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Pyrolysis-tandem mass spectrometry of bacteria
Journaf of Anuiytical and Applied P~ro~sjs, 14 (1988) 7-15 Elsevier Science Publishers B.V., Amsterdam - Printed in The Netherlands
PYROLYSIS-TANDEM
KENT J. VOORHEES
MASS
* and STEVEN
SPECTROMETRY
L. DURFEE
Department of Chemistry and Geochemistty, CO 80401 (U.S.A.) JAMES
OF BACTERIA
Colorado School of Mines, Golden,
R. HOLTZCLAW
Brunswick
Defense, 9509 International
Court, St. Petersburg, FL 33716 (U.S.A.)
C.G. ENKE and MARK R. BAUER Department
of Chemistry,
Michigan State University, East L.ansing, MI 48824 (U.S.A.)
(Received February 23rd, 1988; accepted May 9th, 1988)
ABSTRACT Curie-point pyrolysis-tandem mass spectrometry has been applied to three bacteria, Escheri~h~a co/i, Bacii~~ cereus and Bacillus subt~~is. Parent ion scans, neutral loss and daughter ion scans were used. Based on the results from the three bacteria, parent ion scans of daughter ions selected by pattern recognition techniques provided the best data for identification of the three bacteria. The utility of combining pyrolysis-mass spectrometry with the chemical noise reduction of tandem mass spectrometry is demonstrated. Baciilus cereus; BaciIIus subtilis; tandem mass spectrometry.
bacteria;
Escherichia
coli; mass spectrometry;
pyrolysis;
INTRODUCTION
Pyrolysis-mass spectrometry (Py-MS) has been extensively utilized for classifying bacteria [1,2]. Because of the complex spectra obtained from Py-MS, pattern recognition techniques are usually required to interpret the data. In a recent study [3] involving a diverse bacteria set, it was reported that Py-MS using factor analysis [4] with graphical rotation [5] was successful in identifying a large percentage of the single organisms, provided that the data set did not exceed more than 20 samples. At that point, the complexity of the data set exceeded the capability of the pattern recognition approach. 0165-2370/88/$03.50
0 1988 Elsevier Science Publishers B.V.
For the Py-MS technique to be applicable to larger data sets, a procedure must be employed to reduce the redundancy (chemical noise) in the data. Pyrolysis with gas chromatography has been shown to provide this type of selectivity. Morgan and co-workers [6] reported that unique gas chromatographic peaks were produced in the pyrolysis of groups A and B streptococci. The biomarker of group B has been partially identified as arising from glucitol phosphate which was part of a cell surface antigen. This study has shown that a unique compound was produced for group B but not in groups A, C, G and F streptococci strains. Single stage analyzer Py-MS does not provide the separation capability necessary to take full advantage of using unique compounds for bacterial differentiation. One way to combine the positive aspects of Py-MS, such as sensitivity, rapid analysis and data format, with a necessary separation capability, is through employment of tandem mass spectrometry. Pyrolysis-tandem mass spectrometry (Py-MS/MS) provides three common scanning modes: neutral loss scans, parent ion scans and daughter ion scans [7]. The chief limitation of a single stage analyzer Py-MS is that each peak in the spectrum may arise from several different pyrolysis products and is not unique to any sample. The three MS/MS scanning modes, in principle, provide capabilities similar to gas chromatography in eliminating the previously listed drawbacks. This paper presents data for the pyrolysis of three bacteria to show the utility of Py-MS/MS and the selectivity offered by the various MS/MS scan modes.
EXPERIMENTAL
Samples Bacillus cereus, Bacillus subtilis and Escherichia coli grown on trypticase soy agar in petri dishes were used in the study. Samples were prepared for pyrolysis by removing about 50 mg of bacteria directly from the plate onto the pyrolysis wire. Instrumentation A Curie-point gas chromatographic inlet [8] was coupled directly to the ion source of a tandem mass spectrometer with a 4 m x 0.25 mm I.D. methyl silicone fused silica column. The size and length of the column were selected to provide a pressure drop that would produce the proper leak rate for several seconds of data acquisition while minimizing chromatographic separation. The internal portion of the pyrolysis device was heated to 310°C while the transfer line was heated to 250 ’ C. A Fisher power supply (1.1 kW and 750 kHz) and 510°C wires were used in the study.
