Jackie Jackie1,2, Chun Kiang Chua2, Douglas Chiang Yon Chong1, Si Ying Lim1,3, Sam Fong Yau Li1,3. 1. Department of Chemistry, National University of Singapore, 3 Science Drive 3, Singapore 117543, Singapore. 2. Shimadzu (Asia Pacific) Pte Ltd, 79 Science Park Drive, #02-01/08 Cintech IV Science Park 1, Singapore 118264, Singapore. 3. NUS Environmental Research Institute, National University of Singapore, T-Lab Building, 5A Engineering Drive 1, Singapore 117411, Singapore.
Abstract
The capability of pyrolysis-gas chromatography-mass spectrometry (Py-GC-MS) for the direct analysis of endotoxins is demonstrated in this research article using the lipopolysaccharides of Pseudomonas aeruginosa 10. Analytical methods based on evolved gas analysis-MS, single-shot (SS) Py-GC-MS, and multishot heart cut Py-GC-MS were investigated. Among the various methods developed, the SS Py-GC-MS method shows superior potential for identifying bacterial endotoxins effectively through their biomarkers. The results obtained were validated with conventional mass spectral analysis after hydrolysis. The method was also evaluated for its robustness based on quality control criteria indicated by the U.S. EPA Method 8270D. When applied onto endotoxins of different Gram-negative bacteria, this method produced vastly distinct pyrograms. The results show that rapid and sensitive direct detection of endotoxins is possible with the Py-GC-MS method developed.
The capability of pyrolysis-gas chromatography-mass spectrometry (Py-GC-MS) for the direct analysis of endotoxins is demonstrated in this research article using the lipopolysaccharides of Pseudomonas aeruginosa 10. Analytical methods based on evolved gas analysis-MS, single-shot (SS) Py-GC-MS, and multishot heart cut Py-GC-MS were investigated. Among the various methods developed, the SS Py-GC-MS method shows superior potential for identifying bacterial endotoxins effectively through their biomarkers. The results obtained were validated with conventional mass spectral analysis after hydrolysis. The method was also evaluated for its robustness based on quality control criteria indicated by the U.S. EPA Method 8270D. When applied onto endotoxins of different Gram-negative bacteria, this method produced vastly distinct pyrograms. The results show that rapid and sensitive direct detection of endotoxins is possible with the Py-GC-MS method developed.
Endotoxins
are toxic substances released when Gram-negative bacteria
undergo cell death or cell division. This process happens regardless
of whether the bacterial membrane ruptures naturally or by human activities.[1] The endotoxin mostly comprises three molecular
components: O-antigenpolysaccharide, core polysaccharide, and lipid
A. The lipid A moiety, in particular, is associated with toxicity
for it interacts with tolllike receptors in the animal immune system,
which subsequently triggers inflammatory responses.[2] Endotoxins can be hazardous due to the ubiquity of bacteria.
People who routinely get exposed to endotoxins in occupational settings
are especially susceptible.[3]Due
to the major health threats of endotoxins, many techniques
have been devoted to the trace detection of these compounds. Among
all, biological detection of endotoxins is well established and widely
accepted, despite having some limitations.[4] Chemical analysis, however, offers the potential to study endotoxins
based on their molecular structures. Cross validation of biological
assays and chemical analysis can provide valuable insights into the
relationship between the lipopolysaccharide (LPS) structure and its
endotoxicity.[4]Among the many chemical
detection techniques, the pyrolysis–gas
chromatography–mass spectrometry (Py–GC–MS) combination
has been demonstrated to have the capability to discern between Gram-positive
and Gram-negative bacteria.[5] The biomarkers
of Gram-negative bacteria in Py–GC–MS analysis are generally
derived from the fatty acyl chains in the lipid A structure. These
include aldehydes and methylalkylketones (from the 3-OH fatty acids
bound to the glucosamine backbone) as well as hydrocarbons, fatty
acids, and nitriles (from secondary acyl chains). The Gram-positive
bacteria are marked by the presence of 2-picolinamide.[6] While there have been applications of Py–GC–MS
in differentiating bacteria types with cumbersome sample preparation
and chemical derivatization steps involved, the use of this technique
for direct endotoxin detection has not been explored.In this
study, the Py–GC–MS technique was explored
for the direct analysis of intact endotoxins. The results obtained
by these direct analyses were compared with the conventional derivatization
technique for method validation. The newly developed methods offer
huge potential and significant advantages, including simple sample
preparation and requiring only milligrams of raw LPS for direct MS
identification of specific biomarkers.
