Autonomous Dissociation-type Selection for Glycoproteomics Using a Real-Time Library Search

Tandem mass spectrometry (MS/MS) is the gold standard for intact glycopeptide identification, enabling peptide sequence elucidation and site-specific localization of glycan compositions. Beam-type collisional activation is generally sufficient for N-glycopeptides, while electron-driven dissociation...

Full description

Saved in:
Bibliographic Details
Published in:Journal of proteome research
Main Authors: Sutherland, Emmajay, Veth, Tim S., Barshop, William D., Russell, Jacob H., Kothlow, Kathryn, Canterbury, Jesse D., Mullen, Christopher, Bergen, David, Huang, Jingjing, Zabrouskov, Vlad, Huguet, Romain, McAlister, Graeme C., Riley, Nicholas M.
Format: Journal Article
Language:English
Published: 12-11-2024
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Abstract Tandem mass spectrometry (MS/MS) is the gold standard for intact glycopeptide identification, enabling peptide sequence elucidation and site-specific localization of glycan compositions. Beam-type collisional activation is generally sufficient for N-glycopeptides, while electron-driven dissociation is crucial for site localization in O-glycopeptides. Modern glycoproteomic methods often employ multiple dissociation techniques within a single LC-MS/MS analysis, but this approach frequently sacrifices sensitivity when analyzing multiple glycopeptide classes simultaneously. Here we explore the utility of intelligent data acquisition for glycoproteomics through real-time library searching (RTLS) to match oxonium ion patterns for on-the-fly selection of the appropriate dissociation method. By matching dissociation method with glycopeptide class, this autonomous dissociation-type selection (ADS) generates equivalent numbers of N-glycopeptide identifications relative to traditional beam-type collisional activation methods while also yielding comparable numbers of site-localized O-glycopeptide identifications relative to conventional electron transfer dissociation-based methods. The ADS approach represents a step forward in glycoproteomics throughput by enabling site-specific characterization of both N-and O-glycopeptides within the same LC-MS/MS acquisition.Tandem mass spectrometry (MS/MS) is the gold standard for intact glycopeptide identification, enabling peptide sequence elucidation and site-specific localization of glycan compositions. Beam-type collisional activation is generally sufficient for N-glycopeptides, while electron-driven dissociation is crucial for site localization in O-glycopeptides. Modern glycoproteomic methods often employ multiple dissociation techniques within a single LC-MS/MS analysis, but this approach frequently sacrifices sensitivity when analyzing multiple glycopeptide classes simultaneously. Here we explore the utility of intelligent data acquisition for glycoproteomics through real-time library searching (RTLS) to match oxonium ion patterns for on-the-fly selection of the appropriate dissociation method. By matching dissociation method with glycopeptide class, this autonomous dissociation-type selection (ADS) generates equivalent numbers of N-glycopeptide identifications relative to traditional beam-type collisional activation methods while also yielding comparable numbers of site-localized O-glycopeptide identifications relative to conventional electron transfer dissociation-based methods. The ADS approach represents a step forward in glycoproteomics throughput by enabling site-specific characterization of both N-and O-glycopeptides within the same LC-MS/MS acquisition.
