Direct analysis of bacterial glycerides by Curie-point pyrolysis—mass spectrometry

Journal of Analytical and Applied Pyrolysis, 23 (1992) 1-14 Elsevier Science Publishers B.V., Amsterdam

Direct analysis of bacterial glycerides by Curie-point pyrolysis-mass spectrometry Stephan J. DeLuca, Emory W. Sarver ’ and Kent J. Voorhees Department of Chemistry and Geochemistry, Colorado School of Mines, Golden, CO 80401 (USA) (Received

October

7, 1991; accepted

in final form December

12, 1991)

ABSTRACT Pyrolysis-mass spectrometry with pattern recognition has been used to characterize ten bacteria based on their glyceride distributions. Peaks have been identified which allow differentiation of triglycerides and phospholipids. Results are also presented which demonstrated that the phospholipids are thermally desorbed intact. Pattern recognition techniques showed that each genus had a characteristic distribution of glycerides. The results from this study are compared to a previously published Py-GC/MS study of glyceride distributions in bacteria. This comparison shows that direct Py-MS has similar capabilities for distinguishing bacteria based on glyceride distributions as the Py-GC/MS methods. Bacterial

glycerides;

Curie point; mass spectrometry;

pyrolysis.

INTRODUCTION

The distribution of cell membrane lipids in bacteria is commonly used for taxonomy [l-4]. The lipid analyses described in these studies normally require several steps including extraction, cleanup and chromatography. Mass spectrometry (MS) employing various sample introduction and ionization methods has been used for bacterial analysis without extensive sample preparation. The most utilized MS sample introduction method for whole bacterial cells has been pyrolysis, although fast atom bombardment (FAB) methods applied to whole cells have been recently shown to be useful for identifying microorganisms [5]. Vacuum pyrolysis near the ionizer (Py-MS) has been used with both electron ionization (El) and chemical ionization (CI). Because of convenience, Py-EIMS has been most widely used, although the spectra are generally quite complex and require pattern recognition techniques to aid in chemical interpretation of the data. The Correspondence to: K.J. Voorhees, Department of Chemistry and Geochemistry, School of Mines, Golden, CO80401, U.S.A. ’ Present address: US Army CRDEC, Aberdeen, MD 21010, U.S.A. 01652370/92/$05.00

0 1992 - El sevier Science

Publishers

Colorado

B.V. All rights reserved

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amount of information which can be extracted from the data below m/z 250 is limited because most of the components in this mass range are thermal fragments of bioprecursors. Electron ionization causes additional fragmentation that further complicates the spectra. Pyrolysis-CIMS has received less attention due to the difficulties in maintaining stable, uniform CI conditions during pyrolysis. Gas chromatography/mass spectrometry (GC/MS) allows separation and identification of distinct chemical compounds in the pyrolysate. Therefore, using Py-GC/MS, identification of specific cellular components (biomarkers) can be achieved. Holzer et al. used pyrolysis with in situ derivatization to obtain chromatographic profiles of fatty acid methyl esters (FAMES) from bacteria [6]. Recently, several saccharide-derived biomarkers have been identified by Py-GC in the pyrolysates of bacteria [7-91. Recently, Snyder et al. have shown Py-GC/MS useful in determining glyceride distributions in microorganisms [lo]. That study reported that glyceride distributions could be used to distinguish organisms based on visual inspection without the necessity of pattern recognition programs. Anhalt and Fenselau [ll] in 1975, using a direct insertion probe as a pyrolysis device, observed glycerides under EI conditions from whole bacterial cells. They visually differentiated six bacteria by comparing the glycerides and other peaks in the spectra between 190 and 750 u. More recently, Tas et al. [12,13] utilized pyrolysis with direct chemical ionization for analyzing whole bacteria. Although this group identified peaks in the 500-600 u range as glyceride fragments, the differentiation of the organisms was based on pattern recognition over the mass range m/z 70-700 which contained species other than glycerides. DeLuca et al. recently reported on the identification of glycerides by Curie-point Py-EIMS/MS [14]. The major emphasis of the study was to demonstrate that fatty acid profiles could be extracted from pyrolysis-E1 mass spectra, and that these profiles could be used to distinguish bacteria. The glyceride distributions from whole bacterial cells were also shown; however, a comprehensive study of these profiles for taxonomical purposes was not reported. The following study focused on the use of Curie-point Py-EIMS to characterize bacteria based on glyceride distributions. Py-MS and PyGC/MS experiments were conducted on standard phospholipids and triglycerides to understand their thermal degradation characteristics. Whole bacteria were then analyzed by Py-MS followed by multivariate statistical analysis of the data. EXPERIMENTALSECTION Samples

