Identification of five gelatins by ultra performance liquid chromatography/time-of-flight mass spectrometry (UPLC/Q-TOF-MS) using principal component analysis.

Abstract

An ultra-performance liquid chromatography-quadrupole-time of flight mass spectrometry (UPLC/Q-TOF-MS) method coupled with a principal component analysis (PCA) was developed and applied toward identifying donkey-hide gelatin, bovine-hide gelatin, pig-hide gelatin, tortoise shell glue, and deerhorn glue. The UPLC-MS data of the trypsin digested samples were subjected to principal component analysis (PCA) in order to classify these five gelatins. Additionally, marker peptides given by the loadings plot of PCA were identified based on a comparison of recorded LC-MS data with a previously reported database of the corresponding gelatin variants. The results from this study indicate that the proposed method is reliable, and it has been successfully applied to the identification of variants of gelatins commonly used in Traditional Chinese Medicine (TCM).

Full text

Page 1

Journal
of
Pharmaceutical
and
Biomedical
Analysis
62 (2012) 191–
195
Contents
lists
available
at
SciVerse
ScienceDirect
Journal
of
Pharmaceutical
and
Biomedical
Analysis
jou
rn al
h om
epage:
www.elsevier.com/locate/jpba
Short
Identification
chromatography/time-of-flight
principal
communication
of
five
gelatins
by
ultra
performance
liquid
mass
spectrometry
(UPLC/Q-TOF-MS)
using
component
analysis
Xian-Long
Ping
Chenga,b,
Feng
Weia,
Xin-Yue
Xiaoa,∗,
Ying-Yong
Zhaoc,
Yan
Shia,
Wei
Liua,
Zhanga,
Shuang-Cheng
Maa,
Shou-Sheng
Tiand,
Rui-Chao
Lina,b,∗∗
aResearch
State
bSchool
cBiomedicine
dShandong
and
Inspection
Center
of
Traditional
Chinese
Medicine
and
Ethnomedicine,
National
Institutes
for
Food
and
Drug
Control,
Food
and
Drug
Administration,
2 Tiantan
Xili,
Beijing
100050,
China
of Chinese
Pharmacy,
Beijing
University
of
Chinese
Medicine,
No.
6 Wangjing
Zhong
Huan
Nan
Lu,
Chaoyang
District,
Beijing
100102,
China
Key
Laboratory
of
Shaanxi
Province,
Northwest
University,
No.
229
Taibai
North
Road,
Xi’an,
Shaanxi
710069,
China
Dong
E E Jiao
Co.,
Ltd.,
Liaocheng
252201,
China
a
r
t
i
c
l
e

