium. Methods to characterize the physiological status of microorganisms on the level of the cells have been reviewed by Schuster.14 For the genus Clostridium, morphological changes have been correlated with physiological states for some strains,8 and enzyme induction during the solvent shift has been analyzed by chemical assays8 and by detection of the corresponding messenger ribonucleic acids (mRNA).15 Recently, we characterized Clostridium populations by mid-infrared spectroscopy, showing that the chemical composition of cells varies widely in the different growth and production stages of the culture.16-18 Differences were found in the relative concentrations of nucleic acids and lipids, but also in the carbohydrate content of the cells due to storage material accumulation. The method was originally developed for microbial strain identification.19 It yields an average over the population in a culture. Now, the next step would be to assess variations among the cells of one culture sample. Infrared microspectroscopy and infrared imaging is being used to study single cells of higher organisms, but for bacteria, the achievable spatial resolution of ∼10 µm is not sufficient. Raman spectroscopy enables a better spatial resolution than IR spectroscopy. Raman imaging techniques have been variously developed. With point illumination of the samples using optical scanning of the exciting lasers (with wavelengths in the visible range), lateral resolutions near the theoretical limit of the half wavelength, and axial resolutions of ∼1 µm have been achieved.20,21 Markwort et al.22 compared global versus point illumination of samples, at the example of heterogeneous polymers. With global illumination and two-dimensional CCD detectors, lateral resolutions similar to those above were achieved; however, depth was not resolved, and fluorescence problems occurred. An intermediate solution is the scanning of images line by line, with line illumination and a confocal scanning system coupled to a stigmatic spectrograph,23 leading to results in axial and lateral resolution similar to point illumination. (12) Schuster, K. C.; van den Heuvel, R.; Gutierrez, N. A.; Maddox, I. S. Appl. Microbiol. Biotechnol. 1998, 49 (6), 669-676. (13) Gapes, J. R.; Nimcevic, D.; Friedl, A. Appl. Environ. Microbiol. 1996, 62, 3210-3219. (14) Schuster, K. C. In Bioanalysis and Biosensors for Bioprocess Monitoring; Scheper, T., Series Ed.; Sonnleitner, B., Vol. Ed.; Advances in Biochemical Engineering/Biotechnology Vol. 66; Springer: Berlin, Heidelberg, 2000; pp 185-208. (15) Girbal, L.; Soucaille, P. Trends Biotechnol. 1998, 16 (1), 11-16. (16) Grube, M.; Gapes, J. R.; Schuster, K. C. J. Mol. Struct. submitted. (17) Schuster, K. C., Goodacre, R.; Gapes, J. R.; Young, M. J. Ind. Microbiol. Biotechnol. submitted. (18) Schuster, K. C.; Mertens, F.; Gapes, J. R. Vib. Spectrosc. 1999, 19 (2), 467-477. (19) Naumann, D.; Helm, D., Labischinski, H. Nature 1991, 351, 81-82. (20) Shoronov, S.; Nabiev, I.; Chourpa, I.; Feofanov, A.; Valisa, P.; Manfait, M. J Raman Spectrosc. 1994, 25, 699-707. (21) Sijtsema, N. M.; Wouters, S. D.; de Grauw, C. J.; Otto, C.; Greve, J. Appl. Spectrosc. 1998, 52, 348-355. (22) Markwort, L.; Kip, B.; da Silva, E.; Roussel, B. Appl. Spectrosc. 1995, 49, 1411-1429. (23) Barbillat, J.; da Silva, E.; Lenain, B.; Manfait, M.; Sharonov, S.; Valisa, P. Int. Conference on Raman Spectroscopy, Hong Kong, 22-26 August, 1994.