A sample set comprising ten strains representing six bacterial species was used in this study. Freeze dried samples of Bacillus licheniformis (BL)

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3

(BOO17and B0089), Bacillus subtilis (BS)(B0014 and B0095), Bacillus cereus (BC)(B0037 and B0002), Bacillus thuringiensis (BT), Staphylococcus aureus (SA), and Escherichia coli (EC) (00127 and NCTC 10418) comprised the sample set. Several of the bacteria were in a sporulated phase. These included BL (B0017), BS (B0095), BC (B0037) and BT. The phospholipid and triglyceride standards for the study were obtained from Sigma Chemical Co., St. Louis, MO. Samples for both Py-MS and Py-GC/MS were prepared by suspending approximately 8 mg of the freeze-dried organisms in 2 ml of methanol. The suspensions were sonicated for 5 s to disperse the cells. Five microliters of the cell suspension were then applied to a 610°C Curie-point wire and the solvent evaporated under a hot air stream. Coating of the wires and analyses was done in a randomized order. For Py-MS studies, three replicates were run for each sample. Instrumentation

An Extrel model EL-400 triple quadruple mass spectrometer was used for the Py-MS and Py-GC/MS studies. The MS was fitted with both a Curie-point pyrolysis inlet [14] and a capillary column interface connected to a Varian 4000 gas chromatograph. All spectra were collected using 70 eV electron ionization. For Py-MS, ten individual mass spectra collected for about 6 s over a mass range 450-650 were summed to produce a Py-mass spectrum. In this limited mass range, the chemically significant peak intensities did not vary as drastically as they did in the full scan (m/z 50-600) spectrum. The wires used for the Py-MS studies were 610°C and the quartz tube transfer line connecting the pyrolyzer to the ion source was heated to 425°C. Pyrolysis-GC/MS was accomplished by interfacing an aluminum-clad 15 m x 0,250 mm internal diameter, 100% methyl silicone column (Quadrex Corp.) with a Curie-point pyrolysis GC inlet. During pyrolysis, the GC column was held at 100°C. Immediately after the 5 s pyrolysis, the oven was heated to 390°C at 20°C min-‘. The interface was held at 400°C. PyrolysisGC experiments were conducted using 610°C wires. The pyrolysate from approximately 2 pg of standard was split 10: 1, loading about 200 ng onto the analytical column. A mass range of 45-650 u was used in the study. The mass spectral identification of individual species was made by comparing the experimental spectra to the NIH/EPA library. Data analysis

Pattern recognition procedures were conducted using the RESOLVE program [15]. Each Py-MS spectrum was normalized to constant length [16]. Equal results were obtained when the data was run with and without

S.J. DeLuca et al. /J. Anal. Appl. Pyrolysis 23 (1992) 1-14

4

autoscaling. The data for this report was not autoscaled. Therefore, following normalization, the spectra were subjected directly to principal components analysis [17] and supervised rotations [18]. This form of rotation maximized the Fisher distance between the scores of a given category and those of other spectra, producing an oblique linear discriminant for each bacterial class. The results, displayed as score plots [17], show the projections of the samples on the rotated factors. On those score plots, the discriminant vectors are rotated such that a line can be drawn, perpendicular to the factor axis, which separates all replicates of one category from all other samples. The factor spectra (i.e. the projection of the mass spectral peaks) are generated using the loadings [17] on the rotated component axes.