Results and Discussion
Study
Design of the Best Py–GC–MS Analysis Mode
Py–GC–MS
techniques were shown to be capable of the
direct analysis of intact endotoxins. Multiple components could be
observed from the direct pyrolysis of the Pseudomonas aeruginosa 10 (PA10) standard, with the single-shot (SS) pyrogram with the
temperature of the pyrolyzer set at 550 °C. The endotoxins are
assumed to have decomposed spontaneously upon entering the pyrolyzer,
as organic compounds tend to degrade completely beyond 500 °C.
The thermally decomposed products (aka pyrolysates)
then entered the GC and were separated through a capillary column.
As such, the peaks assume their observed retention times based on
the affinity toward the stationary phase. Many peaks could be observed,
and their identities could be indexed against commercial databases
developed for the gas chromatography–electron ionization–mass
spectrometry (GC–EI–MS) analysis.The pyrogram
reveals three major peaks (highlighted in blue, green, and yellow,
respectively): n-decanol (nC10–OH), n-dodecanol (nC12–OH), and n-hexadecanol (nC16–OH), all of
which could be associated with the structure of the fatty acyl chains
in the lipid A (form E) of P. aeruginosa (Figure ). Along the alcohol
peaks, some intact fatty acid chains were detected as well. These
peaks include the 3-hydroxydecanoic acid (labeled as intact 10:0(3-OH)),
a biomarker to the endotoxins,[8] as well
as dodecanoic acid (12:0), highlighted in orange and purple, respectively
(Figure ). From the
relative intensities, the three main peaks (nC10–OH, nC12–OH, and nC16–OH) can
be correlated to the first major hump (zone B) observed in the EGA
thermogram (Figure ).
Figure 1
Pyrogram for the SS analysis of P. aeruginosa PA10
in Py–GC–MS, with significant compounds, their abbreviated
names, and matching ratio against NIST 2017 Mass Spectral Library
listed in the embedded table. Similar to any typical GC–MS
chromatogram, peaks obtained can be searched and matched against GC–MS
database entries. The major peaks (highlighted in blue, green, and
yellow) are identified to be alcohols, which are derived from the
pyrolysis of the fatty acid chains of the lipid A structure. Some
intact fatty acid peaks were also identified (highlighted in orange
and purple).
Figure 2
Thermogram for the EGA of P. aeruginosa PA10 in
Py–GC–MS. Three humps depict the thermal decomposition
products of endotoxins under an inert atmosphere. The hump formation
starts around 200 °C (zone B), with the formation of a second
hump around 250 °C (zone C), and ends around 500 °C (zone
D). Zone A is absent of any significant compounds.
Pyrogram for the SS analysis of P. aeruginosaPA10
in Py–GC–MS, with significant compounds, their abbreviated
names, and matching ratio against NIST 2017 Mass Spectral Library
listed in the embedded table. Similar to any typical GC–MS
chromatogram, peaks obtained can be searched and matched against GC–MS
database entries. The major peaks (highlighted in blue, green, and
yellow) are identified to be alcohols, which are derived from the
pyrolysis of the fatty acid chains of the lipid A structure. Some
intact fatty acid peaks were also identified (highlighted in orange
and purple).Thermogram for the EGA of P. aeruginosaPA10 in
Py–GC–MS. Three humps depict the thermal decomposition
products of endotoxins under an inert atmosphere. The hump formation
starts around 200 °C (zone B), with the formation of a second
hump around 250 °C (zone C), and ends around 500 °C (zone
D). Zone A is absent of any significant compounds.The EGA thermogram of PA10 is seen to comprise three major
humps
(Figure ). As the
thermogram was obtained with a regular heating rate of 20 °C/min
and an initial temperature of 100 °C, it can be calculated that
the endotoxins start degrading around 200 °C (∼5 min)
to form the biggest hump (zone B). The endotoxins also stopped generating
breakdown compounds around 500 °C (∼20 min). This in turn
supports the use of 550 °C for SS analysis to spontaneously pyrolyze
the biomolecules.Because a deactivated metal capillary was
used in the EGA analysis,
the components were not chromatographically separated. As such, multishot
heart cut (HC) analyses were performed according to the zones depicted
in the EGA thermogram (zones A–D in Figure ). Each zone was subjected to pyrolysis,
and the components within each zone were individually separated in
the GC–MS using a capillary column. With the four zones in
the PA10 thermogram, four corresponding pyrograms were obtained (Figure ). All the main alcohol
peaks and intact fatty acids were found in the zone B pyrogram alone.