9
The Extrel triple quadrupole mass spectrometer was operated in a chemical ionization mode. Methane chemical ionization (CI) reagent gas was used to sweep the pyrolysate from the pyrolysis inlet through the fused silica column and into the ion source. The use of helium to sweep the pyrolysate into the column with separate introduction of the methane reagent gas into the ion source resulted in poorer sensitivity. This loss in sensitivity could result from a competition between charge transfer ionization and chemical ionization. Argon was introduced as a collision gas into the second quadrupole at a pressure which produced the maximum abundance of daughter ions from perfluorotributylamine. Parent ion, daughter ion and neutral loss mass spectra were recorded for each bacterium. Neutral scan loss and parent ion scans were run as previously described f7]. Two daughter ion scan modes were used in this study. Daughter ion mode I was a total daughter ion scan in which quadrupole 1 was run in an rf only mode, quadrupole 2 was used as the collision region and quad~pole 3 was scanned. Daughter ion scan mode II was the traditional method of obtaining daughter ions from specific masses [7]. Spectra were collected and stored as individual scans in the range of lo-240 amu. Pyrolysis spectra were produced by summing 30 scans. Three replicates were run on each bacterium. Representative Py-CI mass spectra were obtained by operating the triple quadrupole mass spectrometer as a single analyzer. Data calculations Factor analysis with graphical rotation [9,10] was used to analyze the total daughter ion spectra (daughter ion scan mode I). The details of the pretreatment of the data have been previously described [ll]. The factor spectra generated during the rotation were later used to determine the peaks for subsequent parent ion studies.
RESULTS
AND DISCUSSION
The most common method of ionization used with Py-MS has been low voltage electron ionization (EI). However, the mass spectrometer utilized for this study did not provide adequate sensitivity when operated in the MS/MS mode with low voltage EI. After evaluating both 70-eV EI and methane chemical ionization for maximum sensitivity, the CI mode was selected. The CI spectra demonstrated a IO-fold improvement in sensitivity and exhibited more ions above 200 amu when compared to 70-eV EI spectra. The CI Py-mass spectra for B. cereus, B. ~u~til~~ and E. coli are illustrated in Fig. 1. The spectra were found to have good reproducibility. Visual examination of the three spectra revealed several peaks which could be used to discriminate between the three organisms. These peaks, typically
8. CEREUS
60
80
100
2,
120
140
160
18%
M/Z
f%-
220
24E*
t 8.
,s
Fig. 1. CI F’y-mass
200
SUBTILIS
8 3
spectra
of B. cereus, B. subtilis and E. coli.
large in one sample and minor in the other two, were used to generate daughter ion (scan mode II) mass spectra. Table 1 summarizes the selected parent ions plus the corresponding daughter ion spectra. Relative abundances for the daughter peaks have not been listed in the table, primarily because of the poor reproducibility of the absolute magnitude of the daughter ion peak intensities. In general, the daughter ion spectra from the same parent ion for each of the three bacteria were very similar and were not unique for any of the three organisms. The daughter ion peaks, as indicated in Table 1, were very sparse and in many cases only a single daughter ion peak was observed. The observed daughter ion peaks could be used in some cases for tentative identification of the parent ions. For example, the m/z 75 parent ion appears to fragment in a manner similar to butanol, while m/z 93 parent
11 TABLE 1 Daughter ions for selected parent ions Parent ion 75 81 93 100 104 113 118 136 164
Minor daughter ions
Major daughter ions B. cereus
E. coli
B. subtilis
57 53 91 72 58 95,85 91 94 98,84
51 53 91 72 58 95,85 91 94 98,84
57 53 91 72 58 95, 85 91 94 98,84
B. cereus
E. coli
B. subtih
45,29 71,57 82, 55, 44
82, 55,44
82, 55, 44
96, 72, 43
96, 72,43
96, 72, 43
108 116,44
108 44
108
ion is probably protonated toluene which fragments to a tropylium ion. It is interesting to note that the paucity of daughter peaks suggests that the daughters are often formed from single parent ions. The major step in performing parent ion scans is to determine which daughter ions will be used in the analysis. Data obtained from daughter ion scan mode I, which consists of the summation of all daughter ions produced from all parent ions, was subjected to factor analysis and graphical rotation. Using the first two factors, rotations were performed to maximize the separation of each indi~dual group in the positive direction. Fig. 2 illustrates the final rotation position of B. cc~eus. The reproducibility of the analysis is shown in the figure by the distance between replicates and the distance between different organisms. Factor spectra for each of the individual bacteria were calculated from the factor loadings. Fig. 3 shows these spectra. The large positive peaks in the factor spectra represent those peaks which are positively correlated with the characteristics that allowed separa-
b b
b
KL
oroieotfon for B. eereus a a
c
a
c
c
Fig. 2. Factor-factor coli.