RESULTS AND DISCUSSION

Pyrolysis of glyceride standards

It has been reported by several authors that pyrolysis of phospholipids produces dehydrated diglycerides [10,11,14]. For example, pyrolysis of a dipalmitoyl phospholipid would produce structure I with a molecular weight of 550 D. DeLuca et al. suggested in a previous study [14] that triglycerides can be desorbed essentially intact, and upon 70 eV electron ionization give well-known fragments such as structure II with a molecular weight of 551 D for the dipalmitoyl fragment. A more systematic study,

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involving Py-MS and Py-GC/MS, of the pyrolysis of triglycerides and phospholipids was conducted. A set of triglyceride and phospholipid standards, including tricaprylin (03 : 0) (for Cx : y, x is the number of carbon atoms, y is the number of double bonds), tricaprin (ClO: 01, trilaurin (Cl2 : 01, trimyristin (Cl4 : 01, tripalmitin (Cl6 : 01, dipalmitoylstearin (Cl6 : 0; 16 : 0; 18 : O), l-palmitoyl-2-oleoyl-3-stearoyl-rat-glycerol (Cl6 : 0; 18 : 1; 18 : 01, oleoyldistearin (Cl8 : 1; 18 : 0; 18 : 01, y-palmitoyl-P-oleoyl-Lcr-phosphatidyl-choline (16 : 0; 18 : 1 PC), p-oleoyl-y-stearoyl-r-a-phosphatidyl-choline (18 : 0; 18 : 1 PC), and P-oleoyl-y-stearoyl-r-a-phosphatidylethanolamine (18 : 0; 18 : 1 PE), and y-palmitoyl+oleoyl-r_-cY-phos-

S.J. DeLuca et al. / J. Anal. Appl. Pyrolysis 23 (1992) l-14

5

607 395

383

350

370

I

390

18:o7 le:l_l CH2+

452 I 410

430

450

I// II 470

490

510

530

550

570

590

610

m/z

Fig. 1. Pyrolysis-mass

spectrum of the CM: 1; 18:O; 18:0 triglyceride.

phatidylethanolamine (16: 0; 18: 1 PE) were run by Py-MS and PyGC/MS. The Py-MS results showed the expected fragmentation patterns. Figure 1 is the Py-mass spectrum of the Cl8 : 1, 18: 0; 18: 0 triglyceride. The peak at m/z 605 corresponds to the loss of a Cl8 : 0 side chain while the peak at m/z 607 is formed by loss of the C18: 1 side chain. Analogous peaks are shown in Fig. 2 for a C16: 0; 18: 1; 18 :0 triglyceride. Loss of each of the side chains by inductive cleavage results in peaks at m/z 577, 579 and 605. The spectra of phospholipids are similar to those of triglycerides; however, the diacylglycerol fragments appear at even masses. For example, Fig. 3 shows the Py-mass spectrum of the 16 : 0; 18 : 1 PE. The peak at m/z 576 is the 18: 1; 16: 0 glyceride analogous to structure I. Likewise the 18: 0; 18: 1 PC sample gives a peak at m/z 604 (Fig. 4). The 18: 1; 16: 0 PC also gave a peak at m/z 576; however, the spectra in the 300-400 u range were quite different for PE and PC. If the pyrolysis event was producing a diglyceride from the phospholipid, then the spectra should be identical in this mass region. A pyrolysis-gas chromatogram of a mixture of triglycerides (tricaprylin, tricaprin, trilaurin, trimyristin, tripalmitin, dipalmitoylstearin, l-palmitoyl2-oleoyl-3-stearoyl-rat-glycerol) and the four phospholipids is shown in Fig. 5. All of the chromatographic peaks were assigned to triglycerides, based on the presence of odd-mass diacylglycerol moieties (structure II type). If the phospholipids were converted to diglycerides upon pyrolysis, we would

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Fig. 2. Pyrolysis-mass

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spectrum of the C16:O; 18: 1; 18:0 triglyceride.