This indicates a correlation between the SS and EGA analyses, in which
the biggest EGA hump was associated with the breakdown of the most
exposed fatty acyl chains in the lipid A structure. However, the endotoxin
marker 3-hydroxydecanoic acid[8] found in
SS analysis was not observed here. This indicates that SS may be a
more suitable technique for direct endotoxin analysis as more information
on pyrolysates is retained.
Figure 3
Multishot HC analyses of P. aeruginosa PA10 in
Py–GC–MS, with significant compounds, their abbreviated
names, and matching ratio against NIST 2017 Mass Spectral Library
listed in the embedded table. The four pyrograms obtained (zones A–D)
corresponds to the four zones marked out in the EGA thermogram (Figure ). The results are
consistent with the SS analysis, in which the major components derived
from lipid A (highlighted in blue, green, and yellow): n-decanol (nC10–OH), n-dodecanol
(nC12–OH), and n-hexadecanol
(nC16–OH) are found in the major hump in zone
B. The intact 3-hydroxydecanoic acid found in SS analysis was not
observed here.
Multishot HC analyses of P. aeruginosaPA10 in
Py–GC–MS, with significant compounds, their abbreviated
names, and matching ratio against NIST 2017 Mass Spectral Library
listed in the embedded table. The four pyrograms obtained (zones A–D)
corresponds to the four zones marked out in the EGA thermogram (Figure ). The results are
consistent with the SS analysis, in which the major components derived
from lipid A (highlighted in blue, green, and yellow): n-decanol (nC10–OH), n-dodecanol
(nC12–OH), and n-hexadecanol
(nC16–OH) are found in the major hump in zone
B. The intact 3-hydroxydecanoic acid found in SS analysis was not
observed here.The pyrograms from zones C and
D contain many sugar pyrolysates
and remaining fatty acid pyrolysates, among other biomolecules. It
is thus deduced that as the temperature of the pyrolyzer increases,
the outermost lipid A moiety breaks down first (giving rise to the
big hump in zone B). Subsequently, the inner structures, such as the
inner core and the polysaccharide tail, degrade at a higher temperature.
Notably, within the zone C pyrogram, which contains many sugar pyrolyzates
from the polysaccharide skeleton, the well-known endotoxin biomarker
keto-deoxyoctulosonate (Kdo)[9] was not observed.
The high-temperature degradation may have resulted in the restructuring
of the Kdo, rendering it difficult for observation after pyrolysis.
Further investigation with other endotoxins will be required to evaluate
if Kdo is not observable by the Py–GC–MS method.The results obtained by the direct Py–GC–MS analyses
were validated with the conventional derivatization technique based
on mild acid hydrolysis.[7] The hydrolysis
severs the lipid A moiety from the polysaccharide components. The
lipid A portion was injected into GC–MS for analysis. The major
alcohol peaks and intact fatty acids were all identified to match
those of SS analysis (Figure ). Duplicates of each run had also produced consistent results.
It was confirmed that the lipid A components in bacterial LPS standards
could be observed directly in Py–GC–MS even when the
intact endotoxins were analyzed without any sample preparation, as
normally required in the conventional method based on mild acidic
hydrolysis.
Figure 4
Chromatogram of P. aeruginosa PA10 lipid A extracted
by mild acid hydrolysis in GC–MS, with significant compounds,
their abbreviated names, and matching ratio against NIST 2017 Mass
Spectral Library listed in the embedded table. This conventional method
verified the major components derived from PA10 lipid A in the Py–GC–MS
analysis (alcohols highlighted in blue, green, and yellow; intact
fatty acids highlighted in orange and purple). In other words, lipid
A components could be observed directly by Py–GC–MS
with minimal sample preparation on bacterial LPS standards.