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From biological samples, Raman spectra of tissues and cells of higher organisms have been obtained by microspectroscopy (for animal cells,24-26) and by Raman imaging either directly:21 or in SERS technique.20,27 Bacterial cells are typically a lot smaller than animal or plant cells, with diameters in the 1-µm range, as opposed to 10-100 µm for higher cells (with some exceptions, such as red blood cells, which are only ∼5 µm in diameter). These 1-2 orders of magnitude in length make them 3-4 orders of magnitude smaller in volume, which is in the range of 1 fL (10-15 L). So far, bacteria have been studied mainly for identification purposes. Submilligram amounts of sample could be analyzed by FT-Raman spectroscopy28,29 and by dispersive Raman microspectroscopy.30 Bacterial colonies were studied in vivo,31 groups of a few cells by the SERS technique,32 and single cells by UV resonance Raman spectroscopy.33,34 The latter spectra, however, show only very specifically the components that resonate, in this case, carotinoids. We present here conventional Raman spectra of single bacterial cells, in an approach to characterize the population distribution in bacterial cultures. MATERIALS AND METHODS Bacteria, Growth Conditions, and Reference Analysis. Cells of the anaerobic bacterium Clostridium beijerinckii NRRL B592 were grown in batch culture under oxygen-free conditions at 34 °C, on a semisynthetic growth medium MSS based on glucose and yeast extract, according to Schuster et al.12 A preculture was started from the spore stock by heat-shocking. After ∼24 h of growth, this culture (8%) was transferred to fresh medium. From this culture, samples of the biosuspension were taken and analyzed for products and remaining substrates by gas chromatography and HPLC to determine the physiological status of the culture.13 Cell density was estimated as an optical density (OD) in the spectral photometer by light scattering at 615 nm. Microscopic images were taken through the microscope attached to the Raman spectrometer (Figure 2) or through a separate light microscope after staining with iodine (Figure 5). Preparation of Cell Samples. Cell suspensions were washed twice in distilled water and resuspended in water, and the suspension was diluted to an optical density of ∼1.0. Drops of this cell suspension were dried on transparent carriers of the following materials: sodium glass (common quality glass microscope slides), quartz glass (type Suprasil, Heraeus, Hanau, (24) Puppels, G. J.; deMul, F. F. M.; Otto, C. Nature 1990, 347, 301-303. (25) Puppels, G. J.; Garritsen, H. S. P.; Kummer, J. A.; Greve, J. Cytometry 1993, 14, 251. (26) Otto, C.; Sijtsema, N. M.; Greve, J. Eur. Biophys. J. 1998, 27, 582-589. (27) Sockalingum, G.; Beljebbar, A.; Morjani, H.; Angiboust, J. F.; Manfait, M. Biospectroscopy 1998, 4 (5 Suppl), S71-S78. (28) Naumann, D.; Keller, S.; Helm, D.; Schultz, N. C.; Schrader, B. J. Mol. Struct. 1995, 347, 399-406. (29) Lo ¨chte, T. Ph.D. Thesis, University of Essen, 1997. (30) Goodacre, R.; Timmins, E. M.; Burton, R.; Kaderbhai, N.; Woodward, A. M.; Kell, D. B.; Rooney, P. J. Microbiology 1998, 144, 1157-1170. (31) Maquelin, K.; Choo-Smith, L.-P.; van Vreeswijk, T.; Endtz, H. P.; Smith, B.; Bennett, R.; Bruining, H. A.; Puppels, G. J. Anal. Chem. 2000, 72, 12-17. (32) Sockalingum, G. D.; Lamfarraj, H.; Beljebbar, A.; Pina, P.; Delavenne, M.; Witthuhn, F.; Allouch, P.; Manfait, M. In Proc. SPIE-Int. Soc. Opt. Eng 1999, 3608, 185-194 (Biomedical Applications of Raman Spectroscopy). (33) Dalterio, R. A.; Baek, M.; Nelson, W. H.; Btirr, D.; Sperry, J. F.; Purcell, F. Appl. Spectrosc. 1987, 41 (2), 241-244. (34) Nelson, W. H.; Manoharam, R.; Sperry, J. F. Appl. Spectrosc. Rev. 1992, 27, 67-124.
Figure 1. Comparison of the background signals of different carrier materials on which cells were dried. Empty, clean carriers without cells were used. Original spectra without any processing (smoothing, etc.) are shown, with the fluorescent background.