AbstractList Tandem mass spectrometry (MS/MS) is the gold standard for intact glycopeptide identification, enabling peptide sequence elucidation and site-specific localization of glycan compositions. Beam-type collisional activation is generally sufficient for N-glycopeptides, while electron-driven dissociation is crucial for site localization in O-glycopeptides. Modern glycoproteomic methods often employ multiple dissociation techniques within a single LC-MS/MS analysis, but this approach frequently sacrifices sensitivity when analyzing multiple glycopeptide classes simultaneously. Here we explore the utility of intelligent data acquisition for glycoproteomics through real-time library searching (RTLS) to match oxonium ion patterns for on-the-fly selection of the appropriate dissociation method. By matching dissociation method with glycopeptide class, this autonomous dissociation-type selection (ADS) generates equivalent numbers of N-glycopeptide identifications relative to traditional beam-type collisional activation methods while also yielding comparable numbers of site-localized O-glycopeptide identifications relative to conventional electron transfer dissociation-based methods. The ADS approach represents a step forward in glycoproteomics throughput by enabling site-specific characterization of both N-and O-glycopeptides within the same LC-MS/MS acquisition.Tandem mass spectrometry (MS/MS) is the gold standard for intact glycopeptide identification, enabling peptide sequence elucidation and site-specific localization of glycan compositions. Beam-type collisional activation is generally sufficient for N-glycopeptides, while electron-driven dissociation is crucial for site localization in O-glycopeptides. Modern glycoproteomic methods often employ multiple dissociation techniques within a single LC-MS/MS analysis, but this approach frequently sacrifices sensitivity when analyzing multiple glycopeptide classes simultaneously. Here we explore the utility of intelligent data acquisition for glycoproteomics through real-time library searching (RTLS) to match oxonium ion patterns for on-the-fly selection of the appropriate dissociation method. By matching dissociation method with glycopeptide class, this autonomous dissociation-type selection (ADS) generates equivalent numbers of N-glycopeptide identifications relative to traditional beam-type collisional activation methods while also yielding comparable numbers of site-localized O-glycopeptide identifications relative to conventional electron transfer dissociation-based methods. The ADS approach represents a step forward in glycoproteomics throughput by enabling site-specific characterization of both N-and O-glycopeptides within the same LC-MS/MS acquisition.
Author Kothlow, Kathryn
Huguet, Romain
McAlister, Graeme C.
Russell, Jacob H.
Bergen, David
Huang, Jingjing
Sutherland, Emmajay
Riley, Nicholas M.
Veth, Tim S.
Canterbury, Jesse D.
Mullen, Christopher
Zabrouskov, Vlad
Barshop, William D.
Author_xml – sequence: 1
  givenname: Emmajay
  orcidid: 0000-0001-5150-4346
  surname: Sutherland
  fullname: Sutherland, Emmajay
  organization: Department of Chemistry, University of Washington, Seattle, Washington 98195, United States
– sequence: 2
  givenname: Tim S.
  orcidid: 0000-0002-2561-5437
  surname: Veth
  fullname: Veth, Tim S.
  organization: Department of Chemistry, University of Washington, Seattle, Washington 98195, United States
– sequence: 3
  givenname: William D.
  orcidid: 0000-0001-9517-2339
  surname: Barshop
  fullname: Barshop, William D.
  organization: Thermo Fisher Scientific, San Jose, California 95134, United States
– sequence: 4
  givenname: Jacob H.
  orcidid: 0009-0006-8054-7082
  surname: Russell
  fullname: Russell, Jacob H.
  organization: Department of Chemistry, University of Washington, Seattle, Washington 98195, United States
– sequence: 5
  givenname: Kathryn
  orcidid: 0009-0007-3252-0616
  surname: Kothlow
  fullname: Kothlow, Kathryn
  organization: Department of Chemistry, University of Washington, Seattle, Washington 98195, United States
– sequence: 6
  givenname: Jesse D.
  surname: Canterbury
  fullname: Canterbury, Jesse D.
  organization: Thermo Fisher Scientific, San Jose, California 95134, United States
– sequence: 7
  givenname: Christopher
  surname: Mullen
  fullname: Mullen, Christopher
  organization: Thermo Fisher Scientific, San Jose, California 95134, United States
– sequence: 8
  givenname: David
  surname: Bergen
  fullname: Bergen, David
  organization: Thermo Fisher Scientific, San Jose, California 95134, United States
– sequence: 9
  givenname: Jingjing
  surname: Huang
  fullname: Huang, Jingjing
  organization: Thermo Fisher Scientific, San Jose, California 95134, United States
– sequence: 10
  givenname: Vlad
  orcidid: 0000-0003-3567-9407
  surname: Zabrouskov
  fullname: Zabrouskov, Vlad
  organization: Thermo Fisher Scientific, San Jose, California 95134, United States
– sequence: 11
  givenname: Romain
  surname: Huguet
  fullname: Huguet, Romain
  organization: Thermo Fisher Scientific, San Jose, California 95134, United States
– sequence: 12
  givenname: Graeme C.