Chromatogram of P. aeruginosaPA10 lipid A extracted
by mild acid hydrolysis in GC–MS, with significant compounds,
their abbreviated names, and matching ratio against NIST 2017 Mass
Spectral Library listed in the embedded table. This conventional method
verified the major components derived from PA10 lipid A in the Py–GC–MS
analysis (alcohols highlighted in blue, green, and yellow; intact
fatty acids highlighted in orange and purple). In other words, lipid
A components could be observed directly by Py–GC–MS
with minimal sample preparation on bacterial LPS standards.A summary of the advantages and disadvantages of
the methods developed
in this study, as compared to the conventional derivatization method
based on mild acid hydrolysis, can be found in Table . The Py–GC–MS methods developed
are highly effective because compounds from the chromatograms can
be easily identified by matching against commercial databases. With
multishot HC, biomarkers and other components from the lipid A moiety
can be identified, but sugar components can be optionally omitted.
This allows the possibility of endotoxin screening through specific
compounds and bacteria profiling through the lipid A chromatogram
within a single analysis. However, HC is time consuming as multiple
runs have to be performed. SS is superior in terms of time efficiency
while still providing sufficient information for identifying the endotoxins
through their major components and biomarkers.
Table 1
Sample Requirement, Advantages, and
Disadvantages of GC–MS Methods Developed in This Work for the
Direct Detection of Endotoxins, with Reference to the Conventional
Derivatization Technique
methods
minimal sample
amount
state of sample
advantage
disadvantage
Py–GC–MS (SS)
0.1 mg
intact endotoxins (solid)
indexing against the commercial database for peak identification
large amount of information (all components from lipid A and
saccharides elute in a single chromatogram)
Py–GC–MS (EGA)
0.1 mg
intact endotoxins (solid)
categorization of how endotoxins react to heat
no separation
of components, making it difficult for elucidation
Py–GC–MS (HC)
0.1 mg
intact endotoxins (solid)
combined advantages from EGA and SS
time-consuming
to segregate lipid A from saccharides information
in multiple runs
mild
acid hydrolysis[7]
10 mg
lipid A components (hydrolyzed)
rapid and efficient relative to other extraction
techniques
reaction takes a long time and chemical reagents
requires a separate detection method
Application on the Spiked
Water Sample
The Py–GC–MS
method was validated with reference to the US EPA method 8270D[10] in view of its future applicability for analyzing
environmental samples. The test includes robustness, linearity, intra-,
and interday repeatability. The superior SS method was selected for
complete validation because it is a straightforward method that consumes
less time. The five main peaks associated with the structure of the
fatty acyl chains in the lipid A (form E) of P. aeruginosa were chosen for evaluation.A summary of the validation results
can be found in Table . For the linearity test, it was found that sample amounts less than
0.1 mg did not give repeatable results. A five-point calibration of
the PA10 standard was performed at 0.1, 0.2, 0.5, 1, and 2 mg. All
five compounds gave an R2 of more than
0.99, indicating good linearity. The response factor, which indicates
deviations from the calibration line, was all within 30%, except for
the intact 10:0(3-OH). Repeatability tests were performed at the lower
limit of quantitation of 0.1 mg, calibration midpoint of 0.5 mg, and
upper limit of quantitation (ULOQ) of 2 mg of which, the repeatability
for retention time was all within 0.05% and that for peak area within
25%. Notably, the ULOQ repeatability data were missing 10:0(3-OH)
and 12:0, likely due to incomplete pyrolysis when the sample amount
was very high.
Table 2
Validation Results of the Py–GC–MS
(SS) Method Developed in This Work for the Direct Detection of Endotoxins
compound
calibration range (mg)
linearity, R2
response factor, RF (%)
area
repeatability, RSD (n = 3) (%)
interday area repeatability, RSD
(n = 3) (%)
0.1 mg
0.5 mg
2 mg
nC10–OH
0.1–2
0.9946
23
25
4
2
4
nC12–OH
0.1–2
0.9931
21
25
4
6
4
nC16–OH
0.1–2
0.9938
16
10
4
7
6
10:0(3-OH)
0.1–2
0.9956
52
1
6
8
12:0
0.1–2
0.9915
9
6
6
10
The linearity and calibration midpoint repeatability
tests were
repeated a week after the first results were obtained. The interday
results were reproducible, with linearity R2 more than 0.99% and peak area RSD within 10%. Real sample run results
showed that the developed method was applicable to water samples spiked
with PA10 endotoxins. As observed in Figure , the chromatographic profile of the sample
matches that of the P. aeruginosa standard. By applying
the calibration curve, the amount of endotoxins was found to be 0.058
mg based on the average of the five main compounds. This value is
significantly different from the 0.45 mg spiked and could be attributed
to the loss during drying. Further investigations will have to be
performed to improve the extraction and recovery of real sample runs.