plot (KL plot) of three bacteria. a = 3. cereus, b = B. subtiiis and c = E.
12
60
I
Fig. 3. Factor
spectra
of the three bacteria.
4
59
I
j
B. cereus
73 100
IIIIII1
1,
IIIII
114 I I, ,#I, , ,, ; , ,b , , , ,
50
70
90
110
130
150
170
50
70
90
110
130
150
170
Fig. 4. Parent ion spectra
for daughter
ion m/r
58.
13
E. coli
70
90
110
130
150
170
210
190
Fig. 5. Parent ion spectra for daughter ion m/z 84. E. coii
127
144 120
140
156 II 160
16g I
186 I 180
200 III, 200
127
8. cereus
127
8. subtilis
220
240
150
Fig. 6. Parent ion spectra for daughter ion m/z
127.
I
14 TABLE 2 Diagnostic daughter peaks used for parent ion scans B. cereus
B. subtilis
E. coli
60 63 81 96 110 136
58 84 104 117 118 144 145
70 77 84 95 113 127 130
tion of each bacterium. Table 2 lists the prominent peaks observed in the factor spectra for each bacterium. Parent ion scans were performed using the peaks listed in Table 2. Figs. 4-6 show some of the parent ion spectra obtained. Not all of the peaks listed in Table 2 were diagnostic; however, the degree of complexity and selectivity of the data were dramatically improved by parent ion scanning when compared to the Py-CIMS data. The spectra shown in Figs. 4-6 were distinct enough that identification of the three bacteria can be easily made based on one or two peaks without the need of pattern recognition. In the case of the parent ions from the m/z 58 and 84 daughter ions, major changes in the spectra were observed (increase in intensity of m/z 104 parent ion for the 58 daughter ion and the m/z 144 parent ion for the 84 daughter ion). The changes of intensities in the parent scans for other ions were more subtle. For example, the parent scans for the m/z 127 daughter ion produced a small peak at m/z 142 for B. ccreus. This peak was absent in the other bacteria. We recognize that the degree of success of the parent ion scan mode in identifying individual bacteria is probably overemphasized because of the small data set. However, despite the limited amount of data, there are several points that can be generalized from this work. Daughter ions produced from the major peaks in the single stage Py-mass spectra in the mass range studied were not unique (Table 1). This means that parent ions producing these daughter ions were similar for all three bacteria and probably represent thermodynamically stable compounds. Larger data sets will only add complications to the daughter ion results. Improved means of identifying parent ions possessing unique structures must be employed if the daughter ion scans are to be useful. Identification of these parent ions could be achieved using the gas chromatographic techniques of Morgan [6] or perhaps by studying parent ions of higher mass (i.e. over 200 amu). High mass ions were not used in the present study because of the limited transfer capabilities for high mass compounds of our experimental configuration. For future studies involving high mass parent
15
ions, the pyrolysate must be introduced either directly into the ion source or through an improved transfer line and instrument configuration. Diverse high molecular weight compounds ( > 600 dalton) have been eluted from gas chromatographic columns [12]. The relative intensities for some of the daughter ion peaks were different between species, but the general sparseness of daughter ions severely limits application of pattern recognition techniques. Parent ion scans, whether or not they are totally unique, provided the elimination of redundancy necessary to apply Py-MS to large data sets. In summary, the results from this study clearly demonstrate the potential utility of combining Py-MS with the chemical noise reduction capabilities of tandem mass spectrometry. These results further suggest that parent ion scans produce useful data for classifying bacteria.