  surname: McAlister
  fullname: McAlister, Graeme C.
  organization: Thermo Fisher Scientific, San Jose, California 95134, United States
– sequence: 13
  givenname: Nicholas M.
  orcidid: 0000-0002-1536-2966
  surname: Riley
  fullname: Riley, Nicholas M.
  organization: Department of Chemistry, University of Washington, Seattle, Washington 98195, United States
BookMark eNo9kE9PwzAMxSM0JLbBR0DKkUtHnDT9c5wGDKRKSLCdOERp6kKmthlJd9i3X6cVTralZ_u934xMOtchIffAFsA4PGoTFru9dz26FhexYSzl4opMQQoZiZylk78-y8UNmYWwYwxkysSUfC0Pvetc6w6BPtkQnLG6t66L-uMe6Sc2aM4jrZ2n6-Zo3PjHmkC3wXbfVNMP1E20sS3SwpZe--Owp735uSXXtW4C3o11TrYvz5vVa1S8r99WyyIyABKiijGZZFyUPJOQa55WTOalTnMudGwqidLEWVVWokRZx6gxzgWI2ABCWUOSiDl5uNwdvP0eMPSqtcFg0-gOh1xKAM_SBCBjg1RepMa7EDzWau9tO1hWwNQZphpgqn-YaoQpTkcibvI
Cites_doi 10.1002/rcm.8191
10.1021/acs.analchem.3c01111
10.1021/acs.jproteome.2c00519
10.1016/j.sbi.2011.08.005
10.1007/s13361-015-1183-1
10.1074/mcp.R120.002277
10.1007/BF01049915
10.1007/978-3-030-70115-4_1
10.1007/978-1-0716-1241-5_8
10.1155/2012/560391
10.1039/D2MO00244B
10.1021/acs.jproteome.3c00858
10.1021/acs.jproteome.0c00218
10.1074/mcp.MR117.000126
10.1002/chem.201503659
10.1007/s13361-018-1945-7
10.1073/pnas.2012196117
10.1038/s43586-022-00128-4
10.1021/acs.analchem.2c05141
10.1021/pr2002726
10.1038/s41551-023-01067-5
10.1101/2024.07.06.602348
10.1038/s41467-022-31062-4
10.1016/j.sbi.2019.02.007
10.1021/pr500898r
10.1021/jasms.3c00375
10.1016/j.ijms.2017.09.002
10.1038/s41467-024-47772-w
10.1021/acs.analchem.3c04497
10.1038/s41580-020-00294-x
10.3390/ijms24097869
10.1021/acs.analchem.3c04484
10.1016/j.ijms.2012.08.031
10.1016/j.cbpa.2023.102272
10.1021/acs.analchem.7b04810
10.1021/jasms.0c00482
10.1021/acs.analchem.2c04633
10.1021/pr300257c
10.1074/mcp.RA120.002260
10.1021/ac500945m
10.1093/glycob/cwac026
10.1074/mcp.RA117.000240
10.1016/j.mcpro.2021.100167
10.1080/19420862.2018.1494106
10.1038/s41592-020-00985-5
10.1101/2023.09.26.559616
10.1021/acs.jproteome.3c00085
10.1016/j.mcpro.2022.100486
10.1038/s41467-017-00535-2
10.1002/pmic.201800282
10.1038/s41592-021-01209-0
10.1021/jasms.0c00425
10.1021/acs.analchem.1c04336
10.1021/acs.chemrev.7b00732
10.1038/s41467-019-09222-w
10.1021/acs.jproteome.8b00587
10.1016/j.mcpro.2022.100439
10.1093/nar/gkab1038
10.1038/srep37189
10.1021/acs.analchem.0c01218
10.1007/s13361-017-1701-4
10.1021/acs.analchem.4c01450
10.1021/jasms.9b00089
10.3390/ijms22105369
10.1002/pmic.202200156
10.1111/febs.16148
10.1021/acs.analchem.0c02950
10.1021/acschembio.1c00932
10.1007/s13361-018-1909-y
ContentType Journal Article
DBID AAYXX
CITATION
7X8
DOI 10.1021/acs.jproteome.4c00723
DatabaseName CrossRef