Germany); calcium fluoride (IR-spectrometer windows from Spectral Systems, Hopewell Jct., NY). Spectroscopic Instrumentation. Raman spectra of single cells were obtained using a confocal Raman microscope (LabRAM system, Jobin-Yvon/Dilor, Lille, France), similar to the system used by Shoronov et al.20 In this system, the Raman spectrometer is coupled to a microscope (model BX40, Olympus). Raman scattering was excited by a He-Ne laser at 632.8 nm and a laser power of 8 mW. The dispersive spectrometer was equipped with a grating of 1800 lines/mm, giving a spectral resolution of ∼3 cm-1. The detector was a Peltier-cooled CCD detector (ISA, Edison, NJ). Spectra were taken in point illumination. The laser beam was focused manually on individual cells by means of a ×100/0.9 microscope objective to a spot of 1-2-µm diameter, using attenuated laser power first while the cell was moved into the beam, as the laser at full power overexposed the microscopic image. A confocal pinhole of 200- or 300-µm diameter before the entrance slit rejected fluorescence and Raman signal from outof-focus planes. This enables a spatial resolution on the range of 2-3-µm according to Shoronov et al.20 Accumulation time for one spectrum was mostly 180 s (3 min). For the reference spectrum of granular starch, starch was placed on a microscopic slide and the spectrum taken through the same microscope objective, but only with 10-s accumulation time and a confocal pinhole of 1000 µm. Some measurements were also taken with excitation wavelengths of 514 (Ar laser) and 783 nm (diode laser). Spectra were recorded and processed (for smoothing, baseline subtraction, and peak detection) by means of the Labspec software (Jobin-Yvon/Dilor). The filtering factors mentioned in the description of spectra are the numbers of data points that were averaged. The video images were taken by a CCD camera and stored and processed by the Labspec software, which also enabled the measurement of cell sizes. RESULTS AND DISCUSSION Carrier Materials. Different carrier materials on which the cells should be presented to the Raman micro-spectrometer were tested for their spectral backgrounds. Figure 1 shows the result: At the excitation wavelength of 632.8 nm, normal glass of micro-
Figure 2. Raman spectrum of a single Clostridium cell of on a CaF2 carrier, of a size about 2 µm by 4 µm. The wavenumbers of the Raman shift and some tentative attributions of the major bands are given. For more attributions, also see Table 1. The inset is a video image showing a single Clostridium cell in the focused laser beam of the Raman microscope and the diffraction pattern arising from the small object of a size in the range of the laser light wavelength. It can also be seen that the diameter of the laser focus, which partly determines the sampling volume by the excitation of the Raman effect, is about the same size as the cell (modified from ref 14).
scopic slides had a quite high and fluorescent background, leading to a considerable noise level. Quartz glass performed somewhat better, but in the lower wavenumber range, this material also showed some bands and a high background. Calcium fluoride, however, showed a very flat baseline with low noise and with only one very sharp peak at 322 cm-1. Raman Spectra from Single Cells. By drying the cells from a diluted suspension in water, the cells could be placed on the carrier well separated from each other, as shown in Figure 2 and the inset in Figure 5. The lateral and axial resolution of spectral signals has been reported to be in the range of 1 µm,20,23 which should be sufficient to resolve single bacterial cells from the background of the carrier. Indeed, spectra could be obtained from such single, separated cells. An example is shown in Figure 2. The inset gives the appearance of the cell when it was moved into the (attenuated) laser beam. A good focusing of the laser onto the cell was achieved when the diffraction pattern from the small object was visible. It can also be seen that the diameter of the laser focus, which partly determines the sampling volume by the excitation of the Raman effect, is about the same size as the cell. Several interesting bands appear in the spectrum. Some tentative attributions are listed in detail in Table 1. The bands match features reported in the literature for samples of larger amounts of bacterial biomass29,31 or its molecular components35,36 (Table 1). Most bands correspond to functional groups in the main constituents of a microbial cell, proteins, carbohydrates, lipids, and nucleic acids. Some are more specific for smaller molecular (35) Schrader, B. Chem. Unserer Zeit 1997, 31 (5), 229-234. (36) Goral, J.; Zichy, V. Spectrochimica Acta 1990, 46A (2), 253-275.