i
n
f
o
Article
Received
Received
19
Accepted
Available online 29 December 2011
history:
26 September
2011
in revised
form
December
2011
19 December
2011
Keywords:
UPLC/Q-TOF-MS
Gelatin
Polypeptides
PCA
Identification
a
b
s
t
r
a
c
t
An
TOF-MS)
identifying
glue.
(PCA)
PCA
of
reliable,
in
ultra-performance
liquid
chromatography-quadrupole-time
of
flight
mass
spectrometry
(UPLC/Q-
method
coupled
with
a
principal
component
analysis
(PCA)
was
developed
and
applied
toward
donkey-hide
gelatin,
bovine-hide
gelatin,
pig-hide
gelatin,
tortoise
shell
glue, and
deerhorn
The
UPLC-MS
data
of the
trypsin
digested
samples
were
subjected
to
principal
component
analysis
in
order
to
classify
these
five
gelatins.
Additionally,
marker
peptides
given
by
the
loadings
plot
of
were
identified
based
on
a
comparison
of
recorded
LC–MS
data
with
a
previously
reported
database
the
corresponding
gelatin
variants.
The
results
from
this
study
indicate
that
the
proposed
method
is
and
it
has
been
successfully
applied
to
the
identification
of
variants
of
gelatins
commonly
used
Traditional
Chinese
Medicine
(TCM).
© 2011 Elsevier B.V. All rights reserved.
1.
Introduction
Gelatin
the
and
lagen
China,
glue
tional
In
cases,
spongiform
response
incorrectly
is a mixture
of
high
molecular
weight
polypeptides
from
hydrolysis
of
collagen,
and
it is
widely
used
in food,
cosmetic,
pharmaceutical
industries
[1–3]. There
are
many
sources
of
col-
for
gelatin
production,
i.e.,
bovine,
porcine,
and
fish
skin.
In
donkey-hide
gelatin,
bovine-hide
gelatin,
pig-hide
gelatin,
of
tortoise
shell,
and
deerhorn
glue
are
widely
used
as
Tradi-
Chinese
Medicines
(TCM)
[4–6].
Islamic
countries,
porcine
gelatin
is forbidden,
and
in some
bovine
gelatin
carrying
prion
proteins
associated
with
bovine
encephalopathy
should
be
identified.
An
immune
will
occur
when
gelatins
from
certain
sources
are
used
[7]. These
gelatins
are
believed
to produce
different
∗Corresponding
∗∗Corresponding
Medicine
Food
Tel.:
E-mail
author.
Tel.:
+86
10
67095432;
fax:
+86
10
67023650.
author
at: Research
and
Inspection
Center
of
Traditional
Chinese
and
Ethnomedicine,
National
Institutes
for
Food
and
Drug
Control,
State
and
Drug
Administration,
2 Tiantan
Xili,
Beijing
100050,
China.
+86
10
67095432;
fax:
+86
10 67023650.
addresses:
xiaoxxy@sina.com
(X.-Y.
Xiao),
linrch307@sina.com
(R.-C.
Lin).
clinical
market
sive
These
they
using
cal
may
plays
gen
in gelatin
gelatin
in
amino
HPLC
amino
lagen
differentiation
Time
an
knowledge,
analysis
effects,
and
they
command
different
prices
on the
open
in China.
Therefore,
it is important
to complete
comprehen-
studies
on
identifying
and
distinguishing
these
five
gelatins.
five
gelatins
have
similar
chemical
properties
because
are
homologous
[8],
and
it is difficult
to distinguish
them
conventional
spectroscopic
methods
[9]. The
immunochemi-
method
has
been
used
to identify
collagen
[10], but
this
method
be
influenced
by
the
extent
of
proline
hydroxylation,
which
an
important
role
in determining
the
antigenicity
of
colla-
[11]. The
polymerase
chain
reaction
(PCR)
method
is
not
used
identification
because
DNA
integrity
is destroyed
during
processing,
although
this
method
has
been
widely
applied
collagen
identification
[12,13]. To the
best
of
our
knowledge,
acids
from
the
hydrolysis
of
collagen
were
analyzed
using
coupled
with
PCA
to classify
bovine
and
porcine
gelatin,
but
acids
do not
reveal
the
properties
of
primary
gelatins”.
Col-
marker
peptides,
combined
with
sequence
searching,
allow
of
bovine
and
porcine
gelatin
[8,14,15].
of
flight
mass
spectrometry
(TOF)
has
been
developed
as
efficient
method
for
protein
analysis
[16–19]. To
the
best
of our
there
has
been
little
use
of
UPLC
QTOF
MS
and
PCA
for
the
identification
of
these
five
gelatins.
In this
work,
0731-7085/$
doi:10.1016/j.jpba.2011.12.024
– see
front
matter ©