MEDLINE - Academic
DatabaseTitle CrossRef
MEDLINE - Academic
DatabaseTitleList MEDLINE - Academic
DeliveryMethod fulltext_linktorsrc
Discipline Chemistry
EISSN 1535-3907
ExternalDocumentID 10_1021_acs_jproteome_4c00723
GroupedDBID ---
4.4
53G
55A
5GY
5VS
7~N
AABXI
AAHBH
AAYXX
ABJNI
ABMVS
ABQRX
ABUCX
ACGFS
ACS
ADHLV
AEESW
AENEX
AFEFF
AHGAQ
ALMA_UNASSIGNED_HOLDINGS
AQSVZ
BAANH
CITATION
CS3
CUPRZ
DU5
EBS
ED~
F5P
GGK
GNL
IH9
IHE
JG~
P2P
RNS
ROL
UI2
VF5
VG9
W1F
7X8
ID FETCH-LOGICAL-c1151-d0056823b28519a27d059ba7923a4cd5e5c48dbd3be5f4eae493134c1e1bf1663
IEDL.DBID ACS
ISSN 1535-3893
1535-3907
IngestDate Fri Nov 15 20:28:26 EST 2024
Wed Nov 13 12:50:46 EST 2024
IsPeerReviewed true
IsScholarly true
Language English
LinkModel DirectLink
MergedId FETCHMERGED-LOGICAL-c1151-d0056823b28519a27d059ba7923a4cd5e5c48dbd3be5f4eae493134c1e1bf1663
Notes ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
ORCID 0000-0002-2561-5437
0009-0007-3252-0616
0009-0006-8054-7082
0000-0001-9517-2339
0000-0003-3567-9407
0000-0001-5150-4346
0000-0002-1536-2966
PQID 3128761180
PQPubID 23479
ParticipantIDs proquest_miscellaneous_3128761180
crossref_primary_10_1021_acs_jproteome_4c00723
PublicationCentury 2000
PublicationDate 2024-11-12
20241112
PublicationDateYYYYMMDD 2024-11-12
PublicationDate_xml – month: 11
  year: 2024
  text: 2024-11-12
  day: 12
PublicationDecade 2020
PublicationTitle Journal of proteome research
PublicationYear 2024
References ref9/cit9
ref45/cit45
ref3/cit3
ref27/cit27
ref63/cit63
ref56/cit56
ref16/cit16
ref52/cit52
ref23/cit23
ref8/cit8
ref31/cit31
ref59/cit59
ref2/cit2
ref34/cit34
ref37/cit37
ref20/cit20
ref48/cit48
ref60/cit60
ref17/cit17
ref10/cit10
ref35/cit35
ref53/cit53
ref19/cit19
ref21/cit21
ref42/cit42
ref46/cit46
ref49/cit49
ref13/cit13
ref61/cit61
Varki A. (ref1/cit1) 2022
ref67/cit67
ref24/cit24
ref38/cit38
ref50/cit50
ref64/cit64
ref54/cit54
ref6/cit6
ref36/cit36
ref18/cit18
ref65/cit65
ref11/cit11
ref25/cit25
ref29/cit29
ref32/cit32
ref39/cit39
ref14/cit14
ref57/cit57
ref5/cit5
ref51/cit51
ref43/cit43
ref28/cit28
ref40/cit40
ref68/cit68
ref26/cit26
ref55/cit55
ref69/cit69
ref12/cit12
ref15/cit15
ref62/cit62
ref66/cit66
ref41/cit41
ref58/cit58
ref22/cit22
ref33/cit33
ref4/cit4
ref30/cit30
ref47/cit47
ref44/cit44
ref70/cit70
ref7/cit7
References_xml – ident: ref16/cit16
  doi: 10.1002/rcm.8191
– ident: ref68/cit68
  doi: 10.1021/acs.analchem.3c01111
– ident: ref15/cit15
  doi: 10.1021/acs.jproteome.2c00519
– ident: ref4/cit4
  doi: 10.1016/j.sbi.2011.08.005
– ident: ref31/cit31
  doi: 10.1007/s13361-015-1183-1
– ident: ref39/cit39
  doi: 10.1074/mcp.R120.002277
– ident: ref50/cit50