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Table 1. Raman Bands Observed in Spectra of Single Bacterial Cells and Tentative Assignation
a
band or band range (cm-1)
assigned toa
ref
407 481 530-540 550 range 778-782 810-820 830, 850 1004 1030-1130 1100 range ∼1130 1249 1220-1290 ∼1320 ∼1450 1573 1660-1670
skeletal modes of carbohydrates (glucose) skeletal modes of carbohydrates (starch) δ (C-O-C) glycosidic ring glass background nucleic acids (cytidine, uracil) nucleic acids (C-O-P-O-C in RNA backbone) tyrosine (in proteins) phenylalanine (in proteins) carbohydrates, mainly -C-C-(skeletal), C-O, δ (C-O-H) glass background dCsCd (unsatd fatty acids in lipids) N-H, C-N amide III random protein (amide III); δ(CH) δ(CH2) CdC; δ (N-H) and ν (C-N) (amide II) amide I
35, 36 35, 36 31 b 29, 31, 35, 36 31 35 29 31, 35 b 35 29 29 29 35 29, 31 29
ν, stretching vibration; δ, deformation vibration. b Our measurements.
compounds, like the very characteristic sharp band of phenylalanine at ∼1001 cm-1, which is present in all protein-containing samples, and glucose (407 cm-1). So, the obtained Raman spectra contain multidimensional information on the presence and relative abundance of all major cellular components, without adding any chemical reagents to specifically mark these components. Obviously, in a complex multicomponent system such as a cell, peak attributions remain somewhat tentative, unless independent reference methods are employed, such as iodine staining for granulose (Figure 5). Measurements from single cells were also attempted at excitation wavelengths of 514 and 783 nm (spectra not shown). At 514 nm, the signals were dominated by fluorescence. At 783 nm, no signals from the cells could be detected. Line Scan over Carrier and Single Cell. To unambiguously prove that the obtained spectra were of a single cell, spectra from a line over a cell were recorded, starting at a spot near the cell where the empty carrier was viewed in the microscope image, and moving in a line over the cell in steps of ∼2 µm (Figure 3). The cell was 5.3 µm long and 1.8 µm in diameter. Clear signals were only seen when the focus was directly at the cell (spectra 3-5). These spectra differed only in overall intensity but not in the relative band intensities. The spectra taken at the carrier showed very little signal, probably resulting from some material released by a slight cell lysis during the drying process. Depth Scan through a Single Cell. The issue of proper focusing in the depth axis was assessed by depth scans through cells. Figure 4 shows the results for the same cell as the one in Figure 3: The optimal focus according to the visible laser diffraction is given as depth zero. At this position, the spectrum was most intense. Focusing 1 µm deeper into the sample resulted in a slightly lower intensity of the cell spectrum and, as expected, a higher signal from the carrier (as assessed by the band in the range of 300-375 cm-1). Spectra from even deeper spots in the carrier showed hardly any cell signal and lower carrier signal due to internal reflection at the surface. Shifting the focus 1 µm higher than the optimum, both the cell and background bands decreased 5532 Analytical Chemistry, Vol. 72, No. 22, November 15, 2000
Figure 3. Line scan over a single cell. Top: The inserted video image shows the cell of 5.3-µm length and 1.8-µm diameter on the carrier, and the trace of the excitation laser beam (* marks). Bottom: Spectra over the line scan (confocal pinhole 300 µm, acquisition time 180 s, smoothed with factor 5, no baseline correction). Only the spectra where the focus was directly at the cell (3-5) show clear signals. The spectra taken at the carrier show very litte signal.
drastically. The intense granulose signal at 481 cm-1 is visible in a range of (2 µm from the optimal focus. Detection of Culture Heterogeneity. The main purpose of this study was to assess whether heterogeneities and distributions in the chemical composition of individual cells in a culture could be detected. For this aim, a sample was analyzed in which the cells were visibly differentiated (Figure 5). This culture was 47 h
Figure 4. Depth scan over the same cell as in Figure 3. Top: Spectra (confocal pinhole 200 µm, acquisition time 120 s, smoothed with factor 7, no baseline correction). The optimal focus according to the laser diffraction was set as depth zero. Bottom: Integrated signal intensities at characteristic wavelength ranges, 300-375 cm-1 for the signal from the carrier material CaF2, 460-510 cm-1 for storage material granulose, and 800-1750 cm-1 for the protein, lipid, and carbohydrate regions of the spectra.
