Integrated GlycoProteome Analyzer (I-GPA) for Automated Identification and Quantitation of Site-Specific N-Glycosylation

Gun Wook Park, Jin Young Kim, Heeyoun Hwang, Ju Yeon Lee, Young Hee Ahn, Hyun Kyoung Lee, Eun Sun Ji, Kwang Hoe Kim, Hoi Keun Jeong, Ki Na Yun, Yong Sam Kim, Jeong Heon Ko, Hyun Joo An, Jae Han Kim, Young-Ki Paik, Jong Shin Yoo

Research output: Contribution to journalArticle

30 Citations (Scopus)

Abstract

Human glycoproteins exhibit enormous heterogeneity at each N-glycosite, but few studies have attempted to globally characterize the site-specific structural features. We have developed Integrated GlycoProteome Analyzer (I-GPA) including mapping system for complex N-glycoproteomes, which combines methods for tandem mass spectrometry with a database search and algorithmic suite. Using an N-glycopeptide database that we constructed, we created novel scoring algorithms with decoy glycopeptides, where 95 N-glycopeptides from standard α1-acid glycoprotein were identified with 0% false positives, giving the same results as manual validation. Additionally automated label-free quantitation method was first developed that utilizes the combined intensity of top three isotope peaks at three highest MS spectral points. The efficiency of I-GPA was demonstrated by automatically identifying 619 site-specific N-glycopeptides with FDR ≤ 1%, and simultaneously quantifying 598 N-glycopeptides, from human plasma samples that are known to contain highly glycosylated proteins. Thus, I-GPA platform could make a major breakthrough in high-throughput mapping of complex N-glycoproteomes, which can be applied to biomarker discovery and ongoing global human proteome project.

Original languageEnglish
Article number21175
JournalScientific reports
Volume6
DOIs
Publication statusPublished - 2016 Feb 17

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Glycopeptides
Glycosylation
Glycoproteins
Databases
Proteome
Tandem Mass Spectrometry
Isotopes
Biomarkers
Acids
Proteins

All Science Journal Classification (ASJC) codes

  • General

Cite this

Park, Gun Wook ; Kim, Jin Young ; Hwang, Heeyoun ; Lee, Ju Yeon ; Ahn, Young Hee ; Lee, Hyun Kyoung ; Ji, Eun Sun ; Kim, Kwang Hoe ; Jeong, Hoi Keun ; Yun, Ki Na ; Kim, Yong Sam ; Ko, Jeong Heon ; An, Hyun Joo ; Kim, Jae Han ; Paik, Young-Ki ; Yoo, Jong Shin. / Integrated GlycoProteome Analyzer (I-GPA) for Automated Identification and Quantitation of Site-Specific N-Glycosylation. In: Scientific reports. 2016 ; Vol. 6.
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title = "Integrated GlycoProteome Analyzer (I-GPA) for Automated Identification and Quantitation of Site-Specific N-Glycosylation",
abstract = "Human glycoproteins exhibit enormous heterogeneity at each N-glycosite, but few studies have attempted to globally characterize the site-specific structural features. We have developed Integrated GlycoProteome Analyzer (I-GPA) including mapping system for complex N-glycoproteomes, which combines methods for tandem mass spectrometry with a database search and algorithmic suite. Using an N-glycopeptide database that we constructed, we created novel scoring algorithms with decoy glycopeptides, where 95 N-glycopeptides from standard α1-acid glycoprotein were identified with 0{\%} false positives, giving the same results as manual validation. Additionally automated label-free quantitation method was first developed that utilizes the combined intensity of top three isotope peaks at three highest MS spectral points. The efficiency of I-GPA was demonstrated by automatically identifying 619 site-specific N-glycopeptides with FDR ≤ 1{\%}, and simultaneously quantifying 598 N-glycopeptides, from human plasma samples that are known to contain highly glycosylated proteins. Thus, I-GPA platform could make a major breakthrough in high-throughput mapping of complex N-glycoproteomes, which can be applied to biomarker discovery and ongoing global human proteome project.",
author = "Park, {Gun Wook} and Kim, {Jin Young} and Heeyoun Hwang and Lee, {Ju Yeon} and Ahn, {Young Hee} and Lee, {Hyun Kyoung} and Ji, {Eun Sun} and Kim, {Kwang Hoe} and Jeong, {Hoi Keun} and Yun, {Ki Na} and Kim, {Yong Sam} and Ko, {Jeong Heon} and An, {Hyun Joo} and Kim, {Jae Han} and Young-Ki Paik and Yoo, {Jong Shin}",
year = "2016",
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Park, GW, Kim, JY, Hwang, H, Lee, JY, Ahn, YH, Lee, HK, Ji, ES, Kim, KH, Jeong, HK, Yun, KN, Kim, YS, Ko, JH, An, HJ, Kim, JH, Paik, Y-K & Yoo, JS 2016, 'Integrated GlycoProteome Analyzer (I-GPA) for Automated Identification and Quantitation of Site-Specific N-Glycosylation', Scientific reports, vol. 6, 21175. https://doi.org/10.1038/srep21175