Figure 5
Water
sample spiked with P. aeruginosa PA10 lipid
and analyzed in the Py–GC–MS, producing the black chromatogram.
Significant compounds, their abbreviated names, and matching ratio
against NIST 2017 Mass Spectral Library are listed in the embedded
table. The lipid A components (alcohols highlighted in blue, green,
and yellow; intact fatty acids highlighted in orange and purple) are
directly comparable to those obtained with pure bacterial LPS standards
(0.09 mg) by SS mode, represented by the pink chromatogram.
Water
sample spiked with P. aeruginosaPA10lipid
and analyzed in the Py–GC–MS, producing the black chromatogram.
Significant compounds, their abbreviated names, and matching ratio
against NIST 2017 Mass Spectral Library are listed in the embedded
table. The lipid A components (alcohols highlighted in blue, green,
and yellow; intact fatty acids highlighted in orange and purple) are
directly comparable to those obtained with pure bacterial LPS standards
(0.09 mg) by SS mode, represented by the pink chromatogram.
Application on Other Endotoxin Standards
The SS mode
of the Py–GC–MS method can also be used to analyze other
bacterial endotoxins directly. As seen in Figure A,B, respectively, Salmonellaenterica serovar Typhimurium (S. Typhimurium) and Escherichia coli J5 generated
vastly different pyrograms.
Figure 6
Pyrogram for SS analysis of (A)S. Typhimurium and (B)E. coli J5 in
Py–GC–MS. Similar to that of PA10, the major peaks are
likely derived from the pyrolysis of the fatty acid chains of the
lipid A structure. Common to both S. Typhimurium and E. coli J5 are tridecene, dodecanal, and tetradecenamide
(highlighted in purple, orange, and yellow, respectively). Common
to PA10 (see Figure ) and S. Typhimurium are the alcohols (highlighted
in blue and green). Some intact fatty acid peaks were identified in E. coli J5, associating directly to the fatty acyl
chains (highlighted in various gray shades). Significant compounds,
their abbreviated names, and matching ratio against NIST 2017 Mass
Spectral Library are listed in the correspondingly embedded tables.
*Tetradecenamide and **2-tetradecenoic acid were not matched directly
with the library but deduced through the retention time and a relatively
high similarity index of >80% with 13-docosenamide and 2-dodecenoic
acid, respectively. These deduced compounds are not registered in
the commercial GC–MS library.
Pyrogram for SS analysis of (A)S. Typhimurium and (B)E. coli J5 in
Py–GC–MS. Similar to that of PA10, the major peaks are
likely derived from the pyrolysis of the fatty acid chains of the
lipid A structure. Common to both S. Typhimurium and E. coli J5 are tridecene, dodecanal, and tetradecenamide
(highlighted in purple, orange, and yellow, respectively). Common
to PA10 (see Figure ) and S. Typhimurium are the alcohols (highlighted
in blue and green). Some intact fatty acid peaks were identified in E. coli J5, associating directly to the fatty acyl
chains (highlighted in various gray shades). Significant compounds,
their abbreviated names, and matching ratio against NIST 2017 Mass
Spectral Library are listed in the correspondingly embedded tables.
*Tetradecenamide and **2-tetradecenoic acid were not matched directly
with the library but deduced through the retention time and a relatively
high similarity index of >80% with 13-docosenamide and 2-dodecenoic
acid, respectively. These deduced compounds are not registered in
the commercial GC–MS library.The pyrolysis of S. Typhimurium produces alcohols
in a similar fashion to that of PA10 (highlighted in green and blue,
respectively): n-dodecanol (nC12–OH)
and n-tetradecanol (nC14–OH),
matching with the lengths of the fatty acyl chains in its lipid A
structure (Figure A). Along the alcohol peaks, some new major compounds are observed,
which are tridecene (C12=CH2), dodecanal (C11–CHO), and tetradecenamide
(14:1am), highlighted in purple, orange, and yellow, respectively
(Figure A). These
three new compounds are coincidentally observed in the pyrogram of E. coli J5 (Figure B) and can be associated with the respective structures
of the lipid A moiety.The identity of tetradecenamide (14:1am)
was partially deduced
through similarity search to another homologous compound, 13-docosenamide
(22:1am), which could not have eluted this early in the chromatogram.