  doi: 10.1007/BF01049915
– ident: ref3/cit3
  doi: 10.1007/978-3-030-70115-4_1
– ident: ref44/cit44
  doi: 10.1007/978-1-0716-1241-5_8
– ident: ref35/cit35
  doi: 10.1155/2012/560391
– ident: ref48/cit48
  doi: 10.1039/D2MO00244B
– ident: ref62/cit62
  doi: 10.1021/acs.jproteome.3c00858
– ident: ref18/cit18
  doi: 10.1021/acs.jproteome.0c00218
– ident: ref19/cit19
  doi: 10.1074/mcp.MR117.000126
– ident: ref52/cit52
  doi: 10.1002/chem.201503659
– ident: ref26/cit26
  doi: 10.1007/s13361-018-1945-7
– ident: ref45/cit45
  doi: 10.1073/pnas.2012196117
– ident: ref7/cit7
  doi: 10.1038/s43586-022-00128-4
– ident: ref43/cit43
  doi: 10.1021/acs.analchem.2c05141
– ident: ref34/cit34
  doi: 10.1021/pr2002726
– ident: ref56/cit56
  doi: 10.1038/s41551-023-01067-5
– ident: ref69/cit69
  doi: 10.1101/2024.07.06.602348
– ident: ref55/cit55
  doi: 10.1038/s41467-022-31062-4
– ident: ref20/cit20
  doi: 10.1016/j.sbi.2019.02.007
– ident: ref51/cit51
  doi: 10.1021/pr500898r
– ident: ref14/cit14
  doi: 10.1021/jasms.3c00375
– ident: ref24/cit24
  doi: 10.1016/j.ijms.2017.09.002
– volume-title: Essentials of Glycobiology
  year: 2022
  ident: ref1/cit1
  contributor:
    fullname: Varki A.
– ident: ref38/cit38
  doi: 10.1038/s41467-024-47772-w
– ident: ref10/cit10
  doi: 10.1021/acs.analchem.3c04497
– ident: ref2/cit2
  doi: 10.1038/s41580-020-00294-x
– ident: ref63/cit63
  doi: 10.3390/ijms24097869
– ident: ref66/cit66
  doi: 10.1021/acs.analchem.3c04484
– ident: ref60/cit60
  doi: 10.1016/j.ijms.2012.08.031
– ident: ref9/cit9
  doi: 10.1016/j.cbpa.2023.102272
– ident: ref21/cit21
  doi: 10.1021/acs.analchem.7b04810
– ident: ref64/cit64
  doi: 10.1021/jasms.0c00482
– ident: ref41/cit41
  doi: 10.1021/acs.analchem.2c04633
– ident: ref32/cit32
  doi: 10.1021/pr300257c
– ident: ref46/cit46
  doi: 10.1074/mcp.RA120.002260
– ident: ref33/cit33
  doi: 10.1021/ac500945m
– ident: ref37/cit37
  doi: 10.1093/glycob/cwac026
– ident: ref54/cit54
  doi: 10.1074/mcp.RA117.000240
– ident: ref30/cit30
  doi: 10.1016/j.mcpro.2021.100167
– ident: ref57/cit57
  doi: 10.1080/19420862.2018.1494106
– ident: ref47/cit47
  doi: 10.1038/s41592-020-00985-5
– ident: ref36/cit36
  doi: 10.1101/2023.09.26.559616
– ident: ref42/cit42
  doi: 10.1021/acs.jproteome.3c00085
– ident: ref58/cit58
  doi: 10.1016/j.mcpro.2022.100486
– ident: ref12/cit12
  doi: 10.1038/s41467-017-00535-2
– ident: ref11/cit11
  doi: 10.1002/pmic.201800282
– ident: ref13/cit13
  doi: 10.1038/s41592-021-01209-0
– ident: ref65/cit65
  doi: 10.1021/jasms.0c00425
– ident: ref40/cit40
  doi: 10.1021/acs.analchem.1c04336
– ident: ref8/cit8
  doi: 10.1021/acs.chemrev.7b00732