ACKNOWLEDGEMENT
The authors wish to thank CRDEC, Aberdeen Proving Grounds, Maryland, contract # DAAG29985-K-0199 and Brunswick Defense (formerly Honeywell CDC) for their support of this work.
REFERENCES 1 W.J. Irwin, Analytical Pyrolysis; A Comprehensive Guide, Marcel Dekker, New York, 1982. 2 H.L.C. Meuzelaar, J. Haverkamp and F.D. Hileman, Pyrolysis-Mass Spectrometry of Recent and Fossil Biomaterials, A Compendum and Atlas, Elsevier, Amsterdam, 1982. 3 K.J. Voorhees, S.L. Durfee and D.M. Updegraff, J. Microbial. Methods, in press. 4 E.R. Malinowsky and D.G. Howery, Factor Analysis in Chemistry, Wiley-Interscience, New York, 1980. 5 R.J. Rummel, Applied Factor Analysis, Northwestern University Press, Evansville, IN, 1970. 6 C.S. Smith, S.L. Morgan, CD. Parks, A. Fox and D.G. Pritchard, Anal. Chem., 59 (1987) 1410. 7 R.A. Yost and C.G. Enke, Anal. Chem., 51 (1979) 1251A. 8 J.W. de Leeuw, W.L. Maters, D.v.d. Meent and J.J. Boon, Anal. Chem., 49 (1977) 1181. 9 W. Windig and H.L.C. Meuzelaar, Anal. Chem., 56 (1984) 2297. 10 K.J. Voorhees and R. Tsao, Anal. Chem., 57 (1985) 1630. 11 R. Tsao and K.J. Voorhees, Anal. Chem., 56 (1984) 368. 12 H.L.C. Meuzelaar, W. McClennen and P. Synder, University of Utah, unpublished results.
PYROLYSIS-TANDEM
KENT J. VOORHEES
MASS
* and STEVEN
SPECTROMETRY
L. DURFEE
Department of Chemistry and Geochemistty, CO 80401 (U.S.A.) JAMES
OF BACTERIA
Colorado School of Mines, Golden,
R. HOLTZCLAW
Brunswick
Defense, 9509 International
Court, St. Petersburg, FL 33716 (U.S.A.)
C.G. ENKE and MARK R. BAUER Department
of Chemistry,
Michigan State University, East L.ansing, MI 48824 (U.S.A.)
(Received February 23rd, 1988; accepted May 9th, 1988)
ABSTRACT Curie-point pyrolysis-tandem mass spectrometry has been applied to three bacteria, Escheri~h~a co/i, Bacii~~ cereus and Bacillus subt~~is. Parent ion scans, neutral loss and daughter ion scans were used. Based on the results from the three bacteria, parent ion scans of daughter ions selected by pattern recognition techniques provided the best data for identification of the three bacteria. The utility of combining pyrolysis-mass spectrometry with the chemical noise reduction of tandem mass spectrometry is demonstrated. Baciilus cereus; BaciIIus subtilis; tandem mass spectrometry.
bacteria;
Escherichia
coli; mass spectrometry;
pyrolysis;
INTRODUCTION
Pyrolysis-mass spectrometry (Py-MS) has been extensively utilized for classifying bacteria [1,2]. Because of the complex spectra obtained from Py-MS, pattern recognition techniques are usually required to interpret the data. In a recent study [3] involving a diverse bacteria set, it was reported that Py-MS using factor analysis [4] with graphical rotation [5] was successful in identifying a large percentage of the single organisms, provided that the data set did not exceed more than 20 samples. At that point, the complexity of the data set exceeded the capability of the pattern recognition approach. 0165-2370/88/$03.50
0 1988 Elsevier Science Publishers B.V.