2011 Elsevier B.V. All rights reserved.

Page 2

192
X.-L.
Cheng
et al.
/ Journal
of
Pharmaceutical
and
Biomedical
Analysis
62 (2012) 191–
195
we
used
gelatin,
and
analyzed
tryptic
peptides
of
gelatins
using
UPLC/Q-TOF-MS
and
principal
component
analysis
(PCA)
to classify
donkey-hide
bovine-hide
gelatin,
pig-hide
gelatin,
tortoise
shell
glue,
deer-horn
glue.
2.
Experimental
2.1.
Materials
and
reagents
Leucine
Sigma–Aldrich
purchased
USA).
(Pittsburgh,
a
ford,
(Madison,
Millipore
lytical
National
pared
concentration
provided
conditions
of
enkephalin
and
formic
acid
were
purchased
from
(St.
Louis,
MO,
USA).
Acetonitrile
(HPLC
grade)
was
from
J.T.
Baker
(Baker
Mallinckrodt,
Phillipsburg,
NJ,
Methanol
(HPLC
grade)
was
purchased
from
Fisher
Scientific
PA,
USA).
Ultra
high
purity
water
was
prepared
using
Milli-Q
water
purification
system
(Millipore
Corporation,
Bed-
MA).
Trypsin
(sequencing
grade)
was
obtained
from
Promega
WI,
USA).
Syringe
filters
(0.22
?m)
were
purchased
from
(Billerica,
MA,
USA).
All
other
chemicals
used
were
of
ana-
grade.
A total
of
25
gelatin
samples
were
collected
by
the
Institute
for
Food
and
Drug
Control.
All
samples
were
pre-
in the
laboratory
by
decoction
at 110◦C for
2 h in water
and
to a solid
at 100◦C.
The
three
unknown
samples
were
by the
manufacturer
and
were
prepared
under
severe
by
decoction
at 120◦C for
4 h in an
aqueous
solution
0.6%
NaCO3and
concentration
to a solid
at 100◦C.
2.2.
Sample
preparation
First,
100
mg
of
the
gelatin
standard
was
dissolved
in 50
mL
of
a
a 0.22
drawn,
8.0)
1%
NH4HCO3solution
(pH
8.0).
The
solution
was
filtered
through
?m syringe
filter.
Then,
100
?L of
the
gelatin
solution
was
and
10
?L of
trypsin
solution
(1 mg/ml
in 1% NH4HCO3, pH
was
added.
The
mixture
was
incubated
at
37◦C for
12
h.
2.3.
Chromatographic
separation
The
UPLC
analysis
was
performed
using
a Waters
AcquityTM
Ultra
ester,
ACQUITY
column
A (0.1%
optimized
5%–20%
40.0–45.0
5.0%.
pler
volume
Performance
LC system
(Waters
MS
Technologies,
Manch-
UK).
Chromatographic
separation
was
carried
out
on
an
UPLC
BEH
C18column
(100
mm
× 2.1
mm,
1.7
?m)
at
a
temperature
of
45◦C.
The
mobile
phase
consisted
of
solvent
formic
acid
in water,
v/v)
and
solvent
B (acetonitrile).
The
UPLC
elution
conditions
were
as
follows:
0.0–25.0
min,
B;
25.0–40.0
min,
20–50%
B; 40.0–41.0
min,
50–99%
B;
min,
99%
B; 45.0–45.1
min,
99.0–5.0%
B;
45.1–55.0
min,
The
flow
rate
was
set
at 300
?L/min.
The
column
and
autosam-
were
maintained
at
40◦C and
10◦C,
respectively.
The
injection
was
5 ?L.
2.4.
Mass
spectrometry
Mass
spectrometry
was
performed
on
a XevoTMQTof
(Waters
MS
2000
voltage
gas
was
The
in
to
using
ity.
rate
quency
An
energy
Technologies,
Manchester,
UK).
The
scan
range
was
from
50
to
m/z. For
positive
electrospray
modes,
the
capillary
and
cone
were
set
at
3.0
kV and
30
V,
respectively.
The
desolvation
was
set
to 600
L/h
at
a temperature
of
450◦C,
and
the
cone
gas
set
to 50 L/h,
and
the
source
temperature
was
set
to 150◦C.
MCP
detector
voltage
was
set
at
2200
V.
Data
were
collected
continuum
mode,
in which
the
data
acquisition
rate
was
set
0.1
s,
with
a 0.1
s interscan
delay.
All
analyses
were
acquired
the
lock
spray
feature
to ensure
accuracy
and
reproducibil-
Leucine–enkephalin
at a concentration
of
2 ?g/mL
and
a
flow
of
3 ?L/min
was
used
for
the
lock
mass.
The
lock
spray
fre-
was
set
at 10
s,
and
the
data
were
averaged
over
10
scans.
alternation
low-energy
(collision
cell
energy
of
4 V)
and
elevated
(collision
cell
energy
ramped
from
20
to 30
V)
acquisition
was
data
using
used
to obtain
the
precursor
ion
(MS)
and
