Integrated computational pipeline for the complete sequencing of...
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Integrated computational pipeline for the complete sequencing
of glycopeptide using HCD/CID-MS/MS and MS3
Mingqi Liu, Wenfeng Zeng, Yang Zhang, Jianqiang Wu, Simin He, Pengyuan Yang
Institutes of Biomedical Sciences, Fudan University, Shanghai
Institute of Computing Technology, Chinese Academy of Sciences, Beijing
CNCP-2014, 11.12-13
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Biological function of site-specific glycosylation:
Example of IgG
Science 313, 670-673 (2006);
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Long term goal:
Interpretation of intact glycopeptide in complex sample
· Study of site-specific glycosylation is developing rapidly
· Identification of intact glycopeptide using LC-MS is the method of
choice at the moment
· “Small” obstacle: low abundance, low ionization efficiency
· “Big” obstacle: incomplete information from single MS spectrum
PSM : peptide - spectrum match
“GPSM” : glycopeptide - (2~3) spectra match
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Long term goal:
Interpretation of intact glycopeptide in complex sample
· Possible strategies
· Our pipeline
· Challenges
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Complete sequencing of glycopeptide:
CID + ETD?
· Typical fragmentation methods:
CID: collision based, in trap
HCD: collision based, in beam-type module
ETD: electric based
J. Proteome Res., 2005, 4 (2), 628-632
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Glycopeptide spectra : ETD
Peptide Glycan
· ETD is widely used in
O-glycopeptide profiling.
Large-scale N-
glycopeptide profiling using
ETD is less common.
· It seems that ETD has
the “m/z” barrier around
1,000 ~ 1,100. No such
barrier is observed in CID.
Anal. Chem. 2009, 81, 3208–3215
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Glycopeptide spectra : ETD
Anal. Chem. 2013, 85, 5023-5032
m/z :
1132.7
m/z :
1415.6
m/z :
944.1
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Glycopeptide spectra : CID
J. Proteome Res. 2014, 13, 3121-3129
· De-glycosylation is
required. Application is
limited to N-glycosylation.
· Strictly speaking,
information of peptide
backbone is incomplete
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Long term goal:
Interpretation of intact glycopeptide in complex sample
· Possible strategies
· Our pipeline
· Challenges
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Integrated computational pipeline for the complete sequencing of
glycopeptide using HCD/CID-MS/MS and MS3
· Sample:
Tryptic glycopeptides
from mixture of seven
standard glycoproteins
· Instrument:
Thermo LTQ Orbitrap
Fusion
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HCD-MS/MS @ 40ev :
Interpretation of the mass of peptide backbone
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HCD-MS/MS @ 40ev :
Interpretation of the mass of peptide backbone
· Interpretation of
HCD-MS/MS is protein
database free
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HCD-MS/MS @ 40ev :
Interpretation of the mass of peptide backbone
· Target-decoy analysis
on HCD-MS/MS. The
cutoff we used is 0.4.
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CID-MS/MS:
Interpretation of the glycan
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CID-MS/MS:
Interpretation of the glycan
· Glycopeptide CID-MS/MS:
1) Extensive glycosidic bond
cleavage
2) Intensity of individual
fragments is variable
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CID-MS2
HCD-MS2@40ev
MS3 from where
and how?
Interpretation of peptide sequence from MS3
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Interpretation of peptide sequence from MS3
· Appropriate target and
MS parameter for MS3
· We have tested
CID-MS/MS-DDA-MS3
CID-MS/MS-DIA-MS3
HCD-MS/MS-DDA-MS3
HCD-MS/MS-DIA-MS3
CID or HCD?
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· HCD-MS/MS based MS3 can only be performed on
Orbitrap Fusion at the moment*
Interpretation of peptide sequence from MS3
Q
OT
IT
Q
OT
Q IT
Ion source
Ion source
Before Orbitrap Fusion:
Orbitrap Fusion:
IT: ion trap
(CID, MSn)
OT: Orbitrap
(Detector)
Q: Quadrupole
(HCD)
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Interpretation of peptide sequence from MS3
· Conventional DDA MS3 from HCD-MS/MS could collect a
lot of spectra with peptide sequence information
· Peptide database searching software can be used for
peptide sequence in MS3
(pFind, Mascot, SEQUEST, Maxquant, etc.)