– ident: ref23/cit23
  doi: 10.1038/s41467-019-09222-w
– ident: ref27/cit27
  doi: 10.1021/acs.jproteome.8b00587
– ident: ref28/cit28
  doi: 10.1016/j.mcpro.2022.100439
– ident: ref49/cit49
  doi: 10.1093/nar/gkab1038
– ident: ref59/cit59
  doi: 10.1038/srep37189
– ident: ref61/cit61
  doi: 10.1021/acs.analchem.0c01218
– ident: ref22/cit22
  doi: 10.1007/s13361-017-1701-4
– ident: ref67/cit67
  doi: 10.1021/acs.analchem.4c01450
– ident: ref17/cit17
  doi: 10.1021/jasms.9b00089
– ident: ref53/cit53
  doi: 10.3390/ijms22105369
– ident: ref6/cit6
  doi: 10.1002/pmic.202200156
– ident: ref5/cit5
  doi: 10.1111/febs.16148
– ident: ref25/cit25
  doi: 10.1021/acs.analchem.0c02950
– ident: ref29/cit29
  doi: 10.1021/acschembio.1c00932
– ident: ref70/cit70
  doi: 10.1007/s13361-018-1909-y
SSID ssj0015703
Score 2.4944038
Snippet Tandem mass spectrometry (MS/MS) is the gold standard for intact glycopeptide identification, enabling peptide sequence elucidation and site-specific...
SourceID proquest
crossref
SourceType Aggregation Database
Title Autonomous Dissociation-type Selection for Glycoproteomics Using a Real-Time Library Search
URI https://www.proquest.com/docview/3128761180
hasFullText 1
inHoldings 1
isFullTextHit
isPrint
link http://sdu.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlZ25T8MwFMYt6AILN6JcMhKr29ixc4xVDzoxUJCQGCJfkYogrWg78N_zXo6iDh06ZnGiz1beZz-_3yPk0TvEzEnFnAs8nlalzAR5zmwqvcmDSAQGM7rjSfz8ngyGiMnpbsngC97VdtH5LKEFs2_fkRZZ1yXdM45wFff6k3XWAGlSFR9VMQzETcXOtlE2Y9Hmr7iML6Pjnb_shBzVVpL2qrk_JXu-OCMH_aaD2zn56K2WWLMAm3s6mP7PA8NzVzopO-DAIwXfSp--fu2sfsvULmh5lYBq-gJGkmGdCK0rHGh1QfmCvI2Gr_0xq5spMAumjzOH0M9EhEaAx0q1iB0YK6MRH6ildcorKxNnXGi8yqXXXqYhD6Xlnpucgy-5JK1iVvgrQhOdR7B_tch2kx67-mkPm1pndapy5VSbdBpZs3nFzMjKXLfgGWiWrTXLas3a5KERPwOJMGWhCw_iZCGEzzhCTN31roPekEMBBgTrBrm4Ja3lz8rfkf2FW92Xq-YPbA_EAw
link.rule.ids 315,782,786,2769,27933,27934
linkProvider American Chemical Society
openUrl ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Autonomous+Dissociation-type+Selection+for+Glycoproteomics+Using+a+Real-Time+Library+Search&rft.jtitle=Journal+of+proteome+research&rft.au=Sutherland%2C+Emmajay&rft.au=Veth%2C+Tim+S&rft.au=Barshop%2C+William+D&rft.au=Russell%2C+Jacob+H&rft.date=2024-11-12&rft.issn=1535-3907&rft.eissn=1535-3907&rft_id=info:doi/10.1021%2Facs.jproteome.4c00723&rft.externalDBID=NO_FULL_TEXT
thumbnail_l http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=1535-3893&client=summon
thumbnail_m http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=1535-3893&client=summon
thumbnail_s http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=1535-3893&client=summon