their
fragmentation
(MSE).
All
the
acquisition
and
analysis
of
data
were
controlled
Waters
MassLynx
v 4.1
software.
2.5.
Multivariate
data
analyses
The
raw
data
were
analyzed
by the
MarkerLynx
applications
manager
tion
50–2000
set
and
was
generated
were
same
The
the
ynx.
(RT
analyzed
variables
version
4.1
(Waters,
UK).
The
parameters
used
were
reten-
time
(RT)
in the
range
of
1–40
min,
mass
in the
range
of
Da,
mass
tolerance
0.05
Da,
noise
elimination
level
was
at
6.00,
intensity
threshold
100
counts,
mass
window
0.05
amu,
retention
time
window
of
0.2
min.
No specific
mass
or
adduct
excluded.
A list
of
the
intensities
of
the
peaks
detected
was
using
RT
and
m/z
data
pairs.
Ions
in different
samples
considered
to be
the
same
ion
when
they
demonstrated
the
RT (tolerance
of
0.2
min)
and
m/z
value
(tolerance
of
0.05
Da).
ion
intensities
for
each
detected
peak
were
normalized
against
sum
of
the
peak
intensities
within
that
sample
using
MarkerL-
The
resulting
three-dimensional
data
comprising
peak
number
m/z
pair),
sample
name
(observations),
and
ion
intensity
were
by
unsupervised
principal
component
analysis
(PCA).
All
were
pareto-scaled
prior
to analysis.
3.
Results
and
discussion
3.1.
spectrometry
Optimization
of
chromatographic
separation
and
mass
An
earlier
study
reported
profiling
of
tryptic
peptides
in bovine
and
study,
reported
significantly
mising
in
selectivity
resolution
method
plexity
The
and
voltage
tion
was
remove
of
for
to obtain
was
no
peak
ples
robust
the
469.2430,
737.9980)
porcine
gelatin
with
a 120
min
analysis
method
[14]. In our
a
55
min
UPLC
QTOF
MS
tryptic
peptides
profiling
assay
was
for
the
profiling
of
gelatins
using
step-gradients,
which
shortens
the
time
of
sample
analysis
without
compro-
chromatographic
peak
resolution.
The
significant
reduction
analysis
time
was
a result
of
a combination
of
the
enhanced
of
TOF/MS
detection
and
the
enhanced
chromatographic
due
to the
use
of
a
sub-2
?m particle
column.
This
could
reduce
the
severe
ion
suppression,
although
the
com-
of
the
tryptic
gelatin
peptides
makes
separation
difficult.
peptides
are
amphiprotic
substances
and
can
be
ionized
in ESI+
ESI−mode,
but
sparkover
will
often
occur
at a high
capillary
in the
ESI−mode.
Therefore,
ESI+was
selected
as
the
ioniza-
mode
for
the
TOF-MS
experiments.
The
desolvation
gas
flow
set
at
600
L/h,
and
desolvation
temperature
was
set
at 450◦C to
the
abundant
solvent
that
results
from
a higher
proportion
water
in the
mobile
phase.
A cone
voltage
of 30
V was
selected
use
after
optimizing
the
cone
voltage
in the
range
of
15–45
V
a higher
sensitivity.
The
data
acquisition
rate
of
200
ms
used
to ensure
that
the
chromatographic
peaks
are
defined
by
less
than
10
data
points
[20]. The
comparison
of
the
five
base
ion
(BPI)
chromatograms
obtained
from
the
five
tryptic
sam-
is shown
in Fig.
1.
The
UPLC-QTOF-MS
system
proved
to be
for
the
retention
time
shift
and
the
mass
accuracy
based
on
extracted
ion
chromatographic
peaks
of
eight
ions
(402.2120,
473.2303,
802.4034,
672.3723,
765.8712,
714.3438,
and
were
<0.02
min
and
10
ppm,
respectively.
3.2.
Multivariate
data
analyses
It appears
cealed
indistinguishable
ogy
each
fore,
multivariate
that
the
marker
peptides
of
each
gelatin
were
con-
within
a larger
number
of
tryptic
peptides
that
were
at
higher
concentrations
because
of
the
homol-
of
collagen
in TIC
chromatography.
It is
difficult
to distinguish
gelatin
by
visual
observation
of
their
chromatograms;
there-
further
sample
profiling
of
the
gelatins
requires
the
use
of
statistical
tools.
In our
study,
the
first
step
of
the