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590

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610

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S.J. DeLuca et al. /J. Anal. Appl. Pyrolysis 23 (1992) 1-14

6

.. .

I 510

Fig. 3. Pyrolysis-mass =2x).

,. 1

I., I 1 530

I 550

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spectrum of the C16:O; 18: 1 PE phospholipid

(relative intensity

expect to see distinct chromatographic peaks with even-mass diacylglycerol peaks (structure I type). The lack of diglyceride peaks in the chromatogram could be explained by evaporation of the intact phospholipid. These species would not migrate through a GC column and thus would be observed by the MS. Enke and Cole [19] have recently corroborated this hypothesis. They observed molecular ion adducts for phospholipids from direct-probe Py-CI MS. Enke and Cole [19] noted that the molecular species decreased with prolonged pyrolysis. Based on this observation, it is possible that the even-mass diacylglycerol fragments are products of electron ionization rather than pyrolysis. It is difficult to reconcile these observations with those of Snyder et al. [lo] who showed similar Curie-point (610°C 1 s) pyrolysis chromatographic profiles for dipalmitin and dipalmitoyl-phosphatidyl dimethylethanolamine. Pyrolysis conditions may play an important role in determining which species are liberated. In any case, it is evident that Py-MS has the capability of determining glyceride distributions in the same manner as for fatty acids [14]. Once the characteristic glyceride peaks for standards were established in the Curie-point Py-mass spectra, the utilization of these peaks for bacterial identification was initiated. Pattern recognition of glyceride distributions

Figure 6 shows replicate Py-mass spectra for B. licheniformis (BOO171in the mass range 450-650 u. When examining the reproducibility of the

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Fig. 4. Pyrolysis-mass

spectrum of the Cl8 : 0; 18 : 1 PC phospholipid.

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S.J. DeLuca et al. / J. Anal. Appl. Pyrolysis 23 (1992) 1-14

7

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SCAN NUMBER

Fig. 5. A pyrolysis-gas

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of a standard

triglyceride

and phospholipid

M/Z Fig. 6. Replicate

pyrolysis-mass

spectra

of B. licheniformis (B0017).

mixture.

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S.J. DeLuca et al. / J. Anal. Appl. Pyrolysis 23 (1992) 1-14

spectra, it should be emphasized that the signal to noise ratio for even the most intense peaks was about 10: 1. Detailed comparison of the spectra on a peak-by-peak basis is therefore difficult. However, even simple visual inspection of the general patterns (Fig. 7) shows that discrimination is possible at least to the genus level.

551

1 I

Fig. 7. Pyrolysis-mass

spectra of bacteria.

Bacaus cemus BOO02

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S.J. DeLuca et al. / J. Anal. Appl. Pyrolysis 23 (1992) 1-14

The rotated score plot in Fig. S(a) shows an oblique linear discriminant model with excellent separation of different bacterial genus. The axis labelled variables b and s represent linear combinations of the original masses with the coordinate system rotated to more clearly reveal discrimination among the selected groups. The points on this graph marked e, s,

BociUus lichenifomis BOO89

M/Z

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5so

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Bacihs 507

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BOO14 5p

Bacillus subtilis Spores

M/Z

M/Z Fig. 7 (continued).

10

S.J. DeLuca et al. /J. Anal. Appl. Pyrolysis 23 (1992) l-14

M/Z Fig. 7 (continued).

and b represent the individual Py-mass spectra plotted on the corresponding axes. These axes (score values) increase in a positive direction toward the right for variable b and toward the top for variable s. Cross validation of this model produced 100% correct predictions. The factor spectra associated with this model (Fig. S(b)) show positive correlation of peaks at m/z 565, 579, 592, 607, 621 and 634 with the genus Staphylococcus. Peaks at m/z 563, 576, 590 and 603 were correlated with Escherichia. The major peak correlated with Bacillus was m/z 523. These correlations are consistent with visual inspection of the raw spectra. Separation of the Bacillus species from one another could not be accomplished with the supervised pattern recognition techniques employed. Figure 9 shows a typical plot where in this case separation of B. subtilis and B. cereus are displayed. When the sporulated organisms were grouped together, a clear separation of these organisms from the nonsporulated Bacilli was achieved (Fig. 10). The major peaks correlated with the sporulated organisms were m/z 522 and 523. It appears that upon sporulation the organisms become enriched in the glycerides having Cl5 : 0; 15 : 0 or Cl4 : 0; 16 : 0 diacyl moieties. Others have reported changes in the Cl4 and Cl5 fatty acids distribution during sporulation [20,21]. Comparison of Py-MS and Py-GC/MS