· We have develop an integrated software package for the
complete sequencing of glycopeptide from MS/MS and MS3
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Interpretation of peptide sequence from MS3:
Spectral quality
Identified peptide backbone sequence
100semi
500semi
2500semi
Allsemi
CANLVPVPITJATLDR Y Y
EEQFJSTFR Y Y Y
EEQFJSTYR Y Y
EEQYJSTYR Y Y Y
EJGTISR Y
EJGTVSR
FSIJTTNVMGTSLTVR Y
FYFTPJK Y Y Y
FYFTPJKTEDTIFLR Y Y Y YGLTFQQJASSM Y Y Y YGNEANYYSJATTDEHGLVQF Y Y
JNSDISSTR Y Y
JSSYLNVQR Y
LAGKPTHVJVS Y Y Y YLAGKPTHVJVSVVM Y Y Y YLAGKPTHVJVSVVMAEVDGTC Y
LAGKPTHVJVSVVMAEVDGTCY Y Y
LVPVPITJATLDQITGK Y Y Y YLVPVPITJATLDR Y Y Y YMJVSVCGLYTYGK Y
MVSHHJLTTG Y Y Y
MVSHHJLTTGA Y Y Y YMVSHHJLTTGAT Y Y Y YMVSHHJLTTGATLINEQWLLTTAK Y Y
NEEYJK Y Y Y YNLFLJH Y Y Y
NLFLJHSEJATAK Y Y Y Y
· Spectral quality of MS3 was
tested by changing the size of
protein database*
· The quality MS3 spectra is
sufficient for protein database
searching
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Complete sequencing of glycopeptide
· For each glycopeptide
identification, a pair of
HCD/CID-MS/MS is needed
· A group of glycopeptide
identification shares one or
more MS3 spectra for peptide
backbone sequencing
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Exemplary spectra:
CID-MS/MS
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Exemplary spectra:
HCD-MS/MS
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Exemplary spectra:
MS3
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Long term goal:
Interpretation of intact glycopeptide in complex sample
· Possible strategies
· Our pipeline
· Challenges
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Application of our pipeline to complex sample:
Potential challenge
· MS/MS spectral processing
Protein-database free algorithm should work fine
· MS/MS spectral collection
We intentionally split MS/MS and MS3 spectral collection into
two MS runs, therefore the balance between quality and
quantity should work well
· MS3 spectral processing
Conventional protein database searching of tryptic peptide
· MS3 spectral collection
Is the sensitivity of MS3 enough?
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Application of our pipeline to complex sample:
Challenge in MS3
· For MS/MS, the latest instrument shows almost zero
difference in terms of sensitivity between IT and OT.
· However, for MS3, it is completely different.
DDA MS3 from
HCD-MS/MS
IT as
detector
OT as
detector
Results
shown today
Nothing
AGC target: maximum
Accumulation time: 500ms
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Application of our pipeline to complex sample:Top 500 MS3 TIC – IT vs OT
3
3.5
4
4.5
5
5.5
6
0 100 200 300 400 500
IT
3
3.5
4
4.5
5
5.5
6
0 100 200 300 400 500
OT
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Conclusion
· We have developed Integrated computational pipeline for the complete sequencing of glycopeptide using HCD/CID-MS/MS and MS3
· We will try to interpret glycopeptide in complex sample after some fine tuning in MS3 spectral collection
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Acknowledgement
· IBS, Fudan UniversityPr. Pengyuan Yang
Yang ZhangPan Fang
Guoquan YanWeiqian Cao
· ICT, CASPr. Simin HeWenfeng ZengJianqiang WuHao ChiRuixiang Sun
· Thermo Fisher Scientific, ShanghaiAiying Nie