Page 3

X.-L.
Cheng
et
al.
/ Journal
of
Pharmaceutical
and
Biomedical
Analysis
62 (2012) 191–
195
193
Time
5.00
10. 00
15.00
20.00
25.00
30.00
35.00
40.00
%
-5
95
5.00
10. 00
15.00
20.00
25.00
30.00
35.00
40.00
%
-5
95
5.00
10. 00
15.00
20.00
25.00
30.00
35.00
40.00
%
-5
95
5.00
10. 00
15.00
20.00
25.00
30.00
35.00
40.00
%
-5
95
5.00
10. 00
15.00
20.00
25.00
30.00
35.00
40.00
%
-5
95
(A)
(B)
(C)
(D)
(E)
Fig.
(D)
1.
Positive
ion
base
peak
intensity
chromatograms
obtained
from
the
analysis
of
tryptic
digest
of
(A)
donkey-hide
gelatin,
(B)
bovine-hide
gelatin,
(C)
pig-hide
gelatin,
glue
of
tortoise
shell
and
(E)
deerhorn
glue.
multivariate
vert
Mass
Application
was
classification
statistical
analysis
of
the
UPLC/MS
dataset
was
to con-
the
3D LC/MS
data
into
a 2D matrix
expressed
as
an
Exact
Retention
Time
(EMRT)
pair
using
Markerlynx,
which
is an
Manager
for
the
MassLynxTMSoftware.
The
data
set
visualized
using
unsupervised
PCA
to check
for
outliers
and
trends
among
the
gelatins.
Preliminary
PCA
was
performed
The
of
Hotelling
obtained
gelatin,
on
all
observations
using
8556
pareto-scaled
variables.
final
PCA
score
plot
demonstrated
that
the
five
different
types
gelatins
cluster
together,
and
all
were
found
to lie
inside
the
T2 (0.95)
ellipse,
as
is shown
in Fig.
2A.
In the
scores
plot
by PCA,
donkey-hide
gelatin,
bovine-hide
gelatin,
pig-hide
deer-horn
glue
are
close
to each
other,
and
the
tortoise
shell
-100
-50
0
50
100
-100
-50
050

100
t[2]
t[1]
Scores Comp[1] vs. Comp[2] colored by Sample Group
(A)
unknow

n
unknow

n
-0.08
-0.04
0.00
0.04
0.08
-0.04
0.00
p[1]
0.04
p[2]
Loadings Comp[1] vs. Comp[2]
(B)
Fig.
2. PCA
score
plot
(A)
and
loading
plot
(B)
of
(
) donkey-hide
gelatin,
(?) bovine-hide
gelatin,
( ) pig-hide
gelatin,
(
) deerhorn
glue
and
(
) glue
of tortoise
shell.