For the Py-MS technique to be applicable to larger data sets, a procedure must be employed to reduce the redundancy (chemical noise) in the data. Pyrolysis with gas chromatography has been shown to provide this type of selectivity. Morgan and co-workers [6] reported that unique gas chromatographic peaks were produced in the pyrolysis of groups A and B streptococci. The biomarker of group B has been partially identified as arising from glucitol phosphate which was part of a cell surface antigen. This study has shown that a unique compound was produced for group B but not in groups A, C, G and F streptococci strains. Single stage analyzer Py-MS does not provide the separation capability necessary to take full advantage of using unique compounds for bacterial differentiation. One way to combine the positive aspects of Py-MS, such as sensitivity, rapid analysis and data format, with a necessary separation capability, is through employment of tandem mass spectrometry. Pyrolysis-tandem mass spectrometry (Py-MS/MS) provides three common scanning modes: neutral loss scans, parent ion scans and daughter ion scans [7]. The chief limitation of a single stage analyzer Py-MS is that each peak in the spectrum may arise from several different pyrolysis products and is not unique to any sample. The three MS/MS scanning modes, in principle, provide capabilities similar to gas chromatography in eliminating the previously listed drawbacks. This paper presents data for the pyrolysis of three bacteria to show the utility of Py-MS/MS and the selectivity offered by the various MS/MS scan modes.
EXPERIMENTAL
Samples Bacillus cereus, Bacillus subtilis and Escherichia coli grown on trypticase soy agar in petri dishes were used in the study. Samples were prepared for pyrolysis by removing about 50 mg of bacteria directly from the plate onto the pyrolysis wire. Instrumentation A Curie-point gas chromatographic inlet [8] was coupled directly to the ion source of a tandem mass spectrometer with a 4 m x 0.25 mm I.D. methyl silicone fused silica column. The size and length of the column were selected to provide a pressure drop that would produce the proper leak rate for several seconds of data acquisition while minimizing chromatographic separation. The internal portion of the pyrolysis device was heated to 310°C while the transfer line was heated to 250 ’ C. A Fisher power supply (1.1 kW and 750 kHz) and 510°C wires were used in the study.
9
The Extrel triple quadrupole mass spectrometer was operated in a chemical ionization mode. Methane chemical ionization (CI) reagent gas was used to sweep the pyrolysate from the pyrolysis inlet through the fused silica column and into the ion source. The use of helium to sweep the pyrolysate into the column with separate introduction of the methane reagent gas into the ion source resulted in poorer sensitivity. This loss in sensitivity could result from a competition between charge transfer ionization and chemical ionization. Argon was introduced as a collision gas into the second quadrupole at a pressure which produced the maximum abundance of daughter ions from perfluorotributylamine. Parent ion, daughter ion and neutral loss mass spectra were recorded for each bacterium. Neutral scan loss and parent ion scans were run as previously described f7]. Two daughter ion scan modes were used in this study. Daughter ion mode I was a total daughter ion scan in which quadrupole 1 was run in an rf only mode, quadrupole 2 was used as the collision region and quad~pole 3 was scanned. Daughter ion scan mode II was the traditional method of obtaining daughter ions from specific masses [7]. Spectra were collected and stored as individual scans in the range of lo-240 amu. Pyrolysis spectra were produced by summing 30 scans. Three replicates were run on each bacterium. Representative Py-CI mass spectra were obtained by operating the triple quadrupole mass spectrometer as a single analyzer. Data calculations Factor analysis with graphical rotation [9,10] was used to analyze the total daughter ion spectra (daughter ion scan mode I). The details of the pretreatment of the data have been previously described [ll]. The factor spectra generated during the rotation were later used to determine the peaks for subsequent parent ion studies.