old after inoculation, had reached a cell density of 5.1 according to optical density at 615 nm, corresponding to ∼1.5 g/L dry matter concentration, and a pH of 5.78. The metabolic shift to solvent production had occurred; the products had reached 9.04 g/L for butanol, 3.80 g/L for acetone, 0.09 g/l butyrate, and 0.26 g/L acetate (from 2.5 g/L present in the medium at the start of the experiment). Some cells were still rather small and rod-shaped; others were enlarged and had accumulated the storage polysaccharide granulose. Indeed, some of the spectra showed the characteristic granulose peak at 481 cm-1 (spectra 1-3), whereas others did not. As a reference, the spectrum of granular starch is shown in Figure 5 (bottom). By comparison, more features of the starchlike granulose in differentiated cells can be found at 941 cm-1 and in the region of 1080-1130 cm-1. On the other hand, one peak in the carbohydrate region at 1050 cm-1 stays fairly constant, suggesting that this is a constitutive component, possibly from the cell wall. Cells with little or no granulose showed a higher phenylalanine peak at 1005 cm-1 and a somewhat more pronounced amide III region (1220-1290 cm-1), indicating a higher relative protein content. As well, the peak around 1450 cm-1 (attributed to CH2-bending vibrations, mainly from lipids and long-chain amino acids) varies considerably in intensity in different cells. So, it can be concluded that the chemical composition of single bacterial cells can indeed be assessed by Raman microspectros-
Figure 5. Heterogeneity in a culture sample: different cells from one sample. Inset: Light micrograph of a differentiated Clostridium culture in the light microscope (bright-field mode, stained with iodine solution). Cell types can be differentiated visibly by size and response to iodine stain. Iodine stains cell protein lightly (in original color, brownish) and storage polysaccharide granulose dark (in original color, black-blue) (e.g., the cell marked with the circle). The bright ends on dark large cells are the forespores. The black bar represents a length of 5 µm. Spectra are shown from different positions in the sample, which were all single cells isolated from each other. Top spectra of different cells (acquisition time 180 s, confocal pinhole 300 µm, smoothed with factor 7, baseline corrected), stacked with different baseline offsets. The cells 1-3 contained granulose in different amounts. The peak at 481 cm-1 is characteristic for starch-like polysaccharides. Bottom spectrum of granular starch shown for comparison.
copy, and differences in composition of cells within a culture sample can be detected. Sensitivity of the New Method. A rough calculation of the detection limit of the method from the minimal cell size to give “good” spectra is given in Table 2. Spectra were accepted as “good” when they showed at least the carbohydrate range (10301130 cm-1), phenylalanine band (1004 cm-1), and nucleic acid bands (at ∼780 cm-1) clearly above the noise level. On glass as a carrier, these bands could only be detected from larger, differentiated cells (spectra not shown), on CaF2 from all sizes of cells in the culture down to the smallest size of ∼1.5 by 0.7 µm. A small cell of this size can be seen in the inset of Figure 3, below the cell analyzed by the line scan. The detection limits were at the individual cell level or ∼1 pg (10-12 g). Compared to the limits Analytical Chemistry, Vol. 72, No. 22, November 15, 2000
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Table 2. Estimation of Detection Limits Depending on the Carrier Materiala carrier
smallest cell diam d to give a “good” spectrum (µm)
sample vol (fL) (assumed spherical, V ) d3π/6)
sample mass (pg) (assuming F ) 1000 kg‚m-3)
glass calcium fluoride
1.5 0.7
1.8 0.34
1.8 0.34
a Spectra were accepted as “good”, i.e., inside the detection limit, when they showed at least the carbohydrate range (1030-1130 cm-1), phenylalanine band (1004 cm-1), and nucleic acid bands (at ∼780 cm-1) clearly above the noise. The sample volume was assumed as a sphere in the diameter of the smallest cell diameter.
