digests a and b digest c trastuzumab · 2014. 6. 12. · digests. a total of 8229 features (charge...
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INTRODUCTION
Sequence variants (SV) are unintended amino acid
substitution in the primary structure, and are
classified as product-related impurities. The presence of sequence variants may pose concerns
regarding bioactivity, stability, and immunogenicity.
Sequence variants are usually present at very low-
level in a therapeutic protein. From an analytical
stand point, the detection and characterizing SV in a complex digest mixture that is several orders of
magnitude more concentrated, remains a significant
challenge.
A comparative analytical strategy is presented to
identify sequence variant among multiple samples. The strategy was developed and tested by analyzing
monoclonal antibody samples which contain spiked
synthetic peptides with amino acid substitutions.
SEQUENCE VARIANT IDENTIFICATION STRATEGIES BASED ON LC/MS PEPTIDE MAPPING ANALYSIS.
Stephane Houel1; Scott Geromanos1, Andrew Tudor2, Barry Dyson2, Ying Qing Yu1; Weibin Chen1 1Waters Corp., Milford, MA 01757; 2Waters Corp., Manchester, UK.
EXPERIMENTAL
Sample Preparation: Three tryptic digests of Trastuzumab (Digest A, B or C) were prepared separately, each at a final
concentration of 2.4 picomole/µL. In digest C, two synthetic peptides of T14 containing substituted amino acid residues (see
Table 2) were spiked at 1.8 femtomole/µL.
LC-MS Analysis: Each sample was analyzed in replicate injection
(4µL inj.). A blank injection was performed between the samples to minimize the sample carryover. The samples were analyzed in
the order of Digest A, Digest C and finally Digest B.
LC/MS Conditions:
LC: Waters ACQUTIY UPLC I-Class Column: Acquity UPLC PST 2.1x150mm BEH C18 300Å, 1.7 µm
MS Conditions: Instrument Waters SynaptTM G2-Si HDMS
Mode: ESI positive mode Capillary Voltage: 3.0 kV
Cone Voltage: 10 V Source Temperature: 100 °C
Desolvation Temperature: 350 °C
Informatics:
Progenesis QI
Figure 1. Data were collected using Waters Synapt G2-Si
CONCLUSIONS
Progenesis can detect and quantify low abundance sequence variant peptides (0.1%)
in a monoclonal antibody digest.
HD-DDA spectra of sequence variant peptides loaded on a 2.1 mm column at 7
femtomoles provides enough information to pin-point the substitution.
Variability increases for features at low abundance and between digest samples.
Nevertheless, more than 95% of the detected features are common to all three
digests.
RESULTS & DISCUSSION
Figure 2: Proposed workflow to identify sequence variant peptides.
Workflow for Sequence Variant Identification Table 1: Native and mutant T14 feature characteristics.
Table 2: Quantification of native and mutant T14 peptides.
Quantification based on Progenesis QI
Progenesis Provides Intuitive Visualization Interface to Compare Feature Difference
Figure 7: 3D montage of features #11 and #11400 for each run of the three digests.
Feature #11 Feature #11400
Digest C
Digest B
Digest A
0
10
20
30
40
50
60
70
80
90
100
1.E-16 1.E-14 1.E-12 1.E-10 1.E-08 1.E-06 1.E-04 1.E-02 1.E+00
CV
(%
)
Anova P value
Digest A
Digest B
Digest C
0
50
100
150
200
250
300
0 5 10 15 20 25 30
Fre
qu
en
cy (
Co
un
ts)
CV (%)
1E4< Abundance <3E5
3E3< Abundance <1E4
1E3< Abundance <3E3
2E2< Abundance <1E3
1E1< Abundance <2E2
0
100
200
300
400
500
600
700
0 5 10 15 20 25 30
Fre
qu
en
cy (
Co
un
ts)
CV (%)
Digest A
Digest B
Digest C
All Digests
0
10
20
30
40
50
60
70
80
90
100
0 5 10 15 20 25 30
Cu
mu
lati
ve R
ela
tive
Fre
qu
en
cy (
%)
CV (%)
Digest A
Digest B
Digest C
All Digests
Figure 4: Frequency (a) and cumulative relative frequen-cy (b) diagrams of the coefficient of variation (CV) for each digest individually (intra-run variability) as well as
for all of the runs (inter-digest variability)
Figure 5: Venn diagram showing all the features detected in all 3 digests. A total of 8229 features (charge states 2+ to 13+) were detected, among which 95.15% are common in all three samples. Less than 2% of features are unique to any one digest, which can be automatically generated and exported to MassLynx to ac-
quire high quality HD-DDA spectra (see figure 8) for SV identification.
Digest B
Digest C
Digest A
7830(95.15%)
9(0.11%)
96(1.17%)
Figure 6: Relationship between the Anova p val-ue and the coefficient of variation (CV) for unique features to each digest.
Figure 3: Frequency (a) and cu-mulative relative frequency (b) diagrams of the coefficient of variation (CV) for digest A at different abundance ranges.
Raw Data
LC-HDMSE
U n d e r s t a n d ,
R e v i e w a n d
Process LC-HDMSE
Data Collected
from an Analytical
Setting for SV
Identification
Figure 8: HD-DDA spectra of T14 with one (N9S) or two substitutions (N3S and N9S).
VDSALQSGSSQESVTEQDSK
VDNALQSGSSQESVTEQDSK
b3 b4 b5 b6 b7 b9 b11
y4y3 y5 y7 y9 y10 y14
y8
y6
y6
y7
y8
y9
y5y4
y3
y10
b5
b6
b10
HD-DDA Spectra Aid in Sequence Variant Peptide Identification
Dat
a P
roce
ssin
g
Digests A and B Digest C
Reduction/Alkylation
Buffer exchange
Trypic digestion
TRASTUZUMAB
Sequence variant peptides spiked into an aliquot of digest C
Buffer A added toan aliquot of digests A and B
Sam
ple
Pre
par
atio
nD
ata
Acq
uis
itio
n
LC-HDMSe
Dat
a P
roce
ssin
g
Detection of unique features: Sequence Variant candidates
LC-DDA/HD-DDAwith inclusion ListD
ata
Acq
uis
itio
n
(Sequence Variant Search in UNIFI:Under Development)
a)
a)
b)
0
10
20
30
40
50
60
70
80
90
100
0 5 10 15 20 25 30
Cu
mu
lati
ve R
elat
ive
Freq
uen
cy (
%)
CV (%)
1E4< Abundance <3E5
3E3< Abundance <1E4
1E3< Abundance <3E3
2E2< Abundance <1E3
1E1< Abundance <2E2
b)