RESULTS
AND DISCUSSION
The most common method of ionization used with Py-MS has been low voltage electron ionization (EI). However, the mass spectrometer utilized for this study did not provide adequate sensitivity when operated in the MS/MS mode with low voltage EI. After evaluating both 70-eV EI and methane chemical ionization for maximum sensitivity, the CI mode was selected. The CI spectra demonstrated a IO-fold improvement in sensitivity and exhibited more ions above 200 amu when compared to 70-eV EI spectra. The CI Py-mass spectra for B. cereus, B. ~u~til~~ and E. coli are illustrated in Fig. 1. The spectra were found to have good reproducibility. Visual examination of the three spectra revealed several peaks which could be used to discriminate between the three organisms. These peaks, typically
8. CEREUS
60
80
100
2,
120
140
160
18%
M/Z
f%-
220
24E*
t 8.
,s
Fig. 1. CI F’y-mass
200
SUBTILIS
8 3
spectra
of B. cereus, B. subtilis and E. coli.
large in one sample and minor in the other two, were used to generate daughter ion (scan mode II) mass spectra. Table 1 summarizes the selected parent ions plus the corresponding daughter ion spectra. Relative abundances for the daughter peaks have not been listed in the table, primarily because of the poor reproducibility of the absolute magnitude of the daughter ion peak intensities. In general, the daughter ion spectra from the same parent ion for each of the three bacteria were very similar and were not unique for any of the three organisms. The daughter ion peaks, as indicated in Table 1, were very sparse and in many cases only a single daughter ion peak was observed. The observed daughter ion peaks could be used in some cases for tentative identification of the parent ions. For example, the m/z 75 parent ion appears to fragment in a manner similar to butanol, while m/z 93 parent
11 TABLE 1 Daughter ions for selected parent ions Parent ion 75 81 93 100 104 113 118 136 164
Minor daughter ions
Major daughter ions B. cereus
E. coli
B. subtilis
57 53 91 72 58 95,85 91 94 98,84
51 53 91 72 58 95,85 91 94 98,84
57 53 91 72 58 95, 85 91 94 98,84
B. cereus
E. coli
B. subtih
45,29 71,57 82, 55, 44
82, 55,44
82, 55, 44
96, 72, 43
96, 72,43
96, 72, 43
108 116,44
108 44
108
ion is probably protonated toluene which fragments to a tropylium ion. It is interesting to note that the paucity of daughter peaks suggests that the daughters are often formed from single parent ions. The major step in performing parent ion scans is to determine which daughter ions will be used in the analysis. Data obtained from daughter ion scan mode I, which consists of the summation of all daughter ions produced from all parent ions, was subjected to factor analysis and graphical rotation. Using the first two factors, rotations were performed to maximize the separation of each indi~dual group in the positive direction. Fig. 2 illustrates the final rotation position of B. cc~eus. The reproducibility of the analysis is shown in the figure by the distance between replicates and the distance between different organisms. Factor spectra for each of the individual bacteria were calculated from the factor loadings. Fig. 3 shows these spectra. The large positive peaks in the factor spectra represent those peaks which are positively correlated with the characteristics that allowed separa-
b b
b
KL
oroieotfon for B. eereus a a
c
a
c
c
Fig. 2. Factor-factor coli.
plot (KL plot) of three bacteria. a = 3. cereus, b = B. subtiiis and c = E.
12
60
I
Fig. 3. Factor
spectra
of the three bacteria.
4
59
I
j
B. cereus
73 100
IIIIII1
1,
IIIII
114 I I, ,#I, , ,, ; , ,b , , , ,
50
70
90
110
130
150
170
50
70
90
110
130
150
170
Fig. 4. Parent ion spectra
for daughter
ion m/r
58.
13
E. coli
70
90
110
130
150
170
210
190
Fig. 5. Parent ion spectra for daughter ion m/z 84. E. coii
127
144 120
140
156 II 160
16g I
186 I 180
200 III, 200
127
8. cereus
127
8. subtilis
220
240
150
Fig. 6. Parent ion spectra for daughter ion m/z
127.