reported for the FT-Raman technique by Lo¨chte,29 the technique presented here is more sensitive by a factor of 109. This range of sensitivity has been achieved before only by the SERS technique32 or by UV resonance Raman spectroscopy.34 However, for the practical purpose of analyzing population distributions, both these techniques have severe drawbacks: The SERS technique requires sophisticated sample handling to get cells into contact with enhancing surfaces, and for quantitative analysis, SERS has a reputation for unreliable reproducibility. UV resonance excitation, on the other hand, has the drawback that it requires cooling in a suspension,34 which makes it difficult to analyze defined individual cells in a population. In contrast, the method presented here works without surface enhancement and in a convenient excitation range at low laser power. Note that the spectra were obtained with accumulation times of 3 min only. It is important that the time for analysis of one individual cell is kept reasonably low; as for the final aim of characterizing the distribution in a bacterial population, a high number of cells has to be analyzed from each culture sample in order to get statistically relevant results. Complement to Other Single-Cell Analysis Methods. As we show in this study, the features of confocal Raman microspectroscopy make it a complement to existing methods for single-cell analysis: Flow cytometry1 and image cytometry2 are more sensitive to specific compounds and can analysis a higher number of cells in a given time. However, the need for specific staining chemistry limits the number of different information channels (to about 5-20 at this stage). The new mass spectrometric methods such as pyrolysis MS37 and MALDI-TOF MS5-7 are at the moment also more directed toward the detection of a few specific compounds rather than patterns (with the exception of organism identification,37 which is normally not done on the single-cell level), down to in situ sequencing of peptides in a whole cell.5 A global interpretation of MS data as patterns is rather difficult, due to the vast information content and also sometimes reproducibility problems, but it is possible with sophisticated chemometrics.37 With Raman spectra of single cells, the rich information content of each single-cell spectrum offers a global view of the overall composition of a cell, rather than specific (37) Shaw, A. D.; Winson, M. K.; Woodward, A. M.; McGovern, A. C.; Davey, H. M.; Kaderbhai, N.; Broadhurst, D.; Gilbert, R. J.; Taylor, J.; Timmins, E. M.; Goodacre, R.; Kell, D. B. In Bioanalysis and Biosensors for Bioprocess Monitoring; Scheper, T., Series Ed.; Sonnleitner, B., Vol. Ed.; Advances in Biochemical Engineering/Biotechnology Vol. 66; Springer: Berlin, Heidelberg, 2000; pp 83-113.
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detection of known compounds. This information comes as a pattern and is open to interpretation by chemometric methods in qualitative and quantitative ways, by the same mathematical tools as for other pattern-yielding analysis methods for biological samples, such as infrared spectroscopy, dielectric spectroscopy, and others,14,37 and as is done, for example, for organism identification.31,37 CONCLUSION AND OUTLOOK Confocal Raman microspectroscopy enables the analysis of single bacterial cells from biosuspensions. The developed method is of practical interest, as it requires only a very simple sample preparation consisting of washing the cells and drying on a calcium fluoride carrier. No chemical reagents are necessary to specifically mark cell components; the spectra contain multidimensional information on all major substance classes present in bacterial cells. Using excitation at 632.8 nm, sufficient sensitivity was obtained, hence avoiding somewhat troublesome or sophisticated techniques such as UV-excited resonance Raman or SERS. The lateral and axial resolution of spectral signals is in the range of 1-2 µm, which is sufficient to resolve single bacterial cells. The lower limit of cell size to obtain spectra of reasonable signalto-noise ratio depends on the carrier material on which the cells are presented. The results of this preliminary study are very promising as they demonstrate that the developed method is capable of assessing the heterogeneity within a bacterial cell population by providing spectral information on the chemical composition of single bacterial cells. Future research activities will be undertaken to gather more Raman data on single bacteria cells during a complete fermentation as well as to interpret the plentiful information from the spectra so that a deeper insight in the complex biochemical pathways in biotechnological processes can be gained. ACKNOWLEDGMENT The authors gratefully acknowledge Myriam Moreau, JobinYvon/Dilor, Lille, France, for technical assistance. The ABE fermentation work for this study was supported in part by the European Commission (Project AIR3-2153). K.C.S. was supported by the Austrian Science Foundation (Project 13686). Received for review June 21, 2000. Accepted September 6, 2000. AC000718X