This can be deduced by its close retention time to nC14–OH. The increased polarity due to the amide functional
group interacts more with the capillary column, resulting in the higher
retention time. The pyrolysate 2-tetradecenoic acid (14:1) from E. coli J5 was deduced similarly. The C=C double
bond only shifts its retention time to slightly later than that of
14:0. Both compounds were not registered in the commercial libraries.In addition, it is interesting to observe that for the pyrolysis
of the E. coli J5 Rc mutant, which
is a rough-type variant of the endotoxin with a shorter saccharide
chain,[11] a much higher amounts of intact
fatty acid chains are formed instead of the alcohols. This suggests
that the size of the polysaccharide moiety might influence the formation
of the pyrolysates.
Conclusions
The rapid detection
capability of Py–GC–MS for lipid
A analysis had been illustrated with the P. aeruginosa 10 LPS standard in this research article. The sample preparation
of endotoxins for MS analysis was significantly simplified, without
the need for any derivatization. Micrograms of endotoxins were sufficient
for fast identification via specific biomarkers originating from the
lipid A portion. Among the multiple Py–GC–MS methods
developed, the SS Py–GC–MS method has the highest potential
in identifying the biomarkers of Gram-negative bacteria effectively.Multiple endotoxin standards were tested with the SS method and
produced vastly different pyrograms. It was clear that endotoxins
of different bacteria species could be discerned, but the applicability
for more bacteria types and their subspecies should be examined. Major
components that can be associated with the lipid A moiety are largely
similar, such as alcohols and intact fatty acids, whereas the combination
of various peaks in the SS pyrogram could create distinct fingerprint
patterns. Chemometric tools can be applied in subsequent studies to
evaluate their suitability as discrimination and identification tools
for the characterization of the mixtures of endotoxins.While
the Py–GC–MS method was shown to work on water
samples spiked with the endotoxins, they should also be applied to
other types of samples. Extension of the method to other endotoxins
standards will also help to evaluate its validity. With a wider variety
of LPS standards, a database of endotoxin biomarkers can be compiled
for bacteria profiling. By combining both the simplified extraction
approach and the lipid A profiling database, the application field
will extend toward the environmental, food, and air samples—fields
that are not as well regulated as the pharmaceuticals but equally
of concern to human health.
Materials and Methods
Py–GC–MS
Analysis
LPS standards of P. aeruginosa 10
(PA10, product code L9143), S.
Typhimurium (product code L6511), and the E. coli J5 Rc mutant (E. coli J5, product code L5014) were purchased from Sigma-Aldrich (St. Louis,
MO, USA). All standards were obtained in the form of a white freeze-dried
powder, kept in amber glass bottles.Around 0.1 mg of the PA10, S. Typhimurium, or E. coli J5 was measured and inserted into a metallic pyrolysis cup (Eco-Cup
LF, Frontier Lab). These stainless steel cups were deactivated to
ensure no catalytic effects during the pyrolysis or absorption of
the target compounds. The weighed standard was then covered in glass
wool, before being placed on the autosampler of the Pyrolyzer (EGA/Py-3030D,
Frontier Lab) coupled with the GC–MS (GCMS-QP2020, Shimadzu
Corp.). The endotoxin standards were analyzed using optimized parameters
in SS, multishot HC, and evolved gas analyses (EGA).In all
these methods, MS parameters were set to the EI mode. General
EI settings included an ion source temperature of 200 °C, interface
temperature of 300 °C, and a scanning speed of 2500 u/s for m/z 35–700. Mass spectral results were indexed against
commercial databases (NIST 2017 Mass Spectral Library) for identification.
Runs are all duplicated to ensure repeatability.