I
14 TABLE 2 Diagnostic daughter peaks used for parent ion scans B. cereus
B. subtilis
E. coli
60 63 81 96 110 136
58 84 104 117 118 144 145
70 77 84 95 113 127 130
tion of each bacterium. Table 2 lists the prominent peaks observed in the factor spectra for each bacterium. Parent ion scans were performed using the peaks listed in Table 2. Figs. 4-6 show some of the parent ion spectra obtained. Not all of the peaks listed in Table 2 were diagnostic; however, the degree of complexity and selectivity of the data were dramatically improved by parent ion scanning when compared to the Py-CIMS data. The spectra shown in Figs. 4-6 were distinct enough that identification of the three bacteria can be easily made based on one or two peaks without the need of pattern recognition. In the case of the parent ions from the m/z 58 and 84 daughter ions, major changes in the spectra were observed (increase in intensity of m/z 104 parent ion for the 58 daughter ion and the m/z 144 parent ion for the 84 daughter ion). The changes of intensities in the parent scans for other ions were more subtle. For example, the parent scans for the m/z 127 daughter ion produced a small peak at m/z 142 for B. ccreus. This peak was absent in the other bacteria. We recognize that the degree of success of the parent ion scan mode in identifying individual bacteria is probably overemphasized because of the small data set. However, despite the limited amount of data, there are several points that can be generalized from this work. Daughter ions produced from the major peaks in the single stage Py-mass spectra in the mass range studied were not unique (Table 1). This means that parent ions producing these daughter ions were similar for all three bacteria and probably represent thermodynamically stable compounds. Larger data sets will only add complications to the daughter ion results. Improved means of identifying parent ions possessing unique structures must be employed if the daughter ion scans are to be useful. Identification of these parent ions could be achieved using the gas chromatographic techniques of Morgan [6] or perhaps by studying parent ions of higher mass (i.e. over 200 amu). High mass ions were not used in the present study because of the limited transfer capabilities for high mass compounds of our experimental configuration. For future studies involving high mass parent
15
ions, the pyrolysate must be introduced either directly into the ion source or through an improved transfer line and instrument configuration. Diverse high molecular weight compounds ( > 600 dalton) have been eluted from gas chromatographic columns [12]. The relative intensities for some of the daughter ion peaks were different between species, but the general sparseness of daughter ions severely limits application of pattern recognition techniques. Parent ion scans, whether or not they are totally unique, provided the elimination of redundancy necessary to apply Py-MS to large data sets. In summary, the results from this study clearly demonstrate the potential utility of combining Py-MS with the chemical noise reduction capabilities of tandem mass spectrometry. These results further suggest that parent ion scans produce useful data for classifying bacteria.
ACKNOWLEDGEMENT
The authors wish to thank CRDEC, Aberdeen Proving Grounds, Maryland, contract # DAAG29985-K-0199 and Brunswick Defense (formerly Honeywell CDC) for their support of this work.
REFERENCES 1 W.J. Irwin, Analytical Pyrolysis; A Comprehensive Guide, Marcel Dekker, New York, 1982. 2 H.L.C. Meuzelaar, J. Haverkamp and F.D. Hileman, Pyrolysis-Mass Spectrometry of Recent and Fossil Biomaterials, A Compendum and Atlas, Elsevier, Amsterdam, 1982. 3 K.J. Voorhees, S.L. Durfee and D.M. Updegraff, J. Microbial. Methods, in press. 4 E.R. Malinowsky and D.G. Howery, Factor Analysis in Chemistry, Wiley-Interscience, New York, 1980. 5 R.J. Rummel, Applied Factor Analysis, Northwestern University Press, Evansville, IN, 1970. 6 C.S. Smith, S.L. Morgan, CD. Parks, A. Fox and D.G. Pritchard, Anal. Chem., 59 (1987) 1410. 7 R.A. Yost and C.G. Enke, Anal. Chem., 51 (1979) 1251A. 8 J.W. de Leeuw, W.L. Maters, D.v.d. Meent and J.J. Boon, Anal. Chem., 49 (1977) 1181. 9 W. Windig and H.L.C. Meuzelaar, Anal. Chem., 56 (1984) 2297. 10 K.J. Voorhees and R. Tsao, Anal. Chem., 57 (1985) 1630. 11 R. Tsao and K.J. Voorhees, Anal. Chem., 56 (1984) 368. 12 H.L.C. Meuzelaar, W. McClennen and P. Synder, University of Utah, unpublished results.