results

A recent report by Snyder et al. [lo] showed glyceride distributions, obtained using short column capillary Py-GC/MS, for several bacterial species. In that paper, plots of “reconstructed ion chromatograms (RIG) intensity distributions of selected masses” are shown. These plots provide essentially equivalent information to the normalized Py-mass spectra shown in Figs. 6 and 7. The same generalizations can be made about the discriminatory abilities of the glyceride distributions with direct Py-MS as those with Py-GC/MS. On a peak-by-peak comparison, however, some discrepancies are evident. The glyceride distribution for E. cofi showed no peaks above m/z 550 with Py-GC/MS. With Py-MS, the E. co/i samples

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S.J. DeLuca et al. / .l. Anal. Appl. Pyrolysis 23 (1992) 1-14

8

e e

eee

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-0.29

-0.22

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Escherichia

603

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CO

M/Z Fig. 8. (Upper) An obliquely rotated score plot (e = Escherichia, Staphylococcus). (Lower) Factor spectra associated with upper plot.

b = Bacillus, and s =

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S.J. DeLuca et al. /J. Anal. Appl. Pyrolysis 23 (1992) 1-14

VARIAEILE c Fig. 9. An obliquely rotated score plot of the various Bacillus species s = B. subtilis, t = B. thuringiensis, and c = B. cereus).

(L = B. licheniformis,

show peaks well above 600 u and included m/z 564 and 578. S. aureus produced peaks at m/z 536 and 578, although these peaks were evidently not detected by Py-GC/MS. Except for two bacteria which were not investigated in this study, an upper mass limit of m/z 550 was observed for the seven bacteria in the Py-GC/MS study [lo]. The added chromatographic dimension does not appear to add significant information over direct Py-MS. With Py-MS, using a supervised pattern recognition approach, the B. licheniformis (BOO891and B. subtilis (BOO141samples could be distinguished (Fig. 10) while with Py-GC/MS [lo] the chromatographic profiles shown (i.e. “lipid TIC” and “representa-

-0.3

-0.21

a13

0.042

-0.043

VAIUAEILE

0.13

g

Fig. 10. An obliquely rotated score plot showing separation of sporulated Bacillus from other Bacillus species (g = sporulated, L = B. lichenifonnis, s = B. subtilis, and c = B. cereus).

S.J. DeLuca et al. / J. Anai. Appl. Pyrolysis 23 (1992) I-14

13

tive RIG”) for these organisms were indistinguishable. The Py-GC/MS approach did distinguish between some of the sporulated organisms that could be separated by supervised pattern recognition procedures with the Py-MS data.

CONCLUSIONS

The ability of Curie-point Py-MS to determine glyceride distributions from whole bacterial cells has been demonstrated. These distributions consist of diacylglycerol fragments from triglycerides as well as phospholipids. Different genera of bacteria are easily distinguished by these distributions; however, distinguishing species within a genus is not always possible. Evidence of sporulation of Bacillus organisms is seen in the relative intensities of peaks at m/z 522 and 523. Finally, although limited data exist for the two techniques, direct Py-MS appears to have similar capabilities for distinguishing bacteria (based on glyceride distributions) to the published Py-GC/MS method [lo].

ACKNOWLEDGMENTS

The authors would like to acknowledge the financial support of Teledyne CME. E.W.S. would also like to thank the U.S. Army for a Secretary of Army Fellowship.

REFERENCES 1 2 3 4 5 6 7 8 9 10 11

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