SS Analysis
Mode
The pyrolyzer was set to a set temperature
while the GC–MS heating rate was programmed to be steadily
increasing. A separating column is installed in the GC oven to separate
the compounds based on their affinity to the stationary phase and
thus their retention in the column. The pyrolyzer furnace was kept
isothermal at 550 °C, while the interface remained in an auto
mode at 300 °C. The GC column used was an Ultra Alloy metal capillary
with 30 m length, 0.25 mm inner diameter, and 0.25 μm film thickness
(UA-5 MS, Frontier Lab). The GC oven was heated from 40 °C (hold
for 2 min) to 320 °C (hold for 4 min) with a ramping rate of
20 °C/min.
EGA Mode
The pyrolyzer heating rate
was programmed
to be steadily increasing, while the GC–MS was set to be isothermal
with no separating column. The setting in the EGA mode is opposite
of that in SS analysis. Because no separating column was used, the
resultant data is a thermogram instead of a chromatogram, and the
peaks/humps represent the retention of compounds as a function of
temperature. The pyrolyzer furnace was programmed from 100 to 550
°C at a ramping rate of 20 °C/min, while the interface was
kept in an auto mode at 300 °C. The GC column used was a deactivated
metal capillary with 2.5 m length and 0.15 mm inner diameter containing
no stationary phase (EGA Capillary Tube UADTM-2.5N, Frontier Lab),
heated isothermally at 300 °C.
Multishot HC Analysis Mode
A multishot analysis combines
both the EGA and SS modes (aka Heart Cut, HC). The
pyrolyzer furnace was programmed from 100 to 550 °C at a ramping
rate of 20 °C/min, while the interface was kept in an auto mode
at 300 °C. At each specific time window (zone), the furnace temperature
was held at the upper temperature range of that window to allow compounds
which had turned volatile by this temperature to enter the GC for
separation. For example, zone A in Figure runs from 100 to 200 °C, and the furnace
temperature was held at 200 °C until the GC run completes. The
GC column used was an Ultra Alloy metal capillary with 30 m length,
0.25 mm inner diameter, and 0.25 μm film thickness (UA-5 MS,
Frontier Lab). The GC oven was heated from 40 °C (hold for 2
min) to 320 °C (hold for 4 min) with a ramping rate of 20 °C/min.
Once the GC run had completed, the furnace temperature was allowed
to increase till the next zone for another round of GC separation.
This process was repeated until the last zone was completed. Multiple
chromatograms were obtained for each zone based on the humps observed
in the EGA analysis.
Method Validation with the Conventional Derivatization
Technique
Mild acidic hydrolysis using the hot ammonium–isobutyrate
solvent was performed to separate the lipid A portion from the endotoxin
structure. The extraction was modified from the hydrolysis procedure
described elsewhere.[7]Isobutyric
acid (250 μL) (Sigma-Aldrich) and ammonium hydroxide (150 μL)
(Sigma-Aldrich) were added to 1 mg PA10 standard in a 1.5 mL Eppendorf
tube, before being placed in a water bath (80 °C) for 2 h. After
hydrolysis, the tubes were immediately placed into an ice bath for
10 min. The extracted lipid A emerged as gelatine-like structures
after the liquid was blown dry using a constant stream of nitrogen
gas at 30 °C (TurboVap II, Biotage). Finally, it was dissolved
in 100 μL of a 95:5 (v/v) mixture of methanol (Kanto Chemicals)
and dichloromethane (Sigma-Aldrich) for subsequent MS analysis. Analysis
of GC–MS follows the exact same parameters described in the
Py–GC–MS analysis section, with a solvent cut time of
5 min added. Runs were all duplicated to ensure repeatability.
Spiked
Water Sample Analysis
To 45 μL of ultrapure
water (Milli-Q), 0.45 mg of the PA10 standard was added and dissolved
in a metallic pyrolysis cup. The sample was then left to stand till
dryness, before being subjected to the SS analysis with the Py–GC–MS
parameters described in the corresponding section.
Authors: Keat G Ong; Joshua M Leland; Kefeng Zeng; Gary Barrett; Mohammed Zourob; Craig A Grimes Journal: Biosens Bioelectron Date: 2005-12-13 Impact factor: 10.618
Authors: Ying S Ting; Scott A Shaffer; Jace W Jones; Wailap V Ng; Robert K Ernst; David R Goodlett Journal: J Am Soc Mass Spectrom Date: 2011-03-05 Impact factor: 3.109
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