Integrated GlycoProteome Analyzer (I-GPA) for Automated Identification and Quantitation of Site-Specific N-Glycosylation. / Park, Gun Wook; Kim, Jin Young; Hwang, Heeyoun; Lee, Ju Yeon; Ahn, Young Hee; Lee, Hyun Kyoung; Ji, Eun Sun; Kim, Kwang Hoe; Jeong, Hoi Keun; Yun, Ki Na; Kim, Yong Sam; Ko, Jeong Heon; An, Hyun Joo; Kim, Jae Han; Paik, Young-Ki; Yoo, Jong Shin.

In: Scientific reports, Vol. 6, 21175, 17.02.2016.

Research output: Contribution to journalArticle

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AU - Park, Gun Wook

AU - Kim, Jin Young

AU - Hwang, Heeyoun

AU - Lee, Ju Yeon

AU - Ahn, Young Hee

AU - Lee, Hyun Kyoung

AU - Ji, Eun Sun

AU - Kim, Kwang Hoe

AU - Jeong, Hoi Keun

AU - Yun, Ki Na

AU - Kim, Yong Sam

AU - Ko, Jeong Heon

AU - An, Hyun Joo

AU - Kim, Jae Han

AU - Paik, Young-Ki

AU - Yoo, Jong Shin

PY - 2016/2/17

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N2 - Human glycoproteins exhibit enormous heterogeneity at each N-glycosite, but few studies have attempted to globally characterize the site-specific structural features. We have developed Integrated GlycoProteome Analyzer (I-GPA) including mapping system for complex N-glycoproteomes, which combines methods for tandem mass spectrometry with a database search and algorithmic suite. Using an N-glycopeptide database that we constructed, we created novel scoring algorithms with decoy glycopeptides, where 95 N-glycopeptides from standard α1-acid glycoprotein were identified with 0% false positives, giving the same results as manual validation. Additionally automated label-free quantitation method was first developed that utilizes the combined intensity of top three isotope peaks at three highest MS spectral points. The efficiency of I-GPA was demonstrated by automatically identifying 619 site-specific N-glycopeptides with FDR ≤ 1%, and simultaneously quantifying 598 N-glycopeptides, from human plasma samples that are known to contain highly glycosylated proteins. Thus, I-GPA platform could make a major breakthrough in high-throughput mapping of complex N-glycoproteomes, which can be applied to biomarker discovery and ongoing global human proteome project.

AB - Human glycoproteins exhibit enormous heterogeneity at each N-glycosite, but few studies have attempted to globally characterize the site-specific structural features. We have developed Integrated GlycoProteome Analyzer (I-GPA) including mapping system for complex N-glycoproteomes, which combines methods for tandem mass spectrometry with a database search and algorithmic suite. Using an N-glycopeptide database that we constructed, we created novel scoring algorithms with decoy glycopeptides, where 95 N-glycopeptides from standard α1-acid glycoprotein were identified with 0% false positives, giving the same results as manual validation. Additionally automated label-free quantitation method was first developed that utilizes the combined intensity of top three isotope peaks at three highest MS spectral points. The efficiency of I-GPA was demonstrated by automatically identifying 619 site-specific N-glycopeptides with FDR ≤ 1%, and simultaneously quantifying 598 N-glycopeptides, from human plasma samples that are known to contain highly glycosylated proteins. Thus, I-GPA platform could make a major breakthrough in high-throughput mapping of complex N-glycoproteomes, which can be applied to biomarker discovery and ongoing global human proteome project.

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