Page 4

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et al.
/ Journal
of
Pharmaceutical
and
Biomedical
Analysis
62 (2012) 191–
195
Fig.
bovine-hide
PAGEEGK.
3.
Selected
ion
monitoring
chromatograms
of
marker
peptides
in (A)
donkey-hide
gelatin,
m/z
765.8556,
doubly-charged
ion
of
fragment
GEAGPAGPAGPIGPVGAR.
(B)
gelatin,
m/z
641.3065,
doubly-charged
ion
of
fragment
GEAGPSGPGPTGAR.
(C)
pig-hide
gelatin,
m/z 925.4326,
doubly-charged
ion
of
fragment
GEPGPTGVQGPPG-
(D)
glue
of
tortoise
shell
m/z
758.3530,
sequence
unknown.
(E)
deerhorn
glue
m/z
732.8282,
sequence
unknown.
glue
because
tortoise
corresponding
is
located
much
farther
from
these
four.
This
is believed
to be
donkey,
bovine,
pig,
and
deer
are
all
mammals,
while
the
is a reptile.
The
unknown
samples
were
clustered
in the
area,
as
expected.
3.3.
Identification
of
the
marker
peptides
Results
tify
of
data
RT
16.16
for
donkey
from
pharmalynx
from
this
study
demonstrate
that
it is possible
to iden-
the
markers
that
play
an
important
role
in the
classification
gelatins.
The
loading
plot
from
the
PCA
based
on
UPLC/MS
(8556
variables)
is shown
in Fig.
2B.
A number
of
ions
with
m/z
pairs
of
15.59
765.8665,
4.65
641.3065,
8.49
925.4326,
758.8589
and
8.53
732.8282
were
chosen
as
marker
peptides
each
gelatin.
To define
the
marker
peptides,
the
sequence
of
collagen,
bovine
collagen,
porcine
collagen
were
obtained
the
swiss-prot
database
(http://www.expasy.org)
and
Bio-
1.2
was
used
to identify
the
sequence
of
the
marker
peptides
at
PAGPIGPVGAR,
641.3065,
is the
bly
marker
of
Additionally,
sequence
ing
are
peptides
using
The
identified
The
of
each
gelatin,
which
was
accomplished
using.
The
ion
m/z
765.8556,
a doubly
charged
ion
of
the
fragment
GEAGPAG-
is
the
marker
of
donkey-hide
gelatin.
The
ion
at m/z
a
doubly
charged
ion
of
the
fragment
GEAGPSGPGPTGAR,
marker
of
bovine-hide
gelatin.
The
ion
at
m/z
925.4326,
a dou-
charged
ion
of
the
fragment
GEPGPTGVQGPPGPAGEEGK,
is
the
of
pig-hide
gelatin.
The
ion
at
m/z
758.3530
is the
marker
the
tortoise
shell
glue,
the
sequence
for
which
is unknown.
the
ion
at
m/z
732.8282
is
the
deer-horn
glue,
the
for
which
is
also
unknown.
The
selected
ion
monitor-
chromatograms
of
the
marker
and
corresponding
MSEspectra
shown
in Fig.
3.
However,
the
identification
of
most
marker
was
not
possible,
despite
searching
available
databases
the
accurate
molecular
weights
and
elemental
compositions.
markers
of
the
tortoise
shell
glue
and
deerhorn
glue
were
not
due
to the
lack
of
corresponding
collagen
sequences.
gelatins
from
different
sources
can
also
be
identified
using
the

Page 5

X.-L.
Cheng
et
al.
/ Journal
of
Pharmaceutical
and
Biomedical
Analysis
62 (2012) 191–
195
195
marker
matography.
peptide
of
each
gelatin
in selected
ion
monitoring
chro-
4.
Conclusion
A
UPLC/Q-TOF-MS
sample
profiling
method
coupled
with
PCA
has
sources.
for
of
The
a
first
systematically.
been
successfully
used
to classify
gelatins
from
different
The
UPLC/Q-TOF-MS
detection
coupled
with
PCA
allowed
details
of
the
samples
to be
profiled
so that
important
markers
differences
can
be
measured,
even
at low
concentration
levels.
markers
of
gelatins
can
be
used
to distinguish
one
gelatin
from
second
or to identify
gelatins
in a mixture.
As
a result,
this
is
the
time
that
differences
among
these
gelatins
have
been
observed
Acknowledgements
This
study
was
supported
in part
by
grants
from
the
National
Institute
istration
of
Quality
Chinese
Program
Republic
Technology
Key
Engineering,
technical
for
Food
and
Drug
Control,
the
State
Food
and
Drug
Admin-
(No.
2010A1),
the
National
Natural
Science
Foundation
China
(Nos.
30873356,
81001622),
the
project
“The
Platform
of
Standards
and
Information
System
Research
of
Traditional
Medicine”
(No.
2009ZX09308-004)
from
the
Important
of
Ministry
of
Science
and
Technology
of
the
People’s
of
China.
The
author
wishes
to thank
Xu
Bai
from
Waters
(Shanghai)
Co.,
Ltd.
and
Gui-Feng
Zhang
from
State
Laboratory
of
Biochemical
Engineering,
Institute
of
Process
and
the
Chinese
Academy
of
Sciences
for
their
expert
assistance.
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